Henrywood and Agarwal, Equation (12)

Percentage Accurate: 66.0% → 75.9%
Time: 9.2s
Alternatives: 15
Speedup: 2.0×

Specification

?
\[\begin{array}{l} \\ \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \end{array} \]
(FPCore (d h l M D)
 :precision binary64
 (*
  (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
  (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M D) (* 2.0 d)) 2.0)) (/ h l)))))
double code(double d, double h, double l, double M, double D) {
	return (pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)));
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(d, h, l, m, d_1)
use fmin_fmax_functions
    real(8), intent (in) :: d
    real(8), intent (in) :: h
    real(8), intent (in) :: l
    real(8), intent (in) :: m
    real(8), intent (in) :: d_1
    code = (((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))
end function
public static double code(double d, double h, double l, double M, double D) {
	return (Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)));
}
def code(d, h, l, M, D):
	return (math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)))
function code(d, h, l, M, D)
	return Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l))))
end
function tmp = code(d, h, l, M, D)
	tmp = (((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M * D) / (2.0 * d)) ^ 2.0)) * (h / l)));
end
code[d_, h_, l_, M_, D_] := N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right)
\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 15 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 66.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \end{array} \]
(FPCore (d h l M D)
 :precision binary64
 (*
  (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
  (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M D) (* 2.0 d)) 2.0)) (/ h l)))))
double code(double d, double h, double l, double M, double D) {
	return (pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)));
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(d, h, l, m, d_1)
use fmin_fmax_functions
    real(8), intent (in) :: d
    real(8), intent (in) :: h
    real(8), intent (in) :: l
    real(8), intent (in) :: m
    real(8), intent (in) :: d_1
    code = (((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))
end function
public static double code(double d, double h, double l, double M, double D) {
	return (Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)));
}
def code(d, h, l, M, D):
	return (math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M * D) / (2.0 * d)), 2.0)) * (h / l)))
function code(d, h, l, M, D)
	return Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l))))
end
function tmp = code(d, h, l, M, D)
	tmp = (((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M * D) / (2.0 * d)) ^ 2.0)) * (h / l)));
end
code[d_, h_, l_, M_, D_] := N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right)
\end{array}

Alternative 1: 75.9% accurate, 1.2× speedup?

\[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := 1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\\ \mathbf{if}\;d \leq -5.6 \cdot 10^{-93}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\ \mathbf{elif}\;d \leq -5 \cdot 10^{-310}:\\ \;\;\;\;\left(\left(-d\right) \cdot {\left(\ell \cdot h\right)}^{-0.5}\right) \cdot t\_0\\ \mathbf{elif}\;d \leq 1.6 \cdot 10^{-134}:\\ \;\;\;\;\left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\frac{\sqrt{d}}{\sqrt{h}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M\_m}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\ \end{array} \end{array} \]
M_m = (fabs.f64 M)
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
(FPCore (d h l M_m D)
 :precision binary64
 (let* ((t_0 (- 1.0 (/ (* (* (pow (/ (* D M_m) (* 2.0 d)) 2.0) 0.5) h) l))))
   (if (<= d -5.6e-93)
     (* (* (sqrt (/ d l)) (sqrt (/ d h))) t_0)
     (if (<= d -5e-310)
       (* (* (- d) (pow (* l h) -0.5)) t_0)
       (if (<= d 1.6e-134)
         (*
          (* (sqrt (pow (* l h) -1.0)) d)
          (-
           1.0
           (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
         (*
          (* (/ (sqrt d) (sqrt h)) (pow (/ d l) (/ 1.0 2.0)))
          (- 1.0 (/ (* (* (pow (* (/ M_m 2.0) (/ D d)) 2.0) 0.5) h) l))))))))
M_m = fabs(M);
assert(d < h && h < l && l < M_m && M_m < D);
double code(double d, double h, double l, double M_m, double D) {
	double t_0 = 1.0 - (((pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l);
	double tmp;
	if (d <= -5.6e-93) {
		tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0;
	} else if (d <= -5e-310) {
		tmp = (-d * pow((l * h), -0.5)) * t_0;
	} else if (d <= 1.6e-134) {
		tmp = (sqrt(pow((l * h), -1.0)) * d) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)));
	} else {
		tmp = ((sqrt(d) / sqrt(h)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((pow(((M_m / 2.0) * (D / d)), 2.0) * 0.5) * h) / l));
	}
	return tmp;
}
M_m =     private
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(d, h, l, m_m, d_1)
use fmin_fmax_functions
    real(8), intent (in) :: d
    real(8), intent (in) :: h
    real(8), intent (in) :: l
    real(8), intent (in) :: m_m
    real(8), intent (in) :: d_1
    real(8) :: t_0
    real(8) :: tmp
    t_0 = 1.0d0 - ((((((d_1 * m_m) / (2.0d0 * d)) ** 2.0d0) * 0.5d0) * h) / l)
    if (d <= (-5.6d-93)) then
        tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0
    else if (d <= (-5d-310)) then
        tmp = (-d * ((l * h) ** (-0.5d0))) * t_0
    else if (d <= 1.6d-134) then
        tmp = (sqrt(((l * h) ** (-1.0d0))) * d) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m_m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))
    else
        tmp = ((sqrt(d) / sqrt(h)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - ((((((m_m / 2.0d0) * (d_1 / d)) ** 2.0d0) * 0.5d0) * h) / l))
    end if
    code = tmp
end function
M_m = Math.abs(M);
assert d < h && h < l && l < M_m && M_m < D;
public static double code(double d, double h, double l, double M_m, double D) {
	double t_0 = 1.0 - (((Math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l);
	double tmp;
	if (d <= -5.6e-93) {
		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * t_0;
	} else if (d <= -5e-310) {
		tmp = (-d * Math.pow((l * h), -0.5)) * t_0;
	} else if (d <= 1.6e-134) {
		tmp = (Math.sqrt(Math.pow((l * h), -1.0)) * d) * (1.0 - (((1.0 / 2.0) * Math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)));
	} else {
		tmp = ((Math.sqrt(d) / Math.sqrt(h)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((Math.pow(((M_m / 2.0) * (D / d)), 2.0) * 0.5) * h) / l));
	}
	return tmp;
}
M_m = math.fabs(M)
[d, h, l, M_m, D] = sort([d, h, l, M_m, D])
def code(d, h, l, M_m, D):
	t_0 = 1.0 - (((math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l)
	tmp = 0
	if d <= -5.6e-93:
		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * t_0
	elif d <= -5e-310:
		tmp = (-d * math.pow((l * h), -0.5)) * t_0
	elif d <= 1.6e-134:
		tmp = (math.sqrt(math.pow((l * h), -1.0)) * d) * (1.0 - (((1.0 / 2.0) * math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))
	else:
		tmp = ((math.sqrt(d) / math.sqrt(h)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((math.pow(((M_m / 2.0) * (D / d)), 2.0) * 0.5) * h) / l))
	return tmp
M_m = abs(M)
d, h, l, M_m, D = sort([d, h, l, M_m, D])
function code(d, h, l, M_m, D)
	t_0 = Float64(1.0 - Float64(Float64(Float64((Float64(Float64(D * M_m) / Float64(2.0 * d)) ^ 2.0) * 0.5) * h) / l))
	tmp = 0.0
	if (d <= -5.6e-93)
		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * t_0);
	elseif (d <= -5e-310)
		tmp = Float64(Float64(Float64(-d) * (Float64(l * h) ^ -0.5)) * t_0);
	elseif (d <= 1.6e-134)
		tmp = Float64(Float64(sqrt((Float64(l * h) ^ -1.0)) * d) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l))));
	else
		tmp = Float64(Float64(Float64(sqrt(d) / sqrt(h)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64((Float64(Float64(M_m / 2.0) * Float64(D / d)) ^ 2.0) * 0.5) * h) / l)));
	end
	return tmp
end
M_m = abs(M);
d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
function tmp_2 = code(d, h, l, M_m, D)
	t_0 = 1.0 - ((((((D * M_m) / (2.0 * d)) ^ 2.0) * 0.5) * h) / l);
	tmp = 0.0;
	if (d <= -5.6e-93)
		tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0;
	elseif (d <= -5e-310)
		tmp = (-d * ((l * h) ^ -0.5)) * t_0;
	elseif (d <= 1.6e-134)
		tmp = (sqrt(((l * h) ^ -1.0)) * d) * (1.0 - (((1.0 / 2.0) * (((M_m * D) / (2.0 * d)) ^ 2.0)) * (h / l)));
	else
		tmp = ((sqrt(d) / sqrt(h)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - ((((((M_m / 2.0) * (D / d)) ^ 2.0) * 0.5) * h) / l));
	end
	tmp_2 = tmp;
end
M_m = N[Abs[M], $MachinePrecision]
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(1.0 - N[(N[(N[(N[Power[N[(N[(D * M$95$m), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 0.5), $MachinePrecision] * h), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[d, -5.6e-93], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision], If[LessEqual[d, -5e-310], N[(N[((-d) * N[Power[N[(l * h), $MachinePrecision], -0.5], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision], If[LessEqual[d, 1.6e-134], N[(N[(N[Sqrt[N[Power[N[(l * h), $MachinePrecision], -1.0], $MachinePrecision]], $MachinePrecision] * d), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(N[Sqrt[d], $MachinePrecision] / N[Sqrt[h], $MachinePrecision]), $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(N[Power[N[(N[(M$95$m / 2.0), $MachinePrecision] * N[(D / d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 0.5), $MachinePrecision] * h), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
M_m = \left|M\right|
\\
[d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
\\
\begin{array}{l}
t_0 := 1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\\
\mathbf{if}\;d \leq -5.6 \cdot 10^{-93}:\\
\;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\

\mathbf{elif}\;d \leq -5 \cdot 10^{-310}:\\
\;\;\;\;\left(\left(-d\right) \cdot {\left(\ell \cdot h\right)}^{-0.5}\right) \cdot t\_0\\

\mathbf{elif}\;d \leq 1.6 \cdot 10^{-134}:\\
\;\;\;\;\left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right)\\

\mathbf{else}:\\
\;\;\;\;\left(\frac{\sqrt{d}}{\sqrt{h}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M\_m}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 4 regimes
  2. if d < -5.59999999999999997e-93

    1. Initial program 77.0%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
      2. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
      5. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      8. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
      10. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
    4. Applied rewrites79.4%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
    5. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. sqr-powN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. lift-/.f6479.2

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    6. Applied rewrites79.2%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    7. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. frac-timesN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. *-commutativeN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-*.f6479.2

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    8. Applied rewrites79.2%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    9. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \color{blue}{\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. lift-pow.f64N/A

        \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. pow-prod-upN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      13. pow1/2N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      14. pow1/2N/A

        \[\leadsto \left(\sqrt{\frac{d}{h}} \cdot \color{blue}{\sqrt{\frac{d}{\ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      15. *-commutativeN/A

        \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      16. lift-sqrt.f64N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      17. lift-/.f64N/A

        \[\leadsto \left(\sqrt{\color{blue}{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      18. lift-sqrt.f64N/A

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \color{blue}{\sqrt{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      19. lift-/.f64N/A

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\color{blue}{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      20. lift-*.f6479.3

        \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    10. Applied rewrites79.3%

      \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

    if -5.59999999999999997e-93 < d < -4.999999999999985e-310

    1. Initial program 48.4%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
      2. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
      5. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      8. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
      10. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
    4. Applied rewrites47.6%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
    5. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. sqr-powN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. lift-/.f6447.5

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    6. Applied rewrites47.5%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    7. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. frac-timesN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. *-commutativeN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-*.f6448.6

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    8. Applied rewrites48.6%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    9. Taylor expanded in h around -inf

      \[\leadsto \color{blue}{\left(\left(d \cdot {\left(\sqrt{-1}\right)}^{2}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
    10. Step-by-step derivation
      1. metadata-evalN/A

        \[\leadsto \left(\left(d \cdot {\left(\sqrt{-1}\right)}^{2}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. pow-prod-upN/A

        \[\leadsto \left(\left(d \cdot \color{blue}{{\left(\sqrt{-1}\right)}^{2}}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. metadata-evalN/A

        \[\leadsto \left(\left(d \cdot {\left(\sqrt{-1}\right)}^{\color{blue}{2}}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. pow1/2N/A

        \[\leadsto \left(\left(\color{blue}{d} \cdot {\left(\sqrt{-1}\right)}^{2}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. pow1/2N/A

        \[\leadsto \left(\left(d \cdot \color{blue}{{\left(\sqrt{-1}\right)}^{2}}\right) \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\left(d \cdot {\left(\sqrt{-1}\right)}^{2}\right)} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. sqrt-pow2N/A

        \[\leadsto \left(\left(d \cdot {-1}^{\left(\frac{2}{2}\right)}\right) \cdot \sqrt{\frac{1}{\color{blue}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. metadata-evalN/A

        \[\leadsto \left(\left(d \cdot {-1}^{1}\right) \cdot \sqrt{\frac{1}{h \cdot \color{blue}{\ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. metadata-evalN/A

        \[\leadsto \left(\left(d \cdot -1\right) \cdot \sqrt{\frac{1}{\color{blue}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. *-commutativeN/A

        \[\leadsto \left(\left(-1 \cdot d\right) \cdot \sqrt{\color{blue}{\frac{1}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. mul-1-negN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(d\right)\right) \cdot \sqrt{\color{blue}{\frac{1}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. lower-*.f64N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(d\right)\right) \cdot \color{blue}{\sqrt{\frac{1}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      13. lower-neg.f64N/A

        \[\leadsto \left(\left(-d\right) \cdot \sqrt{\color{blue}{\frac{1}{h \cdot \ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      14. inv-powN/A

        \[\leadsto \left(\left(-d\right) \cdot \sqrt{{\left(h \cdot \ell\right)}^{-1}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      15. *-commutativeN/A

        \[\leadsto \left(\left(-d\right) \cdot \sqrt{{\left(\ell \cdot h\right)}^{-1}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      16. sqrt-pow1N/A

        \[\leadsto \left(\left(-d\right) \cdot {\left(\ell \cdot h\right)}^{\color{blue}{\left(\frac{-1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
    11. Applied rewrites64.1%

      \[\leadsto \color{blue}{\left(\left(-d\right) \cdot {\left(\ell \cdot h\right)}^{-0.5}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

    if -4.999999999999985e-310 < d < 1.6000000000000001e-134

    1. Initial program 41.0%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in d around 0

      \[\leadsto \color{blue}{\left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      3. lower-sqrt.f64N/A

        \[\leadsto \left(\sqrt{\frac{1}{h \cdot \ell}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. inv-powN/A

        \[\leadsto \left(\sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      5. lower-pow.f64N/A

        \[\leadsto \left(\sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. *-commutativeN/A

        \[\leadsto \left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lower-*.f6457.9

        \[\leadsto \left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    5. Applied rewrites57.9%

      \[\leadsto \color{blue}{\left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]

    if 1.6000000000000001e-134 < d

    1. Initial program 74.9%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
      2. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
      5. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      8. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
      10. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
    4. Applied rewrites77.3%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
    5. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\frac{1}{2}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. pow1/2N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. sqrt-divN/A

        \[\leadsto \left(\color{blue}{\frac{\sqrt{d}}{\sqrt{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lower-/.f64N/A

        \[\leadsto \left(\color{blue}{\frac{\sqrt{d}}{\sqrt{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-sqrt.f64N/A

        \[\leadsto \left(\frac{\color{blue}{\sqrt{d}}}{\sqrt{h}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lower-sqrt.f6485.9

        \[\leadsto \left(\frac{\sqrt{d}}{\color{blue}{\sqrt{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    6. Applied rewrites85.9%

      \[\leadsto \left(\color{blue}{\frac{\sqrt{d}}{\sqrt{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
  3. Recombined 4 regimes into one program.
  4. Add Preprocessing

Alternative 2: 69.3% accurate, 0.4× speedup?

\[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := 1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\\ t_1 := \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot t\_0\\ \mathbf{if}\;t\_1 \leq 2 \cdot 10^{+292}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\ \mathbf{elif}\;t\_1 \leq \infty:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \mathbf{else}:\\ \;\;\;\;\frac{\mathsf{fma}\left(-0.125 \cdot \left(D \cdot \frac{M\_m \cdot M\_m}{d}\right), \sqrt{{\left(\frac{h}{\ell}\right)}^{3}}, \sqrt{\frac{h}{\ell}} \cdot \frac{d}{D}\right)}{h} \cdot D\\ \end{array} \end{array} \]
M_m = (fabs.f64 M)
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
(FPCore (d h l M_m D)
 :precision binary64
 (let* ((t_0
         (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
        (t_1 (* (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0))) t_0)))
   (if (<= t_1 2e+292)
     (* (* (sqrt (/ d l)) (sqrt (/ d h))) t_0)
     (if (<= t_1 INFINITY)
       (* (/ 1.0 (* (sqrt l) (sqrt h))) d)
       (*
        (/
         (fma
          (* -0.125 (* D (/ (* M_m M_m) d)))
          (sqrt (pow (/ h l) 3.0))
          (* (sqrt (/ h l)) (/ d D)))
         h)
        D)))))
M_m = fabs(M);
assert(d < h && h < l && l < M_m && M_m < D);
double code(double d, double h, double l, double M_m, double D) {
	double t_0 = 1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l));
	double t_1 = (pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * t_0;
	double tmp;
	if (t_1 <= 2e+292) {
		tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0;
	} else if (t_1 <= ((double) INFINITY)) {
		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
	} else {
		tmp = (fma((-0.125 * (D * ((M_m * M_m) / d))), sqrt(pow((h / l), 3.0)), (sqrt((h / l)) * (d / D))) / h) * D;
	}
	return tmp;
}
M_m = abs(M)
d, h, l, M_m, D = sort([d, h, l, M_m, D])
function code(d, h, l, M_m, D)
	t_0 = Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))
	t_1 = Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * t_0)
	tmp = 0.0
	if (t_1 <= 2e+292)
		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * t_0);
	elseif (t_1 <= Inf)
		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
	else
		tmp = Float64(Float64(fma(Float64(-0.125 * Float64(D * Float64(Float64(M_m * M_m) / d))), sqrt((Float64(h / l) ^ 3.0)), Float64(sqrt(Float64(h / l)) * Float64(d / D))) / h) * D);
	end
	return tmp
end
M_m = N[Abs[M], $MachinePrecision]
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]}, If[LessEqual[t$95$1, 2e+292], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision], If[LessEqual[t$95$1, Infinity], N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision], N[(N[(N[(N[(-0.125 * N[(D * N[(N[(M$95$m * M$95$m), $MachinePrecision] / d), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[Power[N[(h / l), $MachinePrecision], 3.0], $MachinePrecision]], $MachinePrecision] + N[(N[Sqrt[N[(h / l), $MachinePrecision]], $MachinePrecision] * N[(d / D), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / h), $MachinePrecision] * D), $MachinePrecision]]]]]
\begin{array}{l}
M_m = \left|M\right|
\\
[d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
\\
\begin{array}{l}
t_0 := 1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\\
t_1 := \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot t\_0\\
\mathbf{if}\;t\_1 \leq 2 \cdot 10^{+292}:\\
\;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\

\mathbf{elif}\;t\_1 \leq \infty:\\
\;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\

\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(-0.125 \cdot \left(D \cdot \frac{M\_m \cdot M\_m}{d}\right), \sqrt{{\left(\frac{h}{\ell}\right)}^{3}}, \sqrt{\frac{h}{\ell}} \cdot \frac{d}{D}\right)}{h} \cdot D\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < 2e292

    1. Initial program 86.6%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \color{blue}{\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      3. lift-pow.f64N/A

        \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      5. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      8. *-commutativeN/A

        \[\leadsto \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      9. lower-*.f64N/A

        \[\leadsto \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      11. pow1/2N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{\ell}}} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      12. lower-sqrt.f64N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{\ell}}} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      13. lift-/.f64N/A

        \[\leadsto \left(\sqrt{\color{blue}{\frac{d}{\ell}}} \cdot {\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      14. metadata-evalN/A

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot {\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      15. pow1/2N/A

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \color{blue}{\sqrt{\frac{d}{h}}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      16. lower-sqrt.f64N/A

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \color{blue}{\sqrt{\frac{d}{h}}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      17. lift-/.f6486.6

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\color{blue}{\frac{d}{h}}}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    4. Applied rewrites86.6%

      \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]

    if 2e292 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < +inf.0

    1. Initial program 52.7%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in d around inf

      \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
      3. lower-sqrt.f64N/A

        \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
      4. inv-powN/A

        \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
      5. lower-pow.f64N/A

        \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
      6. *-commutativeN/A

        \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
      7. lower-*.f6448.7

        \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
    5. Applied rewrites48.7%

      \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
    6. Step-by-step derivation
      1. lift-sqrt.f64N/A

        \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
      2. lift-*.f64N/A

        \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
      3. lift-pow.f64N/A

        \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
      5. inv-powN/A

        \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
      6. sqrt-divN/A

        \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
      7. metadata-evalN/A

        \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
      8. lower-/.f64N/A

        \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
      9. *-commutativeN/A

        \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
      10. lower-sqrt.f64N/A

        \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
      11. lift-*.f6448.7

        \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
    7. Applied rewrites48.7%

      \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
    8. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
      2. lift-sqrt.f64N/A

        \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
      3. sqrt-prodN/A

        \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
      4. lower-*.f64N/A

        \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
      5. lower-sqrt.f64N/A

        \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
      6. lower-sqrt.f6450.1

        \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
    9. Applied rewrites50.1%

      \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]

    if +inf.0 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

    1. Initial program 0.0%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in D around inf

      \[\leadsto \color{blue}{{D}^{2} \cdot \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
    5. Applied rewrites11.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-0.125 \cdot \frac{M \cdot M}{d}, \sqrt{\frac{h}{{\ell}^{3}}}, \frac{d}{D \cdot D} \cdot \sqrt{{\left(\ell \cdot h\right)}^{-1}}\right) \cdot \left(D \cdot D\right)} \]
    6. Applied rewrites12.3%

      \[\leadsto \left(\mathsf{fma}\left(\frac{d}{D \cdot D}, {\left(\ell \cdot h\right)}^{-0.5}, \left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot D\right) \cdot \color{blue}{D} \]
    7. Taylor expanded in h around 0

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{D \cdot {M}^{2}}{d} \cdot \sqrt{\frac{{h}^{3}}{{\ell}^{3}}}\right) + \frac{d}{D} \cdot \sqrt{\frac{h}{\ell}}}{h} \cdot D \]
    8. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{D \cdot {M}^{2}}{d} \cdot \sqrt{\frac{{h}^{3}}{{\ell}^{3}}}\right) + \frac{d}{D} \cdot \sqrt{\frac{h}{\ell}}}{h} \cdot D \]
    9. Applied rewrites19.2%

      \[\leadsto \frac{\mathsf{fma}\left(-0.125 \cdot \left(D \cdot \frac{M \cdot M}{d}\right), \sqrt{{\left(\frac{h}{\ell}\right)}^{3}}, \sqrt{\frac{h}{\ell}} \cdot \frac{d}{D}\right)}{h} \cdot D \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 3: 63.9% accurate, 0.7× speedup?

\[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -1 \cdot 10^{-189}:\\ \;\;\;\;\sqrt{\frac{d}{\ell} \cdot \frac{d}{h}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\ \end{array} \end{array} \]
M_m = (fabs.f64 M)
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
(FPCore (d h l M_m D)
 :precision binary64
 (if (<=
      (*
       (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
       (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
      -1e-189)
   (*
    (sqrt (* (/ d l) (/ d h)))
    (- 1.0 (/ (* (* (pow (/ (* D M_m) (* 2.0 d)) 2.0) 0.5) h) l)))
   (* (* (sqrt (/ d l)) (sqrt (/ d h))) 1.0)))
M_m = fabs(M);
assert(d < h && h < l && l < M_m && M_m < D);
double code(double d, double h, double l, double M_m, double D) {
	double tmp;
	if (((pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -1e-189) {
		tmp = sqrt(((d / l) * (d / h))) * (1.0 - (((pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l));
	} else {
		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
	}
	return tmp;
}
M_m =     private
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(d, h, l, m_m, d_1)
use fmin_fmax_functions
    real(8), intent (in) :: d
    real(8), intent (in) :: h
    real(8), intent (in) :: l
    real(8), intent (in) :: m_m
    real(8), intent (in) :: d_1
    real(8) :: tmp
    if (((((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m_m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))) <= (-1d-189)) then
        tmp = sqrt(((d / l) * (d / h))) * (1.0d0 - ((((((d_1 * m_m) / (2.0d0 * d)) ** 2.0d0) * 0.5d0) * h) / l))
    else
        tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0d0
    end if
    code = tmp
end function
M_m = Math.abs(M);
assert d < h && h < l && l < M_m && M_m < D;
public static double code(double d, double h, double l, double M_m, double D) {
	double tmp;
	if (((Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -1e-189) {
		tmp = Math.sqrt(((d / l) * (d / h))) * (1.0 - (((Math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l));
	} else {
		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * 1.0;
	}
	return tmp;
}
M_m = math.fabs(M)
[d, h, l, M_m, D] = sort([d, h, l, M_m, D])
def code(d, h, l, M_m, D):
	tmp = 0
	if ((math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -1e-189:
		tmp = math.sqrt(((d / l) * (d / h))) * (1.0 - (((math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l))
	else:
		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * 1.0
	return tmp
M_m = abs(M)
d, h, l, M_m, D = sort([d, h, l, M_m, D])
function code(d, h, l, M_m, D)
	tmp = 0.0
	if (Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))) <= -1e-189)
		tmp = Float64(sqrt(Float64(Float64(d / l) * Float64(d / h))) * Float64(1.0 - Float64(Float64(Float64((Float64(Float64(D * M_m) / Float64(2.0 * d)) ^ 2.0) * 0.5) * h) / l)));
	else
		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * 1.0);
	end
	return tmp
end
M_m = abs(M);
d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
function tmp_2 = code(d, h, l, M_m, D)
	tmp = 0.0;
	if (((((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M_m * D) / (2.0 * d)) ^ 2.0)) * (h / l)))) <= -1e-189)
		tmp = sqrt(((d / l) * (d / h))) * (1.0 - ((((((D * M_m) / (2.0 * d)) ^ 2.0) * 0.5) * h) / l));
	else
		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
	end
	tmp_2 = tmp;
end
M_m = N[Abs[M], $MachinePrecision]
NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
code[d_, h_, l_, M$95$m_, D_] := If[LessEqual[N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -1e-189], N[(N[Sqrt[N[(N[(d / l), $MachinePrecision] * N[(d / h), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(1.0 - N[(N[(N[(N[Power[N[(N[(D * M$95$m), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 0.5), $MachinePrecision] * h), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 1.0), $MachinePrecision]]
\begin{array}{l}
M_m = \left|M\right|
\\
[d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
\\
\begin{array}{l}
\mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -1 \cdot 10^{-189}:\\
\;\;\;\;\sqrt{\frac{d}{\ell} \cdot \frac{d}{h}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\

\mathbf{else}:\\
\;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < -1.00000000000000007e-189

    1. Initial program 86.3%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
      2. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
      5. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      8. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
      10. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
    4. Applied rewrites85.5%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
    5. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. sqr-powN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. lower-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. lift-/.f6485.5

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    6. Applied rewrites85.5%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    7. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. frac-timesN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. *-commutativeN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lower-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lower-*.f6486.0

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    8. Applied rewrites86.0%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    9. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \color{blue}{\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      4. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      5. lift-pow.f64N/A

        \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      6. lift-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      7. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      8. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      9. lift-/.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      10. lift-pow.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      11. pow-prod-upN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      12. metadata-evalN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      13. pow1/2N/A

        \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      14. pow1/2N/A

        \[\leadsto \left(\sqrt{\frac{d}{h}} \cdot \color{blue}{\sqrt{\frac{d}{\ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      15. *-commutativeN/A

        \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      16. sqrt-unprodN/A

        \[\leadsto \color{blue}{\sqrt{\frac{d}{\ell} \cdot \frac{d}{h}}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      17. lower-sqrt.f64N/A

        \[\leadsto \color{blue}{\sqrt{\frac{d}{\ell} \cdot \frac{d}{h}}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      18. lower-*.f64N/A

        \[\leadsto \sqrt{\color{blue}{\frac{d}{\ell} \cdot \frac{d}{h}}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      19. lift-/.f64N/A

        \[\leadsto \sqrt{\color{blue}{\frac{d}{\ell}} \cdot \frac{d}{h}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
      20. lift-/.f6474.6

        \[\leadsto \sqrt{\frac{d}{\ell} \cdot \color{blue}{\frac{d}{h}}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
    10. Applied rewrites74.6%

      \[\leadsto \color{blue}{\sqrt{\frac{d}{\ell} \cdot \frac{d}{h}}} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

    if -1.00000000000000007e-189 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

    1. Initial program 55.7%

      \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in D around inf

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
    5. Applied rewrites29.4%

      \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
    6. Applied rewrites28.9%

      \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
    7. Taylor expanded in d around inf

      \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
    8. Step-by-step derivation
      1. Applied rewrites58.4%

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
    9. Recombined 2 regimes into one program.
    10. Add Preprocessing

    Alternative 4: 57.8% accurate, 0.8× speedup?

    \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\ \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -1 \cdot 10^{-74}:\\ \;\;\;\;t\_0 \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot 1\\ \end{array} \end{array} \]
    M_m = (fabs.f64 M)
    NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
    (FPCore (d h l M_m D)
     :precision binary64
     (let* ((t_0 (* (sqrt (/ d l)) (sqrt (/ d h)))))
       (if (<=
            (*
             (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
             (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
            -1e-74)
         (*
          t_0
          (* (/ (fma (/ (* (* (* M_m M_m) h) D) (* d d)) -0.125 (/ l D)) l) D))
         (* t_0 1.0))))
    M_m = fabs(M);
    assert(d < h && h < l && l < M_m && M_m < D);
    double code(double d, double h, double l, double M_m, double D) {
    	double t_0 = sqrt((d / l)) * sqrt((d / h));
    	double tmp;
    	if (((pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -1e-74) {
    		tmp = t_0 * ((fma(((((M_m * M_m) * h) * D) / (d * d)), -0.125, (l / D)) / l) * D);
    	} else {
    		tmp = t_0 * 1.0;
    	}
    	return tmp;
    }
    
    M_m = abs(M)
    d, h, l, M_m, D = sort([d, h, l, M_m, D])
    function code(d, h, l, M_m, D)
    	t_0 = Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h)))
    	tmp = 0.0
    	if (Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))) <= -1e-74)
    		tmp = Float64(t_0 * Float64(Float64(fma(Float64(Float64(Float64(Float64(M_m * M_m) * h) * D) / Float64(d * d)), -0.125, Float64(l / D)) / l) * D));
    	else
    		tmp = Float64(t_0 * 1.0);
    	end
    	return tmp
    end
    
    M_m = N[Abs[M], $MachinePrecision]
    NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
    code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -1e-74], N[(t$95$0 * N[(N[(N[(N[(N[(N[(N[(M$95$m * M$95$m), $MachinePrecision] * h), $MachinePrecision] * D), $MachinePrecision] / N[(d * d), $MachinePrecision]), $MachinePrecision] * -0.125 + N[(l / D), $MachinePrecision]), $MachinePrecision] / l), $MachinePrecision] * D), $MachinePrecision]), $MachinePrecision], N[(t$95$0 * 1.0), $MachinePrecision]]]
    
    \begin{array}{l}
    M_m = \left|M\right|
    \\
    [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
    \\
    \begin{array}{l}
    t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\
    \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -1 \cdot 10^{-74}:\\
    \;\;\;\;t\_0 \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;t\_0 \cdot 1\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < -9.99999999999999958e-75

      1. Initial program 86.0%

        \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      2. Add Preprocessing
      3. Taylor expanded in D around inf

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
        2. lower-*.f64N/A

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
      5. Applied rewrites52.6%

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
      6. Applied rewrites54.6%

        \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
      7. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \left(D \cdot \color{blue}{D}\right)\right) \]
        2. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \color{blue}{\left(D \cdot D\right)}\right) \]
        3. lift-fma.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(\color{blue}{D} \cdot D\right)\right) \]
        4. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        5. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        6. lift-/.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        7. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        8. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        9. lift-pow.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
        10. associate-*r*N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
        11. lower-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
      8. Applied rewrites56.1%

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\mathsf{fma}\left(-0.125, \left(M \cdot M\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}, {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
      9. Taylor expanded in l around 0

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
      10. Step-by-step derivation
        1. lower-/.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
        2. *-commutativeN/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} \cdot \frac{-1}{8} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
        3. lower-fma.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        4. lower-/.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        5. *-commutativeN/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        6. lower-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        7. lower-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        8. pow2N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        9. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        10. pow2N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        11. lift-*.f64N/A

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
        12. lower-/.f6457.8

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
      11. Applied rewrites57.8%

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]

      if -9.99999999999999958e-75 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

      1. Initial program 56.2%

        \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
      2. Add Preprocessing
      3. Taylor expanded in D around inf

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
        2. lower-*.f64N/A

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
      5. Applied rewrites29.4%

        \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
      6. Applied rewrites28.9%

        \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
      7. Taylor expanded in d around inf

        \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
      8. Step-by-step derivation
        1. Applied rewrites57.8%

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
      9. Recombined 2 regimes into one program.
      10. Add Preprocessing

      Alternative 5: 57.6% accurate, 0.8× speedup?

      \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\ \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -2 \cdot 10^{-45}:\\ \;\;\;\;t\_0 \cdot \left(\left(\left(\left(-0.125 \cdot \left(M\_m \cdot M\_m\right)\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot 1\\ \end{array} \end{array} \]
      M_m = (fabs.f64 M)
      NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
      (FPCore (d h l M_m D)
       :precision binary64
       (let* ((t_0 (* (sqrt (/ d l)) (sqrt (/ d h)))))
         (if (<=
              (*
               (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
               (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
              -2e-45)
           (* t_0 (* (* (* (* -0.125 (* M_m M_m)) (/ (/ h (* d d)) l)) D) D))
           (* t_0 1.0))))
      M_m = fabs(M);
      assert(d < h && h < l && l < M_m && M_m < D);
      double code(double d, double h, double l, double M_m, double D) {
      	double t_0 = sqrt((d / l)) * sqrt((d / h));
      	double tmp;
      	if (((pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -2e-45) {
      		tmp = t_0 * ((((-0.125 * (M_m * M_m)) * ((h / (d * d)) / l)) * D) * D);
      	} else {
      		tmp = t_0 * 1.0;
      	}
      	return tmp;
      }
      
      M_m =     private
      NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
      module fmin_fmax_functions
          implicit none
          private
          public fmax
          public fmin
      
          interface fmax
              module procedure fmax88
              module procedure fmax44
              module procedure fmax84
              module procedure fmax48
          end interface
          interface fmin
              module procedure fmin88
              module procedure fmin44
              module procedure fmin84
              module procedure fmin48
          end interface
      contains
          real(8) function fmax88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(4) function fmax44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(8) function fmax84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmax48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
          end function
          real(8) function fmin88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(4) function fmin44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(8) function fmin84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmin48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
          end function
      end module
      
      real(8) function code(d, h, l, m_m, d_1)
      use fmin_fmax_functions
          real(8), intent (in) :: d
          real(8), intent (in) :: h
          real(8), intent (in) :: l
          real(8), intent (in) :: m_m
          real(8), intent (in) :: d_1
          real(8) :: t_0
          real(8) :: tmp
          t_0 = sqrt((d / l)) * sqrt((d / h))
          if (((((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m_m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))) <= (-2d-45)) then
              tmp = t_0 * (((((-0.125d0) * (m_m * m_m)) * ((h / (d * d)) / l)) * d_1) * d_1)
          else
              tmp = t_0 * 1.0d0
          end if
          code = tmp
      end function
      
      M_m = Math.abs(M);
      assert d < h && h < l && l < M_m && M_m < D;
      public static double code(double d, double h, double l, double M_m, double D) {
      	double t_0 = Math.sqrt((d / l)) * Math.sqrt((d / h));
      	double tmp;
      	if (((Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -2e-45) {
      		tmp = t_0 * ((((-0.125 * (M_m * M_m)) * ((h / (d * d)) / l)) * D) * D);
      	} else {
      		tmp = t_0 * 1.0;
      	}
      	return tmp;
      }
      
      M_m = math.fabs(M)
      [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
      def code(d, h, l, M_m, D):
      	t_0 = math.sqrt((d / l)) * math.sqrt((d / h))
      	tmp = 0
      	if ((math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -2e-45:
      		tmp = t_0 * ((((-0.125 * (M_m * M_m)) * ((h / (d * d)) / l)) * D) * D)
      	else:
      		tmp = t_0 * 1.0
      	return tmp
      
      M_m = abs(M)
      d, h, l, M_m, D = sort([d, h, l, M_m, D])
      function code(d, h, l, M_m, D)
      	t_0 = Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h)))
      	tmp = 0.0
      	if (Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))) <= -2e-45)
      		tmp = Float64(t_0 * Float64(Float64(Float64(Float64(-0.125 * Float64(M_m * M_m)) * Float64(Float64(h / Float64(d * d)) / l)) * D) * D));
      	else
      		tmp = Float64(t_0 * 1.0);
      	end
      	return tmp
      end
      
      M_m = abs(M);
      d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
      function tmp_2 = code(d, h, l, M_m, D)
      	t_0 = sqrt((d / l)) * sqrt((d / h));
      	tmp = 0.0;
      	if (((((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M_m * D) / (2.0 * d)) ^ 2.0)) * (h / l)))) <= -2e-45)
      		tmp = t_0 * ((((-0.125 * (M_m * M_m)) * ((h / (d * d)) / l)) * D) * D);
      	else
      		tmp = t_0 * 1.0;
      	end
      	tmp_2 = tmp;
      end
      
      M_m = N[Abs[M], $MachinePrecision]
      NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
      code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -2e-45], N[(t$95$0 * N[(N[(N[(N[(-0.125 * N[(M$95$m * M$95$m), $MachinePrecision]), $MachinePrecision] * N[(N[(h / N[(d * d), $MachinePrecision]), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision] * D), $MachinePrecision] * D), $MachinePrecision]), $MachinePrecision], N[(t$95$0 * 1.0), $MachinePrecision]]]
      
      \begin{array}{l}
      M_m = \left|M\right|
      \\
      [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
      \\
      \begin{array}{l}
      t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\
      \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -2 \cdot 10^{-45}:\\
      \;\;\;\;t\_0 \cdot \left(\left(\left(\left(-0.125 \cdot \left(M\_m \cdot M\_m\right)\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;t\_0 \cdot 1\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < -1.99999999999999997e-45

        1. Initial program 86.0%

          \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
        2. Add Preprocessing
        3. Taylor expanded in D around inf

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
          2. lower-*.f64N/A

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
        5. Applied rewrites52.9%

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
        6. Applied rewrites54.9%

          \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
        7. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \left(D \cdot \color{blue}{D}\right)\right) \]
          2. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \color{blue}{\left(D \cdot D\right)}\right) \]
          3. lift-fma.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(\color{blue}{D} \cdot D\right)\right) \]
          4. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          5. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          6. lift-/.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          7. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          8. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          9. lift-pow.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
          10. associate-*r*N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
          11. lower-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
        8. Applied rewrites56.4%

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\mathsf{fma}\left(-0.125, \left(M \cdot M\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}, {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
        9. Taylor expanded in d around 0

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot D\right) \cdot D\right) \]
        10. Step-by-step derivation
          1. associate-/l*N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{h}{{d}^{2} \cdot \ell}\right)\right) \cdot D\right) \cdot D\right) \]
          2. associate-/r*N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{\frac{h}{{d}^{2}}}{\ell}\right)\right) \cdot D\right) \cdot D\right) \]
          3. pow2N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right)\right) \cdot D\right) \cdot D\right) \]
          4. lift-/.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right)\right) \cdot D\right) \cdot D\right) \]
          5. lift-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right)\right) \cdot D\right) \cdot D\right) \]
          6. lift-/.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\frac{-1}{8} \cdot \left({M}^{2} \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right)\right) \cdot D\right) \cdot D\right) \]
          7. associate-*r*N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\frac{-1}{8} \cdot {M}^{2}\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]
          8. lower-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\frac{-1}{8} \cdot {M}^{2}\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]
          9. lower-*.f64N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\frac{-1}{8} \cdot {M}^{2}\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]
          10. pow2N/A

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\frac{-1}{8} \cdot \left(M \cdot M\right)\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]
          11. lift-*.f6457.7

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(-0.125 \cdot \left(M \cdot M\right)\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]
        11. Applied rewrites57.7%

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(-0.125 \cdot \left(M \cdot M\right)\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}\right) \cdot D\right) \cdot D\right) \]

        if -1.99999999999999997e-45 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

        1. Initial program 56.4%

          \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
        2. Add Preprocessing
        3. Taylor expanded in D around inf

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
          2. lower-*.f64N/A

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
        5. Applied rewrites29.4%

          \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
        6. Applied rewrites28.8%

          \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
        7. Taylor expanded in d around inf

          \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
        8. Step-by-step derivation
          1. Applied rewrites57.5%

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
        9. Recombined 2 regimes into one program.
        10. Add Preprocessing

        Alternative 6: 57.0% accurate, 0.8× speedup?

        \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\ \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -5 \cdot 10^{-97}:\\ \;\;\;\;t\_0 \cdot \left(\frac{-0.125 \cdot \left(\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D\right)}{\left(d \cdot d\right) \cdot \ell} \cdot D\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot 1\\ \end{array} \end{array} \]
        M_m = (fabs.f64 M)
        NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
        (FPCore (d h l M_m D)
         :precision binary64
         (let* ((t_0 (* (sqrt (/ d l)) (sqrt (/ d h)))))
           (if (<=
                (*
                 (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
                 (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
                -5e-97)
             (* t_0 (* (/ (* -0.125 (* (* (* M_m M_m) h) D)) (* (* d d) l)) D))
             (* t_0 1.0))))
        M_m = fabs(M);
        assert(d < h && h < l && l < M_m && M_m < D);
        double code(double d, double h, double l, double M_m, double D) {
        	double t_0 = sqrt((d / l)) * sqrt((d / h));
        	double tmp;
        	if (((pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97) {
        		tmp = t_0 * (((-0.125 * (((M_m * M_m) * h) * D)) / ((d * d) * l)) * D);
        	} else {
        		tmp = t_0 * 1.0;
        	}
        	return tmp;
        }
        
        M_m =     private
        NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(8) function code(d, h, l, m_m, d_1)
        use fmin_fmax_functions
            real(8), intent (in) :: d
            real(8), intent (in) :: h
            real(8), intent (in) :: l
            real(8), intent (in) :: m_m
            real(8), intent (in) :: d_1
            real(8) :: t_0
            real(8) :: tmp
            t_0 = sqrt((d / l)) * sqrt((d / h))
            if (((((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m_m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))) <= (-5d-97)) then
                tmp = t_0 * ((((-0.125d0) * (((m_m * m_m) * h) * d_1)) / ((d * d) * l)) * d_1)
            else
                tmp = t_0 * 1.0d0
            end if
            code = tmp
        end function
        
        M_m = Math.abs(M);
        assert d < h && h < l && l < M_m && M_m < D;
        public static double code(double d, double h, double l, double M_m, double D) {
        	double t_0 = Math.sqrt((d / l)) * Math.sqrt((d / h));
        	double tmp;
        	if (((Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97) {
        		tmp = t_0 * (((-0.125 * (((M_m * M_m) * h) * D)) / ((d * d) * l)) * D);
        	} else {
        		tmp = t_0 * 1.0;
        	}
        	return tmp;
        }
        
        M_m = math.fabs(M)
        [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
        def code(d, h, l, M_m, D):
        	t_0 = math.sqrt((d / l)) * math.sqrt((d / h))
        	tmp = 0
        	if ((math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97:
        		tmp = t_0 * (((-0.125 * (((M_m * M_m) * h) * D)) / ((d * d) * l)) * D)
        	else:
        		tmp = t_0 * 1.0
        	return tmp
        
        M_m = abs(M)
        d, h, l, M_m, D = sort([d, h, l, M_m, D])
        function code(d, h, l, M_m, D)
        	t_0 = Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h)))
        	tmp = 0.0
        	if (Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))) <= -5e-97)
        		tmp = Float64(t_0 * Float64(Float64(Float64(-0.125 * Float64(Float64(Float64(M_m * M_m) * h) * D)) / Float64(Float64(d * d) * l)) * D));
        	else
        		tmp = Float64(t_0 * 1.0);
        	end
        	return tmp
        end
        
        M_m = abs(M);
        d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
        function tmp_2 = code(d, h, l, M_m, D)
        	t_0 = sqrt((d / l)) * sqrt((d / h));
        	tmp = 0.0;
        	if (((((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M_m * D) / (2.0 * d)) ^ 2.0)) * (h / l)))) <= -5e-97)
        		tmp = t_0 * (((-0.125 * (((M_m * M_m) * h) * D)) / ((d * d) * l)) * D);
        	else
        		tmp = t_0 * 1.0;
        	end
        	tmp_2 = tmp;
        end
        
        M_m = N[Abs[M], $MachinePrecision]
        NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
        code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-97], N[(t$95$0 * N[(N[(N[(-0.125 * N[(N[(N[(M$95$m * M$95$m), $MachinePrecision] * h), $MachinePrecision] * D), $MachinePrecision]), $MachinePrecision] / N[(N[(d * d), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] * D), $MachinePrecision]), $MachinePrecision], N[(t$95$0 * 1.0), $MachinePrecision]]]
        
        \begin{array}{l}
        M_m = \left|M\right|
        \\
        [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
        \\
        \begin{array}{l}
        t_0 := \sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\\
        \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -5 \cdot 10^{-97}:\\
        \;\;\;\;t\_0 \cdot \left(\frac{-0.125 \cdot \left(\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D\right)}{\left(d \cdot d\right) \cdot \ell} \cdot D\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;t\_0 \cdot 1\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < -4.9999999999999995e-97

          1. Initial program 86.1%

            \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
          2. Add Preprocessing
          3. Taylor expanded in D around inf

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
            2. lower-*.f64N/A

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
          5. Applied rewrites52.4%

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
          6. Applied rewrites54.3%

            \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
          7. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \left(D \cdot \color{blue}{D}\right)\right) \]
            2. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \color{blue}{\left(D \cdot D\right)}\right) \]
            3. lift-fma.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(\color{blue}{D} \cdot D\right)\right) \]
            4. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            5. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            6. lift-/.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            7. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            8. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            9. lift-pow.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
            10. associate-*r*N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
            11. lower-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
          8. Applied rewrites55.9%

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\mathsf{fma}\left(-0.125, \left(M \cdot M\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}, {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
          9. Taylor expanded in d around 0

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\frac{-1}{8} \cdot \frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2} \cdot \ell}\right) \cdot D\right) \]
          10. Step-by-step derivation
            1. associate-*r/N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(D \cdot \left({M}^{2} \cdot h\right)\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            2. lower-/.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(D \cdot \left({M}^{2} \cdot h\right)\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            3. lower-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(D \cdot \left({M}^{2} \cdot h\right)\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            4. *-commutativeN/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left({M}^{2} \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            5. lower-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left({M}^{2} \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            6. lower-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left({M}^{2} \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            7. pow2N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            8. lift-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            9. lower-*.f64N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{{d}^{2} \cdot \ell} \cdot D\right) \]
            10. pow2N/A

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{\left(d \cdot d\right) \cdot \ell} \cdot D\right) \]
            11. lift-*.f6455.1

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{-0.125 \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{\left(d \cdot d\right) \cdot \ell} \cdot D\right) \]
          11. Applied rewrites55.1%

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{-0.125 \cdot \left(\left(\left(M \cdot M\right) \cdot h\right) \cdot D\right)}{\left(d \cdot d\right) \cdot \ell} \cdot D\right) \]

          if -4.9999999999999995e-97 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

          1. Initial program 56.1%

            \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
          2. Add Preprocessing
          3. Taylor expanded in D around inf

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
            2. lower-*.f64N/A

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
          5. Applied rewrites29.5%

            \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
          6. Applied rewrites28.9%

            \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
          7. Taylor expanded in d around inf

            \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
          8. Step-by-step derivation
            1. Applied rewrites57.9%

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
          9. Recombined 2 regimes into one program.
          10. Add Preprocessing

          Alternative 7: 49.0% accurate, 0.9× speedup?

          \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -5 \cdot 10^{-97}:\\ \;\;\;\;\left(\left(\frac{M\_m \cdot M\_m}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\ \end{array} \end{array} \]
          M_m = (fabs.f64 M)
          NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
          (FPCore (d h l M_m D)
           :precision binary64
           (if (<=
                (*
                 (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0)))
                 (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M_m D) (* 2.0 d)) 2.0)) (/ h l))))
                -5e-97)
             (* (* (* (/ (* M_m M_m) d) -0.125) (sqrt (/ h (* (* l l) l)))) (* D D))
             (* (* (sqrt (/ d l)) (sqrt (/ d h))) 1.0)))
          M_m = fabs(M);
          assert(d < h && h < l && l < M_m && M_m < D);
          double code(double d, double h, double l, double M_m, double D) {
          	double tmp;
          	if (((pow((d / h), (1.0 / 2.0)) * pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97) {
          		tmp = ((((M_m * M_m) / d) * -0.125) * sqrt((h / ((l * l) * l)))) * (D * D);
          	} else {
          		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
          	}
          	return tmp;
          }
          
          M_m =     private
          NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
          module fmin_fmax_functions
              implicit none
              private
              public fmax
              public fmin
          
              interface fmax
                  module procedure fmax88
                  module procedure fmax44
                  module procedure fmax84
                  module procedure fmax48
              end interface
              interface fmin
                  module procedure fmin88
                  module procedure fmin44
                  module procedure fmin84
                  module procedure fmin48
              end interface
          contains
              real(8) function fmax88(x, y) result (res)
                  real(8), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(x, max(x, y), y /= y), x /= x)
              end function
              real(4) function fmax44(x, y) result (res)
                  real(4), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(y, merge(x, max(x, y), y /= y), x /= x)
              end function
              real(8) function fmax84(x, y) result(res)
                  real(8), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
              end function
              real(8) function fmax48(x, y) result(res)
                  real(4), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
              end function
              real(8) function fmin88(x, y) result (res)
                  real(8), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(x, min(x, y), y /= y), x /= x)
              end function
              real(4) function fmin44(x, y) result (res)
                  real(4), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(y, merge(x, min(x, y), y /= y), x /= x)
              end function
              real(8) function fmin84(x, y) result(res)
                  real(8), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
              end function
              real(8) function fmin48(x, y) result(res)
                  real(4), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
              end function
          end module
          
          real(8) function code(d, h, l, m_m, d_1)
          use fmin_fmax_functions
              real(8), intent (in) :: d
              real(8), intent (in) :: h
              real(8), intent (in) :: l
              real(8), intent (in) :: m_m
              real(8), intent (in) :: d_1
              real(8) :: tmp
              if (((((d / h) ** (1.0d0 / 2.0d0)) * ((d / l) ** (1.0d0 / 2.0d0))) * (1.0d0 - (((1.0d0 / 2.0d0) * (((m_m * d_1) / (2.0d0 * d)) ** 2.0d0)) * (h / l)))) <= (-5d-97)) then
                  tmp = ((((m_m * m_m) / d) * (-0.125d0)) * sqrt((h / ((l * l) * l)))) * (d_1 * d_1)
              else
                  tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0d0
              end if
              code = tmp
          end function
          
          M_m = Math.abs(M);
          assert d < h && h < l && l < M_m && M_m < D;
          public static double code(double d, double h, double l, double M_m, double D) {
          	double tmp;
          	if (((Math.pow((d / h), (1.0 / 2.0)) * Math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * Math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97) {
          		tmp = ((((M_m * M_m) / d) * -0.125) * Math.sqrt((h / ((l * l) * l)))) * (D * D);
          	} else {
          		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * 1.0;
          	}
          	return tmp;
          }
          
          M_m = math.fabs(M)
          [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
          def code(d, h, l, M_m, D):
          	tmp = 0
          	if ((math.pow((d / h), (1.0 / 2.0)) * math.pow((d / l), (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * math.pow(((M_m * D) / (2.0 * d)), 2.0)) * (h / l)))) <= -5e-97:
          		tmp = ((((M_m * M_m) / d) * -0.125) * math.sqrt((h / ((l * l) * l)))) * (D * D)
          	else:
          		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * 1.0
          	return tmp
          
          M_m = abs(M)
          d, h, l, M_m, D = sort([d, h, l, M_m, D])
          function code(d, h, l, M_m, D)
          	tmp = 0.0
          	if (Float64(Float64((Float64(d / h) ^ Float64(1.0 / 2.0)) * (Float64(d / l) ^ Float64(1.0 / 2.0))) * Float64(1.0 - Float64(Float64(Float64(1.0 / 2.0) * (Float64(Float64(M_m * D) / Float64(2.0 * d)) ^ 2.0)) * Float64(h / l)))) <= -5e-97)
          		tmp = Float64(Float64(Float64(Float64(Float64(M_m * M_m) / d) * -0.125) * sqrt(Float64(h / Float64(Float64(l * l) * l)))) * Float64(D * D));
          	else
          		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * 1.0);
          	end
          	return tmp
          end
          
          M_m = abs(M);
          d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
          function tmp_2 = code(d, h, l, M_m, D)
          	tmp = 0.0;
          	if (((((d / h) ^ (1.0 / 2.0)) * ((d / l) ^ (1.0 / 2.0))) * (1.0 - (((1.0 / 2.0) * (((M_m * D) / (2.0 * d)) ^ 2.0)) * (h / l)))) <= -5e-97)
          		tmp = ((((M_m * M_m) / d) * -0.125) * sqrt((h / ((l * l) * l)))) * (D * D);
          	else
          		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
          	end
          	tmp_2 = tmp;
          end
          
          M_m = N[Abs[M], $MachinePrecision]
          NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
          code[d_, h_, l_, M$95$m_, D_] := If[LessEqual[N[(N[(N[Power[N[(d / h), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Power[N[(d / l), $MachinePrecision], N[(1.0 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(1.0 / 2.0), $MachinePrecision] * N[Power[N[(N[(M$95$m * D), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[(h / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-97], N[(N[(N[(N[(N[(M$95$m * M$95$m), $MachinePrecision] / d), $MachinePrecision] * -0.125), $MachinePrecision] * N[Sqrt[N[(h / N[(N[(l * l), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(D * D), $MachinePrecision]), $MachinePrecision], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 1.0), $MachinePrecision]]
          
          \begin{array}{l}
          M_m = \left|M\right|
          \\
          [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
          \\
          \begin{array}{l}
          \mathbf{if}\;\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M\_m \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \leq -5 \cdot 10^{-97}:\\
          \;\;\;\;\left(\left(\frac{M\_m \cdot M\_m}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l)))) < -4.9999999999999995e-97

            1. Initial program 86.1%

              \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
            2. Add Preprocessing
            3. Taylor expanded in D around inf

              \[\leadsto \color{blue}{{D}^{2} \cdot \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \]
            4. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
              2. lower-*.f64N/A

                \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
            5. Applied rewrites23.8%

              \[\leadsto \color{blue}{\mathsf{fma}\left(-0.125 \cdot \frac{M \cdot M}{d}, \sqrt{\frac{h}{{\ell}^{3}}}, \frac{d}{D \cdot D} \cdot \sqrt{{\left(\ell \cdot h\right)}^{-1}}\right) \cdot \left(D \cdot D\right)} \]
            6. Taylor expanded in d around 0

              \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right)\right) \cdot \left(\color{blue}{D} \cdot D\right) \]
            7. Step-by-step derivation
              1. associate-*r*N/A

                \[\leadsto \left(\left(\frac{-1}{8} \cdot \frac{{M}^{2}}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              2. lower-*.f64N/A

                \[\leadsto \left(\left(\frac{-1}{8} \cdot \frac{{M}^{2}}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              3. *-commutativeN/A

                \[\leadsto \left(\left(\frac{{M}^{2}}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              4. lower-*.f64N/A

                \[\leadsto \left(\left(\frac{{M}^{2}}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              5. pow2N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              6. lift-*.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              7. lift-/.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              8. lift-pow.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              9. lift-/.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              10. lift-sqrt.f6430.9

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
            8. Applied rewrites30.9%

              \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(\color{blue}{D} \cdot D\right) \]
            9. Step-by-step derivation
              1. lift-pow.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              2. unpow3N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]
              3. unpow2N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{2} \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]
              4. lower-*.f64N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{2} \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]
              5. unpow2N/A

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]
              6. lower-*.f6430.9

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]
            10. Applied rewrites30.9%

              \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\right) \cdot \left(D \cdot D\right) \]

            if -4.9999999999999995e-97 < (*.f64 (*.f64 (pow.f64 (/.f64 d h) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64))) (pow.f64 (/.f64 d l) (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)))) (-.f64 #s(literal 1 binary64) (*.f64 (*.f64 (/.f64 #s(literal 1 binary64) #s(literal 2 binary64)) (pow.f64 (/.f64 (*.f64 M D) (*.f64 #s(literal 2 binary64) d)) #s(literal 2 binary64))) (/.f64 h l))))

            1. Initial program 56.1%

              \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
            2. Add Preprocessing
            3. Taylor expanded in D around inf

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
            4. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
              2. lower-*.f64N/A

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
            5. Applied rewrites29.5%

              \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
            6. Applied rewrites28.9%

              \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
            7. Taylor expanded in d around inf

              \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
            8. Step-by-step derivation
              1. Applied rewrites57.9%

                \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
            9. Recombined 2 regimes into one program.
            10. Add Preprocessing

            Alternative 8: 72.4% accurate, 1.5× speedup?

            \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := 1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\\ \mathbf{if}\;\ell \leq 3.4 \cdot 10^{-237}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\ \mathbf{elif}\;\ell \leq 7.2 \cdot 10^{+161}:\\ \;\;\;\;\left({\left(\ell \cdot h\right)}^{-0.5} \cdot d\right) \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \end{array} \end{array} \]
            M_m = (fabs.f64 M)
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            (FPCore (d h l M_m D)
             :precision binary64
             (let* ((t_0 (- 1.0 (/ (* (* (pow (/ (* D M_m) (* 2.0 d)) 2.0) 0.5) h) l))))
               (if (<= l 3.4e-237)
                 (* (* (sqrt (/ d l)) (sqrt (/ d h))) t_0)
                 (if (<= l 7.2e+161)
                   (* (* (pow (* l h) -0.5) d) t_0)
                   (* (/ 1.0 (* (sqrt l) (sqrt h))) d)))))
            M_m = fabs(M);
            assert(d < h && h < l && l < M_m && M_m < D);
            double code(double d, double h, double l, double M_m, double D) {
            	double t_0 = 1.0 - (((pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l);
            	double tmp;
            	if (l <= 3.4e-237) {
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0;
            	} else if (l <= 7.2e+161) {
            		tmp = (pow((l * h), -0.5) * d) * t_0;
            	} else {
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m =     private
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            module fmin_fmax_functions
                implicit none
                private
                public fmax
                public fmin
            
                interface fmax
                    module procedure fmax88
                    module procedure fmax44
                    module procedure fmax84
                    module procedure fmax48
                end interface
                interface fmin
                    module procedure fmin88
                    module procedure fmin44
                    module procedure fmin84
                    module procedure fmin48
                end interface
            contains
                real(8) function fmax88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(4) function fmax44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(8) function fmax84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmax48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                end function
                real(8) function fmin88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(4) function fmin44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(8) function fmin84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmin48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                end function
            end module
            
            real(8) function code(d, h, l, m_m, d_1)
            use fmin_fmax_functions
                real(8), intent (in) :: d
                real(8), intent (in) :: h
                real(8), intent (in) :: l
                real(8), intent (in) :: m_m
                real(8), intent (in) :: d_1
                real(8) :: t_0
                real(8) :: tmp
                t_0 = 1.0d0 - ((((((d_1 * m_m) / (2.0d0 * d)) ** 2.0d0) * 0.5d0) * h) / l)
                if (l <= 3.4d-237) then
                    tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0
                else if (l <= 7.2d+161) then
                    tmp = (((l * h) ** (-0.5d0)) * d) * t_0
                else
                    tmp = (1.0d0 / (sqrt(l) * sqrt(h))) * d
                end if
                code = tmp
            end function
            
            M_m = Math.abs(M);
            assert d < h && h < l && l < M_m && M_m < D;
            public static double code(double d, double h, double l, double M_m, double D) {
            	double t_0 = 1.0 - (((Math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l);
            	double tmp;
            	if (l <= 3.4e-237) {
            		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * t_0;
            	} else if (l <= 7.2e+161) {
            		tmp = (Math.pow((l * h), -0.5) * d) * t_0;
            	} else {
            		tmp = (1.0 / (Math.sqrt(l) * Math.sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m = math.fabs(M)
            [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
            def code(d, h, l, M_m, D):
            	t_0 = 1.0 - (((math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l)
            	tmp = 0
            	if l <= 3.4e-237:
            		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * t_0
            	elif l <= 7.2e+161:
            		tmp = (math.pow((l * h), -0.5) * d) * t_0
            	else:
            		tmp = (1.0 / (math.sqrt(l) * math.sqrt(h))) * d
            	return tmp
            
            M_m = abs(M)
            d, h, l, M_m, D = sort([d, h, l, M_m, D])
            function code(d, h, l, M_m, D)
            	t_0 = Float64(1.0 - Float64(Float64(Float64((Float64(Float64(D * M_m) / Float64(2.0 * d)) ^ 2.0) * 0.5) * h) / l))
            	tmp = 0.0
            	if (l <= 3.4e-237)
            		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * t_0);
            	elseif (l <= 7.2e+161)
            		tmp = Float64(Float64((Float64(l * h) ^ -0.5) * d) * t_0);
            	else
            		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
            	end
            	return tmp
            end
            
            M_m = abs(M);
            d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
            function tmp_2 = code(d, h, l, M_m, D)
            	t_0 = 1.0 - ((((((D * M_m) / (2.0 * d)) ^ 2.0) * 0.5) * h) / l);
            	tmp = 0.0;
            	if (l <= 3.4e-237)
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * t_0;
            	elseif (l <= 7.2e+161)
            		tmp = (((l * h) ^ -0.5) * d) * t_0;
            	else
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	end
            	tmp_2 = tmp;
            end
            
            M_m = N[Abs[M], $MachinePrecision]
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(1.0 - N[(N[(N[(N[Power[N[(N[(D * M$95$m), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 0.5), $MachinePrecision] * h), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[l, 3.4e-237], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision], If[LessEqual[l, 7.2e+161], N[(N[(N[Power[N[(l * h), $MachinePrecision], -0.5], $MachinePrecision] * d), $MachinePrecision] * t$95$0), $MachinePrecision], N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]]]]
            
            \begin{array}{l}
            M_m = \left|M\right|
            \\
            [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
            \\
            \begin{array}{l}
            t_0 := 1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\\
            \mathbf{if}\;\ell \leq 3.4 \cdot 10^{-237}:\\
            \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot t\_0\\
            
            \mathbf{elif}\;\ell \leq 7.2 \cdot 10^{+161}:\\
            \;\;\;\;\left({\left(\ell \cdot h\right)}^{-0.5} \cdot d\right) \cdot t\_0\\
            
            \mathbf{else}:\\
            \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 3 regimes
            2. if l < 3.4000000000000002e-237

              1. Initial program 66.9%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
                2. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
                5. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                8. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
                9. associate-*r/N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
                10. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
              4. Applied rewrites68.7%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
              5. Step-by-step derivation
                1. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. sqr-powN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. lift-/.f6468.6

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              6. Applied rewrites68.6%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              7. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. frac-timesN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. *-commutativeN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-*.f6468.9

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              8. Applied rewrites68.9%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              9. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. lift-pow.f64N/A

                  \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. pow-prod-upN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                13. pow1/2N/A

                  \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                14. pow1/2N/A

                  \[\leadsto \left(\sqrt{\frac{d}{h}} \cdot \color{blue}{\sqrt{\frac{d}{\ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                15. *-commutativeN/A

                  \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                16. lift-sqrt.f64N/A

                  \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                17. lift-/.f64N/A

                  \[\leadsto \left(\sqrt{\color{blue}{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                18. lift-sqrt.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \color{blue}{\sqrt{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                19. lift-/.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\color{blue}{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                20. lift-*.f6469.0

                  \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              10. Applied rewrites69.0%

                \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

              if 3.4000000000000002e-237 < l < 7.19999999999999967e161

              1. Initial program 70.5%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
                2. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
                5. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                8. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
                9. associate-*r/N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
                10. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
              4. Applied rewrites72.1%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
              5. Step-by-step derivation
                1. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. sqr-powN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. lift-/.f6472.0

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              6. Applied rewrites72.0%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              7. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. frac-timesN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. *-commutativeN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-*.f6472.6

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              8. Applied rewrites72.6%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              9. Taylor expanded in d around 0

                \[\leadsto \color{blue}{\left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
              10. Step-by-step derivation
                1. metadata-evalN/A

                  \[\leadsto \left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. pow-prod-upN/A

                  \[\leadsto \left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. metadata-evalN/A

                  \[\leadsto \left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. pow1/2N/A

                  \[\leadsto \left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. pow1/2N/A

                  \[\leadsto \left(d \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. *-commutativeN/A

                  \[\leadsto \left(\color{blue}{d} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. *-commutativeN/A

                  \[\leadsto \left(\sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. inv-powN/A

                  \[\leadsto \left(\sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. *-commutativeN/A

                  \[\leadsto \left(\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. sqrt-pow1N/A

                  \[\leadsto \left({\left(\ell \cdot h\right)}^{\left(\frac{-1}{2}\right)} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. metadata-evalN/A

                  \[\leadsto \left({\left(\ell \cdot h\right)}^{\frac{-1}{2}} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                13. lift-pow.f64N/A

                  \[\leadsto \left({\left(\ell \cdot h\right)}^{\frac{-1}{2}} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                14. lift-*.f6481.1

                  \[\leadsto \left({\left(\ell \cdot h\right)}^{-0.5} \cdot d\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              11. Applied rewrites81.1%

                \[\leadsto \color{blue}{\left({\left(\ell \cdot h\right)}^{-0.5} \cdot d\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

              if 7.19999999999999967e161 < l

              1. Initial program 49.9%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6447.2

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites47.2%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-sqrt.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                4. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. inv-powN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                6. sqrt-divN/A

                  \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                7. metadata-evalN/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                8. lower-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                10. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                11. lift-*.f6447.1

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              7. Applied rewrites47.1%

                \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                2. lift-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                3. sqrt-prodN/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                4. lower-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                5. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                6. lower-sqrt.f6464.0

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
              9. Applied rewrites64.0%

                \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
            3. Recombined 3 regimes into one program.
            4. Add Preprocessing

            Alternative 9: 69.5% accurate, 2.0× speedup?

            \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} \mathbf{if}\;\ell \leq 3.7 \cdot 10^{+100}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \end{array} \end{array} \]
            M_m = (fabs.f64 M)
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            (FPCore (d h l M_m D)
             :precision binary64
             (if (<= l 3.7e+100)
               (*
                (* (sqrt (/ d l)) (sqrt (/ d h)))
                (- 1.0 (/ (* (* (pow (/ (* D M_m) (* 2.0 d)) 2.0) 0.5) h) l)))
               (* (/ 1.0 (* (sqrt l) (sqrt h))) d)))
            M_m = fabs(M);
            assert(d < h && h < l && l < M_m && M_m < D);
            double code(double d, double h, double l, double M_m, double D) {
            	double tmp;
            	if (l <= 3.7e+100) {
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * (1.0 - (((pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l));
            	} else {
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m =     private
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            module fmin_fmax_functions
                implicit none
                private
                public fmax
                public fmin
            
                interface fmax
                    module procedure fmax88
                    module procedure fmax44
                    module procedure fmax84
                    module procedure fmax48
                end interface
                interface fmin
                    module procedure fmin88
                    module procedure fmin44
                    module procedure fmin84
                    module procedure fmin48
                end interface
            contains
                real(8) function fmax88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(4) function fmax44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(8) function fmax84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmax48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                end function
                real(8) function fmin88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(4) function fmin44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(8) function fmin84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmin48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                end function
            end module
            
            real(8) function code(d, h, l, m_m, d_1)
            use fmin_fmax_functions
                real(8), intent (in) :: d
                real(8), intent (in) :: h
                real(8), intent (in) :: l
                real(8), intent (in) :: m_m
                real(8), intent (in) :: d_1
                real(8) :: tmp
                if (l <= 3.7d+100) then
                    tmp = (sqrt((d / l)) * sqrt((d / h))) * (1.0d0 - ((((((d_1 * m_m) / (2.0d0 * d)) ** 2.0d0) * 0.5d0) * h) / l))
                else
                    tmp = (1.0d0 / (sqrt(l) * sqrt(h))) * d
                end if
                code = tmp
            end function
            
            M_m = Math.abs(M);
            assert d < h && h < l && l < M_m && M_m < D;
            public static double code(double d, double h, double l, double M_m, double D) {
            	double tmp;
            	if (l <= 3.7e+100) {
            		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * (1.0 - (((Math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l));
            	} else {
            		tmp = (1.0 / (Math.sqrt(l) * Math.sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m = math.fabs(M)
            [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
            def code(d, h, l, M_m, D):
            	tmp = 0
            	if l <= 3.7e+100:
            		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * (1.0 - (((math.pow(((D * M_m) / (2.0 * d)), 2.0) * 0.5) * h) / l))
            	else:
            		tmp = (1.0 / (math.sqrt(l) * math.sqrt(h))) * d
            	return tmp
            
            M_m = abs(M)
            d, h, l, M_m, D = sort([d, h, l, M_m, D])
            function code(d, h, l, M_m, D)
            	tmp = 0.0
            	if (l <= 3.7e+100)
            		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * Float64(1.0 - Float64(Float64(Float64((Float64(Float64(D * M_m) / Float64(2.0 * d)) ^ 2.0) * 0.5) * h) / l)));
            	else
            		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
            	end
            	return tmp
            end
            
            M_m = abs(M);
            d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
            function tmp_2 = code(d, h, l, M_m, D)
            	tmp = 0.0;
            	if (l <= 3.7e+100)
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * (1.0 - ((((((D * M_m) / (2.0 * d)) ^ 2.0) * 0.5) * h) / l));
            	else
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	end
            	tmp_2 = tmp;
            end
            
            M_m = N[Abs[M], $MachinePrecision]
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            code[d_, h_, l_, M$95$m_, D_] := If[LessEqual[l, 3.7e+100], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(N[(N[(N[Power[N[(N[(D * M$95$m), $MachinePrecision] / N[(2.0 * d), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * 0.5), $MachinePrecision] * h), $MachinePrecision] / l), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]]
            
            \begin{array}{l}
            M_m = \left|M\right|
            \\
            [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
            \\
            \begin{array}{l}
            \mathbf{if}\;\ell \leq 3.7 \cdot 10^{+100}:\\
            \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M\_m}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if l < 3.70000000000000019e100

              1. Initial program 68.6%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}}\right) \]
                2. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right)} \cdot \frac{h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\color{blue}{\frac{1}{2}} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot \color{blue}{{\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}}\right) \cdot \frac{h}{\ell}\right) \]
                5. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{\color{blue}{M \cdot D}}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{\color{blue}{2 \cdot d}}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                8. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \color{blue}{\frac{h}{\ell}}\right) \]
                9. associate-*r/N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
                10. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot h}{\ell}}\right) \]
              4. Applied rewrites70.4%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \color{blue}{\frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}}\right) \]
              5. Step-by-step derivation
                1. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. sqr-powN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. lower-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. lift-/.f6470.3

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              6. Applied rewrites70.3%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \frac{D}{d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              7. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M}{2} \cdot \frac{D}{d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\color{blue}{\frac{M}{2}} \cdot \frac{D}{d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{M}{2} \cdot \color{blue}{\frac{D}{d}}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. frac-timesN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{M \cdot D}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. *-commutativeN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lower-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{\color{blue}{D \cdot M}}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lower-*.f6470.8

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{\color{blue}{2 \cdot d}}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              8. Applied rewrites70.8%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{0.25} \cdot {\left(\frac{d}{\ell}\right)}^{0.25}\right)\right) \cdot \left(1 - \frac{\left({\color{blue}{\left(\frac{D \cdot M}{2 \cdot d}\right)}}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              9. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left({\color{blue}{\left(\frac{d}{h}\right)}}^{\left(\frac{1}{2}\right)} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                3. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\left(\frac{1}{2}\right)}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                4. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\color{blue}{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                5. lift-pow.f64N/A

                  \[\leadsto \left(\color{blue}{{\left(\frac{d}{h}\right)}^{\frac{1}{2}}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{\left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                8. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left(\color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot {\color{blue}{\left(\frac{d}{\ell}\right)}}^{\frac{1}{4}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                10. lift-pow.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \left({\left(\frac{d}{\ell}\right)}^{\frac{1}{4}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\frac{1}{4}}}\right)\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                11. pow-prod-upN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot \color{blue}{{\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                12. metadata-evalN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\frac{1}{2}} \cdot {\left(\frac{d}{\ell}\right)}^{\color{blue}{\frac{1}{2}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                13. pow1/2N/A

                  \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{h}}} \cdot {\left(\frac{d}{\ell}\right)}^{\frac{1}{2}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                14. pow1/2N/A

                  \[\leadsto \left(\sqrt{\frac{d}{h}} \cdot \color{blue}{\sqrt{\frac{d}{\ell}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                15. *-commutativeN/A

                  \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                16. lift-sqrt.f64N/A

                  \[\leadsto \left(\color{blue}{\sqrt{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                17. lift-/.f64N/A

                  \[\leadsto \left(\sqrt{\color{blue}{\frac{d}{\ell}}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                18. lift-sqrt.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \color{blue}{\sqrt{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                19. lift-/.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\color{blue}{\frac{d}{h}}}\right) \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot \frac{1}{2}\right) \cdot h}{\ell}\right) \]
                20. lift-*.f6470.9

                  \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]
              10. Applied rewrites70.9%

                \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right)} \cdot \left(1 - \frac{\left({\left(\frac{D \cdot M}{2 \cdot d}\right)}^{2} \cdot 0.5\right) \cdot h}{\ell}\right) \]

              if 3.70000000000000019e100 < l

              1. Initial program 53.9%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6448.5

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites48.5%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-sqrt.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                4. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. inv-powN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                6. sqrt-divN/A

                  \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                7. metadata-evalN/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                8. lower-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                10. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                11. lift-*.f6448.4

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              7. Applied rewrites48.4%

                \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                2. lift-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                3. sqrt-prodN/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                4. lower-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                5. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                6. lower-sqrt.f6463.0

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
              9. Applied rewrites63.0%

                \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
            3. Recombined 2 regimes into one program.
            4. Add Preprocessing

            Alternative 10: 58.3% accurate, 2.3× speedup?

            \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} t_0 := \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right)\\ \mathbf{if}\;d \leq -5.4 \cdot 10^{-162}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;d \leq 7 \cdot 10^{-299}:\\ \;\;\;\;\left(-0.125 \cdot \frac{{\left(D \cdot M\_m\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\\ \mathbf{elif}\;d \leq 3.1 \cdot 10^{-163}:\\ \;\;\;\;\left(\left(\left(M\_m \cdot \frac{M\_m}{d}\right) \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right)\\ \mathbf{elif}\;d \leq 5 \cdot 10^{+139}:\\ \;\;\;\;t\_0\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \end{array} \end{array} \]
            M_m = (fabs.f64 M)
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            (FPCore (d h l M_m D)
             :precision binary64
             (let* ((t_0
                     (*
                      (* (sqrt (/ d l)) (sqrt (/ d h)))
                      (*
                       (/ (fma (/ (* (* (* M_m M_m) h) D) (* d d)) -0.125 (/ l D)) l)
                       D))))
               (if (<= d -5.4e-162)
                 t_0
                 (if (<= d 7e-299)
                   (*
                    (* -0.125 (/ (* (pow (* D M_m) 2.0) -1.0) d))
                    (sqrt (/ h (* (* l l) l))))
                   (if (<= d 3.1e-163)
                     (* (* (* (* M_m (/ M_m d)) -0.125) (sqrt (/ h (pow l 3.0)))) (* D D))
                     (if (<= d 5e+139) t_0 (* (/ 1.0 (* (sqrt l) (sqrt h))) d)))))))
            M_m = fabs(M);
            assert(d < h && h < l && l < M_m && M_m < D);
            double code(double d, double h, double l, double M_m, double D) {
            	double t_0 = (sqrt((d / l)) * sqrt((d / h))) * ((fma(((((M_m * M_m) * h) * D) / (d * d)), -0.125, (l / D)) / l) * D);
            	double tmp;
            	if (d <= -5.4e-162) {
            		tmp = t_0;
            	} else if (d <= 7e-299) {
            		tmp = (-0.125 * ((pow((D * M_m), 2.0) * -1.0) / d)) * sqrt((h / ((l * l) * l)));
            	} else if (d <= 3.1e-163) {
            		tmp = (((M_m * (M_m / d)) * -0.125) * sqrt((h / pow(l, 3.0)))) * (D * D);
            	} else if (d <= 5e+139) {
            		tmp = t_0;
            	} else {
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m = abs(M)
            d, h, l, M_m, D = sort([d, h, l, M_m, D])
            function code(d, h, l, M_m, D)
            	t_0 = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * Float64(Float64(fma(Float64(Float64(Float64(Float64(M_m * M_m) * h) * D) / Float64(d * d)), -0.125, Float64(l / D)) / l) * D))
            	tmp = 0.0
            	if (d <= -5.4e-162)
            		tmp = t_0;
            	elseif (d <= 7e-299)
            		tmp = Float64(Float64(-0.125 * Float64(Float64((Float64(D * M_m) ^ 2.0) * -1.0) / d)) * sqrt(Float64(h / Float64(Float64(l * l) * l))));
            	elseif (d <= 3.1e-163)
            		tmp = Float64(Float64(Float64(Float64(M_m * Float64(M_m / d)) * -0.125) * sqrt(Float64(h / (l ^ 3.0)))) * Float64(D * D));
            	elseif (d <= 5e+139)
            		tmp = t_0;
            	else
            		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
            	end
            	return tmp
            end
            
            M_m = N[Abs[M], $MachinePrecision]
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            code[d_, h_, l_, M$95$m_, D_] := Block[{t$95$0 = N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[(N[(N[(N[(M$95$m * M$95$m), $MachinePrecision] * h), $MachinePrecision] * D), $MachinePrecision] / N[(d * d), $MachinePrecision]), $MachinePrecision] * -0.125 + N[(l / D), $MachinePrecision]), $MachinePrecision] / l), $MachinePrecision] * D), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[d, -5.4e-162], t$95$0, If[LessEqual[d, 7e-299], N[(N[(-0.125 * N[(N[(N[Power[N[(D * M$95$m), $MachinePrecision], 2.0], $MachinePrecision] * -1.0), $MachinePrecision] / d), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(h / N[(N[(l * l), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], If[LessEqual[d, 3.1e-163], N[(N[(N[(N[(M$95$m * N[(M$95$m / d), $MachinePrecision]), $MachinePrecision] * -0.125), $MachinePrecision] * N[Sqrt[N[(h / N[Power[l, 3.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(D * D), $MachinePrecision]), $MachinePrecision], If[LessEqual[d, 5e+139], t$95$0, N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]]]]]]
            
            \begin{array}{l}
            M_m = \left|M\right|
            \\
            [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
            \\
            \begin{array}{l}
            t_0 := \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M\_m \cdot M\_m\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right)\\
            \mathbf{if}\;d \leq -5.4 \cdot 10^{-162}:\\
            \;\;\;\;t\_0\\
            
            \mathbf{elif}\;d \leq 7 \cdot 10^{-299}:\\
            \;\;\;\;\left(-0.125 \cdot \frac{{\left(D \cdot M\_m\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}}\\
            
            \mathbf{elif}\;d \leq 3.1 \cdot 10^{-163}:\\
            \;\;\;\;\left(\left(\left(M\_m \cdot \frac{M\_m}{d}\right) \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right)\\
            
            \mathbf{elif}\;d \leq 5 \cdot 10^{+139}:\\
            \;\;\;\;t\_0\\
            
            \mathbf{else}:\\
            \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 4 regimes
            2. if d < -5.39999999999999968e-162 or 3.09999999999999975e-163 < d < 5.0000000000000003e139

              1. Initial program 74.4%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in D around inf

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
                2. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
              5. Applied rewrites45.9%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
              6. Applied rewrites45.3%

                \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
              7. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \left(D \cdot \color{blue}{D}\right)\right) \]
                2. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, \frac{-1}{8}, {D}^{-2}\right) \cdot \color{blue}{\left(D \cdot D\right)}\right) \]
                3. lift-fma.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(\color{blue}{D} \cdot D\right)\right) \]
                4. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                5. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                6. lift-/.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                7. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                8. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                9. lift-pow.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot \left(D \cdot D\right)\right) \]
                10. associate-*r*N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
                11. lower-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\left(\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \frac{-1}{8} + {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
              8. Applied rewrites47.7%

                \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\left(\mathsf{fma}\left(-0.125, \left(M \cdot M\right) \cdot \frac{\frac{h}{d \cdot d}}{\ell}, {D}^{-2}\right) \cdot D\right) \cdot \color{blue}{D}\right) \]
              9. Taylor expanded in l around 0

                \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
              10. Step-by-step derivation
                1. lower-/.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{-1}{8} \cdot \frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
                2. *-commutativeN/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}} \cdot \frac{-1}{8} + \frac{\ell}{D}}{\ell} \cdot D\right) \]
                3. lower-fma.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                4. lower-/.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{D \cdot \left({M}^{2} \cdot h\right)}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                5. *-commutativeN/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                6. lower-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left({M}^{2} \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                8. pow2N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                9. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{{d}^{2}}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                10. pow2N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                11. lift-*.f64N/A

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, \frac{-1}{8}, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
                12. lower-/.f6458.6

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]
              11. Applied rewrites58.6%

                \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\frac{\mathsf{fma}\left(\frac{\left(\left(M \cdot M\right) \cdot h\right) \cdot D}{d \cdot d}, -0.125, \frac{\ell}{D}\right)}{\ell} \cdot D\right) \]

              if -5.39999999999999968e-162 < d < 6.99999999999999981e-299

              1. Initial program 42.0%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in h around -inf

                \[\leadsto \color{blue}{\frac{-1}{8} \cdot \left(\frac{{D}^{2} \cdot \left({M}^{2} \cdot {\left(\sqrt{-1}\right)}^{2}\right)}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right)} \]
              4. Step-by-step derivation
                1. associate-*r*N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{D}^{2} \cdot \left({M}^{2} \cdot {\left(\sqrt{-1}\right)}^{2}\right)}{d}\right) \cdot \color{blue}{\sqrt{\frac{h}{{\ell}^{3}}}} \]
                2. lower-*.f64N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{D}^{2} \cdot \left({M}^{2} \cdot {\left(\sqrt{-1}\right)}^{2}\right)}{d}\right) \cdot \color{blue}{\sqrt{\frac{h}{{\ell}^{3}}}} \]
              5. Applied rewrites47.7%

                \[\leadsto \color{blue}{\left(-0.125 \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}} \]
              6. Step-by-step derivation
                1. lift-pow.f64N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}} \]
                2. unpow3N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}} \]
                3. unpow2N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{2} \cdot \ell}} \]
                4. lower-*.f64N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{2} \cdot \ell}} \]
                5. unpow2N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}} \]
                6. lower-*.f6447.7

                  \[\leadsto \left(-0.125 \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}} \]
              7. Applied rewrites47.7%

                \[\leadsto \left(-0.125 \cdot \frac{{\left(D \cdot M\right)}^{2} \cdot -1}{d}\right) \cdot \sqrt{\frac{h}{\left(\ell \cdot \ell\right) \cdot \ell}} \]

              if 6.99999999999999981e-299 < d < 3.09999999999999975e-163

              1. Initial program 39.1%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in D around inf

                \[\leadsto \color{blue}{{D}^{2} \cdot \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right)} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
                2. lower-*.f64N/A

                  \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) + \frac{d}{{D}^{2}} \cdot \sqrt{\frac{1}{h \cdot \ell}}\right) \cdot \color{blue}{{D}^{2}} \]
              5. Applied rewrites37.1%

                \[\leadsto \color{blue}{\mathsf{fma}\left(-0.125 \cdot \frac{M \cdot M}{d}, \sqrt{\frac{h}{{\ell}^{3}}}, \frac{d}{D \cdot D} \cdot \sqrt{{\left(\ell \cdot h\right)}^{-1}}\right) \cdot \left(D \cdot D\right)} \]
              6. Taylor expanded in d around 0

                \[\leadsto \left(\frac{-1}{8} \cdot \left(\frac{{M}^{2}}{d} \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right)\right) \cdot \left(\color{blue}{D} \cdot D\right) \]
              7. Step-by-step derivation
                1. associate-*r*N/A

                  \[\leadsto \left(\left(\frac{-1}{8} \cdot \frac{{M}^{2}}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                2. lower-*.f64N/A

                  \[\leadsto \left(\left(\frac{-1}{8} \cdot \frac{{M}^{2}}{d}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                3. *-commutativeN/A

                  \[\leadsto \left(\left(\frac{{M}^{2}}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                4. lower-*.f64N/A

                  \[\leadsto \left(\left(\frac{{M}^{2}}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                5. pow2N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                6. lift-*.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                7. lift-/.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                8. lift-pow.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                9. lift-/.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                10. lift-sqrt.f6439.4

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              8. Applied rewrites39.4%

                \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(\color{blue}{D} \cdot D\right) \]
              9. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                2. lift-/.f64N/A

                  \[\leadsto \left(\left(\frac{M \cdot M}{d} \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                3. associate-/l*N/A

                  \[\leadsto \left(\left(\left(M \cdot \frac{M}{d}\right) \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                4. lower-*.f64N/A

                  \[\leadsto \left(\left(\left(M \cdot \frac{M}{d}\right) \cdot \frac{-1}{8}\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
                5. lower-/.f6445.0

                  \[\leadsto \left(\left(\left(M \cdot \frac{M}{d}\right) \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]
              10. Applied rewrites45.0%

                \[\leadsto \left(\left(\left(M \cdot \frac{M}{d}\right) \cdot -0.125\right) \cdot \sqrt{\frac{h}{{\ell}^{3}}}\right) \cdot \left(D \cdot D\right) \]

              if 5.0000000000000003e139 < d

              1. Initial program 71.7%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6467.2

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites67.2%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-sqrt.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                4. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. inv-powN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                6. sqrt-divN/A

                  \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                7. metadata-evalN/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                8. lower-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                10. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                11. lift-*.f6467.1

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              7. Applied rewrites67.1%

                \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                2. lift-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                3. sqrt-prodN/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                4. lower-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                5. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                6. lower-sqrt.f6477.2

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
              9. Applied rewrites77.2%

                \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
            3. Recombined 4 regimes into one program.
            4. Add Preprocessing

            Alternative 11: 45.0% accurate, 7.0× speedup?

            \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} \mathbf{if}\;\ell \leq 1.8 \cdot 10^{-295}:\\ \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \end{array} \end{array} \]
            M_m = (fabs.f64 M)
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            (FPCore (d h l M_m D)
             :precision binary64
             (if (<= l 1.8e-295)
               (* (* (sqrt (/ d l)) (sqrt (/ d h))) 1.0)
               (* (/ 1.0 (* (sqrt l) (sqrt h))) d)))
            M_m = fabs(M);
            assert(d < h && h < l && l < M_m && M_m < D);
            double code(double d, double h, double l, double M_m, double D) {
            	double tmp;
            	if (l <= 1.8e-295) {
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
            	} else {
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m =     private
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            module fmin_fmax_functions
                implicit none
                private
                public fmax
                public fmin
            
                interface fmax
                    module procedure fmax88
                    module procedure fmax44
                    module procedure fmax84
                    module procedure fmax48
                end interface
                interface fmin
                    module procedure fmin88
                    module procedure fmin44
                    module procedure fmin84
                    module procedure fmin48
                end interface
            contains
                real(8) function fmax88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(4) function fmax44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(8) function fmax84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmax48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                end function
                real(8) function fmin88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(4) function fmin44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(8) function fmin84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmin48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                end function
            end module
            
            real(8) function code(d, h, l, m_m, d_1)
            use fmin_fmax_functions
                real(8), intent (in) :: d
                real(8), intent (in) :: h
                real(8), intent (in) :: l
                real(8), intent (in) :: m_m
                real(8), intent (in) :: d_1
                real(8) :: tmp
                if (l <= 1.8d-295) then
                    tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0d0
                else
                    tmp = (1.0d0 / (sqrt(l) * sqrt(h))) * d
                end if
                code = tmp
            end function
            
            M_m = Math.abs(M);
            assert d < h && h < l && l < M_m && M_m < D;
            public static double code(double d, double h, double l, double M_m, double D) {
            	double tmp;
            	if (l <= 1.8e-295) {
            		tmp = (Math.sqrt((d / l)) * Math.sqrt((d / h))) * 1.0;
            	} else {
            		tmp = (1.0 / (Math.sqrt(l) * Math.sqrt(h))) * d;
            	}
            	return tmp;
            }
            
            M_m = math.fabs(M)
            [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
            def code(d, h, l, M_m, D):
            	tmp = 0
            	if l <= 1.8e-295:
            		tmp = (math.sqrt((d / l)) * math.sqrt((d / h))) * 1.0
            	else:
            		tmp = (1.0 / (math.sqrt(l) * math.sqrt(h))) * d
            	return tmp
            
            M_m = abs(M)
            d, h, l, M_m, D = sort([d, h, l, M_m, D])
            function code(d, h, l, M_m, D)
            	tmp = 0.0
            	if (l <= 1.8e-295)
            		tmp = Float64(Float64(sqrt(Float64(d / l)) * sqrt(Float64(d / h))) * 1.0);
            	else
            		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
            	end
            	return tmp
            end
            
            M_m = abs(M);
            d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
            function tmp_2 = code(d, h, l, M_m, D)
            	tmp = 0.0;
            	if (l <= 1.8e-295)
            		tmp = (sqrt((d / l)) * sqrt((d / h))) * 1.0;
            	else
            		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
            	end
            	tmp_2 = tmp;
            end
            
            M_m = N[Abs[M], $MachinePrecision]
            NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
            code[d_, h_, l_, M$95$m_, D_] := If[LessEqual[l, 1.8e-295], N[(N[(N[Sqrt[N[(d / l), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(d / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 1.0), $MachinePrecision], N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]]
            
            \begin{array}{l}
            M_m = \left|M\right|
            \\
            [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
            \\
            \begin{array}{l}
            \mathbf{if}\;\ell \leq 1.8 \cdot 10^{-295}:\\
            \;\;\;\;\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1\\
            
            \mathbf{else}:\\
            \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if l < 1.8000000000000001e-295

              1. Initial program 66.6%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in D around inf

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left({D}^{2} \cdot \left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right)\right)} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
                2. lower-*.f64N/A

                  \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(\left(\frac{1}{{D}^{2}} - \frac{1}{8} \cdot \frac{{M}^{2} \cdot h}{{d}^{2} \cdot \ell}\right) \cdot \color{blue}{{D}^{2}}\right) \]
              5. Applied rewrites37.2%

                \[\leadsto \left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \color{blue}{\left(\left({D}^{-2} - \frac{0.125 \cdot \left(\left(M \cdot M\right) \cdot h\right)}{\left(d \cdot d\right) \cdot \ell}\right) \cdot \left(D \cdot D\right)\right)} \]
              6. Applied rewrites37.3%

                \[\leadsto \color{blue}{\left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot \left(\mathsf{fma}\left(\left(M \cdot M\right) \cdot \frac{h}{\left(d \cdot d\right) \cdot \ell}, -0.125, {D}^{-2}\right) \cdot \left(D \cdot D\right)\right)} \]
              7. Taylor expanded in d around inf

                \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]
              8. Step-by-step derivation
                1. Applied rewrites38.8%

                  \[\leadsto \left(\sqrt{\frac{d}{\ell}} \cdot \sqrt{\frac{d}{h}}\right) \cdot 1 \]

                if 1.8000000000000001e-295 < l

                1. Initial program 65.4%

                  \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                2. Add Preprocessing
                3. Taylor expanded in d around inf

                  \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
                4. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  2. lower-*.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  3. lower-sqrt.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                  4. inv-powN/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  5. lower-pow.f64N/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  6. *-commutativeN/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  7. lower-*.f6443.6

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                5. Applied rewrites43.6%

                  \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
                6. Step-by-step derivation
                  1. lift-sqrt.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  2. lift-*.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  3. lift-pow.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  4. *-commutativeN/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  5. inv-powN/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                  6. sqrt-divN/A

                    \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                  7. metadata-evalN/A

                    \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                  8. lower-/.f64N/A

                    \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                  9. *-commutativeN/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  10. lower-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  11. lift-*.f6443.7

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                7. Applied rewrites43.7%

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                8. Step-by-step derivation
                  1. lift-*.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  2. lift-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  3. sqrt-prodN/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  4. lower-*.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  5. lower-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  6. lower-sqrt.f6451.4

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                9. Applied rewrites51.4%

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
              9. Recombined 2 regimes into one program.
              10. Add Preprocessing

              Alternative 12: 31.0% accurate, 8.6× speedup?

              \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \begin{array}{l} \mathbf{if}\;d \leq 7.5 \cdot 10^{-148}:\\ \;\;\;\;\sqrt{\frac{1}{\ell \cdot h}} \cdot d\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\ \end{array} \end{array} \]
              M_m = (fabs.f64 M)
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              (FPCore (d h l M_m D)
               :precision binary64
               (if (<= d 7.5e-148)
                 (* (sqrt (/ 1.0 (* l h))) d)
                 (* (/ 1.0 (* (sqrt l) (sqrt h))) d)))
              M_m = fabs(M);
              assert(d < h && h < l && l < M_m && M_m < D);
              double code(double d, double h, double l, double M_m, double D) {
              	double tmp;
              	if (d <= 7.5e-148) {
              		tmp = sqrt((1.0 / (l * h))) * d;
              	} else {
              		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
              	}
              	return tmp;
              }
              
              M_m =     private
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(8) function code(d, h, l, m_m, d_1)
              use fmin_fmax_functions
                  real(8), intent (in) :: d
                  real(8), intent (in) :: h
                  real(8), intent (in) :: l
                  real(8), intent (in) :: m_m
                  real(8), intent (in) :: d_1
                  real(8) :: tmp
                  if (d <= 7.5d-148) then
                      tmp = sqrt((1.0d0 / (l * h))) * d
                  else
                      tmp = (1.0d0 / (sqrt(l) * sqrt(h))) * d
                  end if
                  code = tmp
              end function
              
              M_m = Math.abs(M);
              assert d < h && h < l && l < M_m && M_m < D;
              public static double code(double d, double h, double l, double M_m, double D) {
              	double tmp;
              	if (d <= 7.5e-148) {
              		tmp = Math.sqrt((1.0 / (l * h))) * d;
              	} else {
              		tmp = (1.0 / (Math.sqrt(l) * Math.sqrt(h))) * d;
              	}
              	return tmp;
              }
              
              M_m = math.fabs(M)
              [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
              def code(d, h, l, M_m, D):
              	tmp = 0
              	if d <= 7.5e-148:
              		tmp = math.sqrt((1.0 / (l * h))) * d
              	else:
              		tmp = (1.0 / (math.sqrt(l) * math.sqrt(h))) * d
              	return tmp
              
              M_m = abs(M)
              d, h, l, M_m, D = sort([d, h, l, M_m, D])
              function code(d, h, l, M_m, D)
              	tmp = 0.0
              	if (d <= 7.5e-148)
              		tmp = Float64(sqrt(Float64(1.0 / Float64(l * h))) * d);
              	else
              		tmp = Float64(Float64(1.0 / Float64(sqrt(l) * sqrt(h))) * d);
              	end
              	return tmp
              end
              
              M_m = abs(M);
              d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
              function tmp_2 = code(d, h, l, M_m, D)
              	tmp = 0.0;
              	if (d <= 7.5e-148)
              		tmp = sqrt((1.0 / (l * h))) * d;
              	else
              		tmp = (1.0 / (sqrt(l) * sqrt(h))) * d;
              	end
              	tmp_2 = tmp;
              end
              
              M_m = N[Abs[M], $MachinePrecision]
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              code[d_, h_, l_, M$95$m_, D_] := If[LessEqual[d, 7.5e-148], N[(N[Sqrt[N[(1.0 / N[(l * h), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * d), $MachinePrecision], N[(N[(1.0 / N[(N[Sqrt[l], $MachinePrecision] * N[Sqrt[h], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]]
              
              \begin{array}{l}
              M_m = \left|M\right|
              \\
              [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
              \\
              \begin{array}{l}
              \mathbf{if}\;d \leq 7.5 \cdot 10^{-148}:\\
              \;\;\;\;\sqrt{\frac{1}{\ell \cdot h}} \cdot d\\
              
              \mathbf{else}:\\
              \;\;\;\;\frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if d < 7.5000000000000005e-148

                1. Initial program 61.0%

                  \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                2. Add Preprocessing
                3. Taylor expanded in d around inf

                  \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
                4. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  2. lower-*.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  3. lower-sqrt.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                  4. inv-powN/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  5. lower-pow.f64N/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  6. *-commutativeN/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  7. lower-*.f6413.4

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                5. Applied rewrites13.4%

                  \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
                6. Step-by-step derivation
                  1. lift-*.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  2. lift-pow.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  3. unpow-1N/A

                    \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
                  4. lower-/.f64N/A

                    \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
                  5. lift-*.f6413.4

                    \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
                7. Applied rewrites13.4%

                  \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]

                if 7.5000000000000005e-148 < d

                1. Initial program 74.4%

                  \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
                2. Add Preprocessing
                3. Taylor expanded in d around inf

                  \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
                4. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  2. lower-*.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                  3. lower-sqrt.f64N/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                  4. inv-powN/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  5. lower-pow.f64N/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  6. *-commutativeN/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  7. lower-*.f6450.9

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                5. Applied rewrites50.9%

                  \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
                6. Step-by-step derivation
                  1. lift-sqrt.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  2. lift-*.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  3. lift-pow.f64N/A

                    \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                  4. *-commutativeN/A

                    \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                  5. inv-powN/A

                    \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                  6. sqrt-divN/A

                    \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                  7. metadata-evalN/A

                    \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                  8. lower-/.f64N/A

                    \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                  9. *-commutativeN/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  10. lower-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  11. lift-*.f6450.9

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                7. Applied rewrites50.9%

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                8. Step-by-step derivation
                  1. lift-*.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  2. lift-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                  3. sqrt-prodN/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  4. lower-*.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  5. lower-sqrt.f64N/A

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                  6. lower-sqrt.f6460.6

                    \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
                9. Applied rewrites60.6%

                  \[\leadsto \frac{1}{\sqrt{\ell} \cdot \sqrt{h}} \cdot d \]
              3. Recombined 2 regimes into one program.
              4. Add Preprocessing

              Alternative 13: 27.2% accurate, 12.9× speedup?

              \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \frac{1 \cdot d}{\sqrt{\ell \cdot h}} \end{array} \]
              M_m = (fabs.f64 M)
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              (FPCore (d h l M_m D) :precision binary64 (/ (* 1.0 d) (sqrt (* l h))))
              M_m = fabs(M);
              assert(d < h && h < l && l < M_m && M_m < D);
              double code(double d, double h, double l, double M_m, double D) {
              	return (1.0 * d) / sqrt((l * h));
              }
              
              M_m =     private
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(8) function code(d, h, l, m_m, d_1)
              use fmin_fmax_functions
                  real(8), intent (in) :: d
                  real(8), intent (in) :: h
                  real(8), intent (in) :: l
                  real(8), intent (in) :: m_m
                  real(8), intent (in) :: d_1
                  code = (1.0d0 * d) / sqrt((l * h))
              end function
              
              M_m = Math.abs(M);
              assert d < h && h < l && l < M_m && M_m < D;
              public static double code(double d, double h, double l, double M_m, double D) {
              	return (1.0 * d) / Math.sqrt((l * h));
              }
              
              M_m = math.fabs(M)
              [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
              def code(d, h, l, M_m, D):
              	return (1.0 * d) / math.sqrt((l * h))
              
              M_m = abs(M)
              d, h, l, M_m, D = sort([d, h, l, M_m, D])
              function code(d, h, l, M_m, D)
              	return Float64(Float64(1.0 * d) / sqrt(Float64(l * h)))
              end
              
              M_m = abs(M);
              d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
              function tmp = code(d, h, l, M_m, D)
              	tmp = (1.0 * d) / sqrt((l * h));
              end
              
              M_m = N[Abs[M], $MachinePrecision]
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              code[d_, h_, l_, M$95$m_, D_] := N[(N[(1.0 * d), $MachinePrecision] / N[Sqrt[N[(l * h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
              
              \begin{array}{l}
              M_m = \left|M\right|
              \\
              [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
              \\
              \frac{1 \cdot d}{\sqrt{\ell \cdot h}}
              \end{array}
              
              Derivation
              1. Initial program 66.0%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6427.4

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites27.4%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-sqrt.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                4. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. inv-powN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                6. sqrt-divN/A

                  \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                7. metadata-evalN/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                8. lower-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                10. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                11. lift-*.f6427.2

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              7. Applied rewrites27.2%

                \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot \color{blue}{d} \]
                2. lift-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                3. lift-*.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                4. lift-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                5. associate-*l/N/A

                  \[\leadsto \frac{1 \cdot d}{\color{blue}{\sqrt{\ell \cdot h}}} \]
                6. *-commutativeN/A

                  \[\leadsto \frac{1 \cdot d}{\sqrt{h \cdot \ell}} \]
                7. lower-/.f64N/A

                  \[\leadsto \frac{1 \cdot d}{\color{blue}{\sqrt{h \cdot \ell}}} \]
                8. lower-*.f64N/A

                  \[\leadsto \frac{1 \cdot d}{\sqrt{\color{blue}{h \cdot \ell}}} \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1 \cdot d}{\sqrt{\ell \cdot h}} \]
                10. lift-sqrt.f64N/A

                  \[\leadsto \frac{1 \cdot d}{\sqrt{\ell \cdot h}} \]
                11. lift-*.f6427.2

                  \[\leadsto \frac{1 \cdot d}{\sqrt{\ell \cdot h}} \]
              9. Applied rewrites27.2%

                \[\leadsto \frac{1 \cdot d}{\color{blue}{\sqrt{\ell \cdot h}}} \]
              10. Add Preprocessing

              Alternative 14: 27.2% accurate, 12.9× speedup?

              \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \frac{1}{\sqrt{\ell \cdot h}} \cdot d \end{array} \]
              M_m = (fabs.f64 M)
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              (FPCore (d h l M_m D) :precision binary64 (* (/ 1.0 (sqrt (* l h))) d))
              M_m = fabs(M);
              assert(d < h && h < l && l < M_m && M_m < D);
              double code(double d, double h, double l, double M_m, double D) {
              	return (1.0 / sqrt((l * h))) * d;
              }
              
              M_m =     private
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(8) function code(d, h, l, m_m, d_1)
              use fmin_fmax_functions
                  real(8), intent (in) :: d
                  real(8), intent (in) :: h
                  real(8), intent (in) :: l
                  real(8), intent (in) :: m_m
                  real(8), intent (in) :: d_1
                  code = (1.0d0 / sqrt((l * h))) * d
              end function
              
              M_m = Math.abs(M);
              assert d < h && h < l && l < M_m && M_m < D;
              public static double code(double d, double h, double l, double M_m, double D) {
              	return (1.0 / Math.sqrt((l * h))) * d;
              }
              
              M_m = math.fabs(M)
              [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
              def code(d, h, l, M_m, D):
              	return (1.0 / math.sqrt((l * h))) * d
              
              M_m = abs(M)
              d, h, l, M_m, D = sort([d, h, l, M_m, D])
              function code(d, h, l, M_m, D)
              	return Float64(Float64(1.0 / sqrt(Float64(l * h))) * d)
              end
              
              M_m = abs(M);
              d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
              function tmp = code(d, h, l, M_m, D)
              	tmp = (1.0 / sqrt((l * h))) * d;
              end
              
              M_m = N[Abs[M], $MachinePrecision]
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              code[d_, h_, l_, M$95$m_, D_] := N[(N[(1.0 / N[Sqrt[N[(l * h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * d), $MachinePrecision]
              
              \begin{array}{l}
              M_m = \left|M\right|
              \\
              [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
              \\
              \frac{1}{\sqrt{\ell \cdot h}} \cdot d
              \end{array}
              
              Derivation
              1. Initial program 66.0%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6427.4

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites27.4%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-sqrt.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                4. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. inv-powN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                6. sqrt-divN/A

                  \[\leadsto \frac{\sqrt{1}}{\sqrt{h \cdot \ell}} \cdot d \]
                7. metadata-evalN/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                8. lower-/.f64N/A

                  \[\leadsto \frac{1}{\sqrt{h \cdot \ell}} \cdot d \]
                9. *-commutativeN/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                10. lower-sqrt.f64N/A

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
                11. lift-*.f6427.2

                  \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              7. Applied rewrites27.2%

                \[\leadsto \frac{1}{\sqrt{\ell \cdot h}} \cdot d \]
              8. Add Preprocessing

              Alternative 15: 27.4% accurate, 12.9× speedup?

              \[\begin{array}{l} M_m = \left|M\right| \\ [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\ \\ \sqrt{\frac{1}{\ell \cdot h}} \cdot d \end{array} \]
              M_m = (fabs.f64 M)
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              (FPCore (d h l M_m D) :precision binary64 (* (sqrt (/ 1.0 (* l h))) d))
              M_m = fabs(M);
              assert(d < h && h < l && l < M_m && M_m < D);
              double code(double d, double h, double l, double M_m, double D) {
              	return sqrt((1.0 / (l * h))) * d;
              }
              
              M_m =     private
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(8) function code(d, h, l, m_m, d_1)
              use fmin_fmax_functions
                  real(8), intent (in) :: d
                  real(8), intent (in) :: h
                  real(8), intent (in) :: l
                  real(8), intent (in) :: m_m
                  real(8), intent (in) :: d_1
                  code = sqrt((1.0d0 / (l * h))) * d
              end function
              
              M_m = Math.abs(M);
              assert d < h && h < l && l < M_m && M_m < D;
              public static double code(double d, double h, double l, double M_m, double D) {
              	return Math.sqrt((1.0 / (l * h))) * d;
              }
              
              M_m = math.fabs(M)
              [d, h, l, M_m, D] = sort([d, h, l, M_m, D])
              def code(d, h, l, M_m, D):
              	return math.sqrt((1.0 / (l * h))) * d
              
              M_m = abs(M)
              d, h, l, M_m, D = sort([d, h, l, M_m, D])
              function code(d, h, l, M_m, D)
              	return Float64(sqrt(Float64(1.0 / Float64(l * h))) * d)
              end
              
              M_m = abs(M);
              d, h, l, M_m, D = num2cell(sort([d, h, l, M_m, D])){:}
              function tmp = code(d, h, l, M_m, D)
              	tmp = sqrt((1.0 / (l * h))) * d;
              end
              
              M_m = N[Abs[M], $MachinePrecision]
              NOTE: d, h, l, M_m, and D should be sorted in increasing order before calling this function.
              code[d_, h_, l_, M$95$m_, D_] := N[(N[Sqrt[N[(1.0 / N[(l * h), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * d), $MachinePrecision]
              
              \begin{array}{l}
              M_m = \left|M\right|
              \\
              [d, h, l, M_m, D] = \mathsf{sort}([d, h, l, M_m, D])\\
              \\
              \sqrt{\frac{1}{\ell \cdot h}} \cdot d
              \end{array}
              
              Derivation
              1. Initial program 66.0%

                \[\left({\left(\frac{d}{h}\right)}^{\left(\frac{1}{2}\right)} \cdot {\left(\frac{d}{\ell}\right)}^{\left(\frac{1}{2}\right)}\right) \cdot \left(1 - \left(\frac{1}{2} \cdot {\left(\frac{M \cdot D}{2 \cdot d}\right)}^{2}\right) \cdot \frac{h}{\ell}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in d around inf

                \[\leadsto \color{blue}{d \cdot \sqrt{\frac{1}{h \cdot \ell}}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                2. lower-*.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot \color{blue}{d} \]
                3. lower-sqrt.f64N/A

                  \[\leadsto \sqrt{\frac{1}{h \cdot \ell}} \cdot d \]
                4. inv-powN/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                5. lower-pow.f64N/A

                  \[\leadsto \sqrt{{\left(h \cdot \ell\right)}^{-1}} \cdot d \]
                6. *-commutativeN/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                7. lower-*.f6427.4

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
              5. Applied rewrites27.4%

                \[\leadsto \color{blue}{\sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d} \]
              6. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                2. lift-pow.f64N/A

                  \[\leadsto \sqrt{{\left(\ell \cdot h\right)}^{-1}} \cdot d \]
                3. unpow-1N/A

                  \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
                4. lower-/.f64N/A

                  \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
                5. lift-*.f6427.4

                  \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
              7. Applied rewrites27.4%

                \[\leadsto \sqrt{\frac{1}{\ell \cdot h}} \cdot d \]
              8. Add Preprocessing

              Reproduce

              ?
              herbie shell --seed 2025089 
              (FPCore (d h l M D)
                :name "Henrywood and Agarwal, Equation (12)"
                :precision binary64
                (* (* (pow (/ d h) (/ 1.0 2.0)) (pow (/ d l) (/ 1.0 2.0))) (- 1.0 (* (* (/ 1.0 2.0) (pow (/ (* M D) (* 2.0 d)) 2.0)) (/ h l)))))