Maksimov and Kolovsky, Equation (4)

Percentage Accurate: 86.2% → 97.1%
Time: 5.0s
Alternatives: 17
Speedup: 2.0×

Specification

?
\[\begin{array}{l} \\ \left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))
double code(double J, double l, double K, double U) {
	return ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
}
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(j, l, k, u)
use fmin_fmax_functions
    real(8), intent (in) :: j
    real(8), intent (in) :: l
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    code = ((j * (exp(l) - exp(-l))) * cos((k / 2.0d0))) + u
end function
public static double code(double J, double l, double K, double U) {
	return ((J * (Math.exp(l) - Math.exp(-l))) * Math.cos((K / 2.0))) + U;
}
def code(J, l, K, U):
	return ((J * (math.exp(l) - math.exp(-l))) * math.cos((K / 2.0))) + U
function code(J, l, K, U)
	return Float64(Float64(Float64(J * Float64(exp(l) - exp(Float64(-l)))) * cos(Float64(K / 2.0))) + U)
end
function tmp = code(J, l, K, U)
	tmp = ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
end
code[J_, l_, K_, U_] := N[(N[(N[(J * N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]
\begin{array}{l}

\\
\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U
\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 17 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: 86.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))
double code(double J, double l, double K, double U) {
	return ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
}
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(j, l, k, u)
use fmin_fmax_functions
    real(8), intent (in) :: j
    real(8), intent (in) :: l
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    code = ((j * (exp(l) - exp(-l))) * cos((k / 2.0d0))) + u
end function
public static double code(double J, double l, double K, double U) {
	return ((J * (Math.exp(l) - Math.exp(-l))) * Math.cos((K / 2.0))) + U;
}
def code(J, l, K, U):
	return ((J * (math.exp(l) - math.exp(-l))) * math.cos((K / 2.0))) + U
function code(J, l, K, U)
	return Float64(Float64(Float64(J * Float64(exp(l) - exp(Float64(-l)))) * cos(Float64(K / 2.0))) + U)
end
function tmp = code(J, l, K, U)
	tmp = ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
end
code[J_, l_, K_, U_] := N[(N[(N[(J * N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]
\begin{array}{l}

\\
\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U
\end{array}

Alternative 1: 97.1% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;J \cdot \left(e^{\ell} - e^{-\ell}\right) \leq -\infty:\\ \;\;\;\;\left(\cos \left(0.5 \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \sinh \ell\right)\\ \mathbf{else}:\\ \;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= (* J (- (exp l) (exp (- l)))) (- INFINITY))
   (* (* (cos (* 0.5 K)) J) (* 2.0 (sinh l)))
   (+
    (*
     (*
      J
      (*
       (fma
        (fma
         (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
         (* l l)
         0.3333333333333333)
        (* l l)
        2.0)
       l))
     (cos (/ K 2.0)))
    U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if ((J * (exp(l) - exp(-l))) <= -((double) INFINITY)) {
		tmp = (cos((0.5 * K)) * J) * (2.0 * sinh(l));
	} else {
		tmp = ((J * (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l)) * cos((K / 2.0))) + U;
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (Float64(J * Float64(exp(l) - exp(Float64(-l)))) <= Float64(-Inf))
		tmp = Float64(Float64(cos(Float64(0.5 * K)) * J) * Float64(2.0 * sinh(l)));
	else
		tmp = Float64(Float64(Float64(J * Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l)) * cos(Float64(K / 2.0))) + U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[N[(J * N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], (-Infinity)], N[(N[(N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision] * J), $MachinePrecision] * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(J * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;J \cdot \left(e^{\ell} - e^{-\ell}\right) \leq -\infty:\\
\;\;\;\;\left(\cos \left(0.5 \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \sinh \ell\right)\\

\mathbf{else}:\\
\;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f64 J (-.f64 (exp.f64 l) (exp.f64 (neg.f64 l)))) < -inf.0

    1. Initial program 100.0%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in J around inf

      \[\leadsto \color{blue}{J \cdot \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \]
    3. Step-by-step derivation
      1. associate-*r*N/A

        \[\leadsto \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right) \cdot \color{blue}{\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
      2. lower-*.f64N/A

        \[\leadsto \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right) \cdot \color{blue}{\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
      3. *-commutativeN/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(\color{blue}{e^{\ell}} - e^{\mathsf{neg}\left(\ell\right)}\right) \]
      4. lower-*.f64N/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(\color{blue}{e^{\ell}} - e^{\mathsf{neg}\left(\ell\right)}\right) \]
      5. lower-cos.f64N/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(e^{\color{blue}{\ell}} - e^{\mathsf{neg}\left(\ell\right)}\right) \]
      6. lower-*.f64N/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \]
      7. sinh-undefN/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \color{blue}{\sinh \ell}\right) \]
      8. lower-*.f64N/A

        \[\leadsto \left(\cos \left(\frac{1}{2} \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \color{blue}{\sinh \ell}\right) \]
      9. lower-sinh.f64100.0

        \[\leadsto \left(\cos \left(0.5 \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \sinh \ell\right) \]
    4. Applied rewrites100.0%

      \[\leadsto \color{blue}{\left(\cos \left(0.5 \cdot K\right) \cdot J\right) \cdot \left(2 \cdot \sinh \ell\right)} \]

    if -inf.0 < (*.f64 J (-.f64 (exp.f64 l) (exp.f64 (neg.f64 l))))

    1. Initial program 81.7%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites96.2%

      \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 2: 86.6% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ \mathbf{if}\;t\_0 \leq -0.89:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\ \mathbf{elif}\;t\_0 \leq -0.05:\\ \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (let* ((t_0 (cos (/ K 2.0))))
   (if (<= t_0 -0.89)
     (+
      (*
       (* (* (fma (* l l) 0.3333333333333333 2.0) l) J)
       (fma (* K K) -0.125 1.0))
      U)
     (if (<= t_0 -0.05)
       (fma (* (* l J) (cos (* 0.5 K))) 2.0 U)
       (fma (* 2.0 (sinh l)) J U)))))
double code(double J, double l, double K, double U) {
	double t_0 = cos((K / 2.0));
	double tmp;
	if (t_0 <= -0.89) {
		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * fma((K * K), -0.125, 1.0)) + U;
	} else if (t_0 <= -0.05) {
		tmp = fma(((l * J) * cos((0.5 * K))), 2.0, U);
	} else {
		tmp = fma((2.0 * sinh(l)), J, U);
	}
	return tmp;
}
function code(J, l, K, U)
	t_0 = cos(Float64(K / 2.0))
	tmp = 0.0
	if (t_0 <= -0.89)
		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * fma(Float64(K * K), -0.125, 1.0)) + U);
	elseif (t_0 <= -0.05)
		tmp = fma(Float64(Float64(l * J) * cos(Float64(0.5 * K))), 2.0, U);
	else
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	end
	return tmp
end
code[J_, l_, K_, U_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, -0.89], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], If[LessEqual[t$95$0, -0.05], N[(N[(N[(l * J), $MachinePrecision] * N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \cos \left(\frac{K}{2}\right)\\
\mathbf{if}\;t\_0 \leq -0.89:\\
\;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\

\mathbf{elif}\;t\_0 \leq -0.05:\\
\;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.890000000000000013

    1. Initial program 85.5%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. unpow2N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f6487.0

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites87.0%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
    6. Step-by-step derivation
      1. lift-*.f6487.0

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
    7. Applied rewrites87.0%

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
    8. Taylor expanded in J around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. +-commutativeN/A

        \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. *-commutativeN/A

        \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      8. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. lift-*.f6488.8

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    10. Applied rewrites88.8%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    11. Taylor expanded in K around 0

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} + U \]
    12. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + {K}^{2} \cdot \color{blue}{\frac{-1}{8}}\right) + U \]
      2. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + \left(K \cdot K\right) \cdot \frac{-1}{8}\right) + U \]
      3. +-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8} + \color{blue}{1}\right) + U \]
      4. lift-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \color{blue}{\frac{-1}{8}}, 1\right) + U \]
      5. lift-*.f6455.5

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U \]
    13. Applied rewrites55.5%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} + U \]

    if -0.890000000000000013 < (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.050000000000000003

    1. Initial program 86.7%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
      4. associate-*r*N/A

        \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
      6. *-commutativeN/A

        \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
      7. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
      8. lower-cos.f64N/A

        \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
      9. lower-*.f6462.9

        \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
    4. Applied rewrites62.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]

    if -0.050000000000000003 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.2%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6495.2

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites95.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 3: 96.2% accurate, 1.2× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ \mathbf{if}\;t\_0 \leq 0.95:\\ \;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot t\_0 + U\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (let* ((t_0 (cos (/ K 2.0))))
   (if (<= t_0 0.95)
     (+
      (*
       (*
        J
        (*
         (fma
          (fma 0.016666666666666666 (* l l) 0.3333333333333333)
          (* l l)
          2.0)
         l))
       t_0)
      U)
     (fma (* 2.0 (sinh l)) J U))))
double code(double J, double l, double K, double U) {
	double t_0 = cos((K / 2.0));
	double tmp;
	if (t_0 <= 0.95) {
		tmp = ((J * (fma(fma(0.016666666666666666, (l * l), 0.3333333333333333), (l * l), 2.0) * l)) * t_0) + U;
	} else {
		tmp = fma((2.0 * sinh(l)), J, U);
	}
	return tmp;
}
function code(J, l, K, U)
	t_0 = cos(Float64(K / 2.0))
	tmp = 0.0
	if (t_0 <= 0.95)
		tmp = Float64(Float64(Float64(J * Float64(fma(fma(0.016666666666666666, Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l)) * t_0) + U);
	else
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	end
	return tmp
end
code[J_, l_, K_, U_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, 0.95], N[(N[(N[(J * N[(N[(N[(0.016666666666666666 * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + U), $MachinePrecision], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \cos \left(\frac{K}{2}\right)\\
\mathbf{if}\;t\_0 \leq 0.95:\\
\;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot t\_0 + U\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.94999999999999996

    1. Initial program 86.1%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. +-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left({\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left(\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) \cdot {\ell}^{2} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. lower-fma.f64N/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. +-commutativeN/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\frac{1}{60} \cdot {\ell}^{2} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. unpow2N/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f64N/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      10. unpow2N/A

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      11. lower-*.f6492.8

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites92.8%

      \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]

    if 0.94999999999999996 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.4%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6498.9

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites98.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 4: 93.9% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.95:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= (cos (/ K 2.0)) 0.95)
   (+ (* (* (* (fma (* l l) 0.3333333333333333 2.0) l) J) (cos (* 0.5 K))) U)
   (fma (* 2.0 (sinh l)) J U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if (cos((K / 2.0)) <= 0.95) {
		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * cos((0.5 * K))) + U;
	} else {
		tmp = fma((2.0 * sinh(l)), J, U);
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (cos(Float64(K / 2.0)) <= 0.95)
		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * cos(Float64(0.5 * K))) + U);
	else
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.95], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.95:\\
\;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.94999999999999996

    1. Initial program 86.1%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. unpow2N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f6485.3

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites85.3%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
    6. Step-by-step derivation
      1. lift-*.f6485.3

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
    7. Applied rewrites85.3%

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
    8. Taylor expanded in J around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. +-commutativeN/A

        \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. *-commutativeN/A

        \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      8. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. lift-*.f6487.8

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    10. Applied rewrites87.8%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]

    if 0.94999999999999996 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.4%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6498.9

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites98.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 5: 93.9% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.95:\\ \;\;\;\;\mathsf{fma}\left(\cos \left(0.5 \cdot K\right), \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= (cos (/ K 2.0)) 0.95)
   (fma (cos (* 0.5 K)) (* (* (fma (* l l) 0.3333333333333333 2.0) l) J) U)
   (fma (* 2.0 (sinh l)) J U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if (cos((K / 2.0)) <= 0.95) {
		tmp = fma(cos((0.5 * K)), ((fma((l * l), 0.3333333333333333, 2.0) * l) * J), U);
	} else {
		tmp = fma((2.0 * sinh(l)), J, U);
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (cos(Float64(K / 2.0)) <= 0.95)
		tmp = fma(cos(Float64(0.5 * K)), Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J), U);
	else
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.95], N[(N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] + U), $MachinePrecision], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.95:\\
\;\;\;\;\mathsf{fma}\left(\cos \left(0.5 \cdot K\right), \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J, U\right)\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.94999999999999996

    1. Initial program 86.1%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. unpow2N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f6485.3

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites85.3%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
    6. Step-by-step derivation
      1. lift-*.f6485.3

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
    7. Applied rewrites85.3%

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
    8. Taylor expanded in J around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. +-commutativeN/A

        \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. *-commutativeN/A

        \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      8. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. lift-*.f6487.8

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    10. Applied rewrites87.8%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    11. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U} \]
    12. Applied rewrites87.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right), \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J, U\right)} \]

    if 0.94999999999999996 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.4%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6498.9

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites98.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 6: 86.2% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= (cos (/ K 2.0)) -0.064)
   (+
    (*
     (* (* (fma (* l l) 0.3333333333333333 2.0) l) J)
     (fma (* K K) -0.125 1.0))
    U)
   (fma (* 2.0 (sinh l)) J U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if (cos((K / 2.0)) <= -0.064) {
		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * fma((K * K), -0.125, 1.0)) + U;
	} else {
		tmp = fma((2.0 * sinh(l)), J, U);
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (cos(Float64(K / 2.0)) <= -0.064)
		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * fma(Float64(K * K), -0.125, 1.0)) + U);
	else
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
\;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

    1. Initial program 86.3%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. unpow2N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f6484.8

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites84.8%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
    6. Step-by-step derivation
      1. lift-*.f6484.8

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
    7. Applied rewrites84.8%

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
    8. Taylor expanded in J around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. +-commutativeN/A

        \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. *-commutativeN/A

        \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      8. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. lift-*.f6487.5

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    10. Applied rewrites87.5%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    11. Taylor expanded in K around 0

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} + U \]
    12. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + {K}^{2} \cdot \color{blue}{\frac{-1}{8}}\right) + U \]
      2. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + \left(K \cdot K\right) \cdot \frac{-1}{8}\right) + U \]
      3. +-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8} + \color{blue}{1}\right) + U \]
      4. lift-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \color{blue}{\frac{-1}{8}}, 1\right) + U \]
      5. lift-*.f6459.1

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U \]
    13. Applied rewrites59.1%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} + U \]

    if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.2%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6495.0

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites95.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 7: 88.9% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;K \leq 2 \cdot 10^{-26}:\\ \;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= K 2e-26)
   (fma (* 2.0 (sinh l)) J U)
   (+
    (*
     (*
      J
      (*
       (fma
        (fma
         (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
         (* l l)
         0.3333333333333333)
        (* l l)
        2.0)
       l))
     (cos (/ K 2.0)))
    U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if (K <= 2e-26) {
		tmp = fma((2.0 * sinh(l)), J, U);
	} else {
		tmp = ((J * (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l)) * cos((K / 2.0))) + U;
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (K <= 2e-26)
		tmp = fma(Float64(2.0 * sinh(l)), J, U);
	else
		tmp = Float64(Float64(Float64(J * Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l)) * cos(Float64(K / 2.0))) + U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[K, 2e-26], N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(N[(J * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;K \leq 2 \cdot 10^{-26}:\\
\;\;\;\;\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)\\

\mathbf{else}:\\
\;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if K < 2.0000000000000001e-26

    1. Initial program 86.2%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in K around 0

      \[\leadsto \color{blue}{U + J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)} \]
    3. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) + \color{blue}{U} \]
      2. *-commutativeN/A

        \[\leadsto \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot J + U \]
      3. lower-fma.f64N/A

        \[\leadsto \mathsf{fma}\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}, \color{blue}{J}, U\right) \]
      4. sinh-undefN/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      5. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
      6. lower-sinh.f6486.8

        \[\leadsto \mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right) \]
    4. Applied rewrites86.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(2 \cdot \sinh \ell, J, U\right)} \]

    if 2.0000000000000001e-26 < K

    1. Initial program 86.3%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites94.5%

      \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 8: 82.2% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\ \mathbf{else}:\\ \;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot 1 + U\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (if (<= (cos (/ K 2.0)) -0.064)
   (+
    (*
     (* (* (fma (* l l) 0.3333333333333333 2.0) l) J)
     (fma (* K K) -0.125 1.0))
    U)
   (+
    (*
     (*
      J
      (*
       (fma
        (fma
         (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
         (* l l)
         0.3333333333333333)
        (* l l)
        2.0)
       l))
     1.0)
    U)))
double code(double J, double l, double K, double U) {
	double tmp;
	if (cos((K / 2.0)) <= -0.064) {
		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * fma((K * K), -0.125, 1.0)) + U;
	} else {
		tmp = ((J * (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l)) * 1.0) + U;
	}
	return tmp;
}
function code(J, l, K, U)
	tmp = 0.0
	if (cos(Float64(K / 2.0)) <= -0.064)
		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * fma(Float64(K * K), -0.125, 1.0)) + U);
	else
		tmp = Float64(Float64(Float64(J * Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l)) * 1.0) + U);
	end
	return tmp
end
code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], N[(N[(N[(J * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision]), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
\;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\

\mathbf{else}:\\
\;\;\;\;\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot 1 + U\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

    1. Initial program 86.3%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      7. unpow2N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      8. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      9. lower-*.f6484.8

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites84.8%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
    6. Step-by-step derivation
      1. lift-*.f6484.8

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
    7. Applied rewrites84.8%

      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
    8. Taylor expanded in J around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      3. *-commutativeN/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. +-commutativeN/A

        \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. *-commutativeN/A

        \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      7. lower-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      8. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. lift-*.f6487.5

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    10. Applied rewrites87.5%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
    11. Taylor expanded in K around 0

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} + U \]
    12. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + {K}^{2} \cdot \color{blue}{\frac{-1}{8}}\right) + U \]
      2. pow2N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + \left(K \cdot K\right) \cdot \frac{-1}{8}\right) + U \]
      3. +-commutativeN/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8} + \color{blue}{1}\right) + U \]
      4. lift-fma.f64N/A

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \color{blue}{\frac{-1}{8}}, 1\right) + U \]
      5. lift-*.f6459.1

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U \]
    13. Applied rewrites59.1%

      \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} + U \]

    if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

    1. Initial program 86.2%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Taylor expanded in l around 0

      \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. lower-*.f64N/A

        \[\leadsto \left(J \cdot \left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \color{blue}{\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. Applied rewrites94.5%

      \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    5. Taylor expanded in K around 0

      \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \color{blue}{1} + U \]
    6. Step-by-step derivation
      1. Applied rewrites89.7%

        \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \color{blue}{1} + U \]
    7. Recombined 2 regimes into one program.
    8. Add Preprocessing

    Alternative 9: 80.6% accurate, 2.1× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, 0.016666666666666666, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U\\ \end{array} \end{array} \]
    (FPCore (J l K U)
     :precision binary64
     (if (<= (cos (/ K 2.0)) -0.064)
       (+
        (*
         (* (* (fma (* l l) 0.3333333333333333 2.0) l) J)
         (fma (* K K) -0.125 1.0))
        U)
       (+
        (*
         (*
          (*
           (fma (fma (* l l) 0.016666666666666666 0.3333333333333333) (* l l) 2.0)
           l)
          J)
         1.0)
        U)))
    double code(double J, double l, double K, double U) {
    	double tmp;
    	if (cos((K / 2.0)) <= -0.064) {
    		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * fma((K * K), -0.125, 1.0)) + U;
    	} else {
    		tmp = (((fma(fma((l * l), 0.016666666666666666, 0.3333333333333333), (l * l), 2.0) * l) * J) * 1.0) + U;
    	}
    	return tmp;
    }
    
    function code(J, l, K, U)
    	tmp = 0.0
    	if (cos(Float64(K / 2.0)) <= -0.064)
    		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * fma(Float64(K * K), -0.125, 1.0)) + U);
    	else
    		tmp = Float64(Float64(Float64(Float64(fma(fma(Float64(l * l), 0.016666666666666666, 0.3333333333333333), Float64(l * l), 2.0) * l) * J) * 1.0) + U);
    	end
    	return tmp
    end
    
    code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], N[(N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.016666666666666666 + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
    \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, 0.016666666666666666, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

      1. Initial program 86.3%

        \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. Taylor expanded in l around 0

        \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. lower-*.f64N/A

          \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        3. *-commutativeN/A

          \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        4. lower-fma.f64N/A

          \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        5. *-commutativeN/A

          \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        6. lower-*.f64N/A

          \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        7. unpow2N/A

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        8. lower-*.f64N/A

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        9. lower-*.f6484.8

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. Applied rewrites84.8%

        \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. Taylor expanded in K around 0

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
      6. Step-by-step derivation
        1. lift-*.f6484.8

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
      7. Applied rewrites84.8%

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
      8. Taylor expanded in J around 0

        \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      9. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        2. lower-*.f64N/A

          \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        3. *-commutativeN/A

          \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        4. lower-*.f64N/A

          \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        5. +-commutativeN/A

          \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        6. *-commutativeN/A

          \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        7. lower-fma.f64N/A

          \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        8. pow2N/A

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        9. lift-*.f6487.5

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
      10. Applied rewrites87.5%

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
      11. Taylor expanded in K around 0

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} + U \]
      12. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + {K}^{2} \cdot \color{blue}{\frac{-1}{8}}\right) + U \]
        2. pow2N/A

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + \left(K \cdot K\right) \cdot \frac{-1}{8}\right) + U \]
        3. +-commutativeN/A

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8} + \color{blue}{1}\right) + U \]
        4. lift-fma.f64N/A

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \color{blue}{\frac{-1}{8}}, 1\right) + U \]
        5. lift-*.f6459.1

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U \]
      13. Applied rewrites59.1%

        \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} + U \]

      if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

      1. Initial program 86.2%

        \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. Taylor expanded in l around 0

        \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
      3. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. lower-*.f64N/A

          \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        3. *-commutativeN/A

          \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        4. lower-fma.f64N/A

          \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        5. *-commutativeN/A

          \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        6. lower-*.f64N/A

          \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        7. unpow2N/A

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        8. lower-*.f64N/A

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        9. lower-*.f6484.7

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      4. Applied rewrites84.7%

        \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
      5. Taylor expanded in K around 0

        \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
      6. Step-by-step derivation
        1. Applied rewrites80.1%

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
        2. Taylor expanded in l around 0

          \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J + {\ell}^{2} \cdot \left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J\right)\right)\right)} \cdot 1 + U \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(2 \cdot J + {\ell}^{2} \cdot \left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J\right)\right) \cdot \color{blue}{\ell}\right) \cdot 1 + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(\left(2 \cdot J + {\ell}^{2} \cdot \left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J\right)\right) \cdot \color{blue}{\ell}\right) \cdot 1 + U \]
          3. +-commutativeN/A

            \[\leadsto \left(\left({\ell}^{2} \cdot \left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J\right) + 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          4. *-commutativeN/A

            \[\leadsto \left(\left(\left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J\right) \cdot {\ell}^{2} + 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          5. lower-fma.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\frac{1}{60} \cdot \left(J \cdot {\ell}^{2}\right) + \frac{1}{3} \cdot J, {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          6. lower-fma.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, J \cdot {\ell}^{2}, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          7. *-commutativeN/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, {\ell}^{2} \cdot J, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          8. pow2N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          9. lift-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          10. lift-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          11. lower-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), {\ell}^{2}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          12. pow2N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), \ell \cdot \ell, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          13. lift-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \left(\ell \cdot \ell\right) \cdot J, \frac{1}{3} \cdot J\right), \ell \cdot \ell, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
          14. lift-*.f6485.0

            \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333 \cdot J\right), \ell \cdot \ell, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
        4. Applied rewrites85.0%

          \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333 \cdot J\right), \ell \cdot \ell, 2 \cdot J\right) \cdot \ell\right)} \cdot 1 + U \]
        5. Taylor expanded in J around 0

          \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right)\right)}\right) \cdot 1 + U \]
        6. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right)\right) \cdot J\right) \cdot 1 + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right)\right) \cdot J\right) \cdot 1 + U \]
          3. *-commutativeN/A

            \[\leadsto \left(\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          4. lower-*.f64N/A

            \[\leadsto \left(\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          5. +-commutativeN/A

            \[\leadsto \left(\left(\left({\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          6. *-commutativeN/A

            \[\leadsto \left(\left(\left(\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          7. lower-fma.f64N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}, {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          8. +-commutativeN/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\frac{1}{60} \cdot {\ell}^{2} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          9. *-commutativeN/A

            \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2} \cdot \frac{1}{60} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          10. lower-fma.f64N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{60}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          11. pow2N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{60}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          12. lift-*.f64N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{60}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          13. pow2N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{60}, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          14. lift-*.f6487.6

            \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, 0.016666666666666666, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
        7. Applied rewrites87.6%

          \[\leadsto \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\ell \cdot \ell, 0.016666666666666666, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot 1 + U \]
      7. Recombined 2 regimes into one program.
      8. Add Preprocessing

      Alternative 10: 76.9% accurate, 2.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\\ \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;t\_0 \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot 1 + U\\ \end{array} \end{array} \]
      (FPCore (J l K U)
       :precision binary64
       (let* ((t_0 (* (* (fma (* l l) 0.3333333333333333 2.0) l) J)))
         (if (<= (cos (/ K 2.0)) -0.064)
           (+ (* t_0 (fma (* K K) -0.125 1.0)) U)
           (+ (* t_0 1.0) U))))
      double code(double J, double l, double K, double U) {
      	double t_0 = (fma((l * l), 0.3333333333333333, 2.0) * l) * J;
      	double tmp;
      	if (cos((K / 2.0)) <= -0.064) {
      		tmp = (t_0 * fma((K * K), -0.125, 1.0)) + U;
      	} else {
      		tmp = (t_0 * 1.0) + U;
      	}
      	return tmp;
      }
      
      function code(J, l, K, U)
      	t_0 = Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J)
      	tmp = 0.0
      	if (cos(Float64(K / 2.0)) <= -0.064)
      		tmp = Float64(Float64(t_0 * fma(Float64(K * K), -0.125, 1.0)) + U);
      	else
      		tmp = Float64(Float64(t_0 * 1.0) + U);
      	end
      	return tmp
      end
      
      code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision]}, If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(t$95$0 * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision], N[(N[(t$95$0 * 1.0), $MachinePrecision] + U), $MachinePrecision]]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\\
      \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
      \;\;\;\;t\_0 \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U\\
      
      \mathbf{else}:\\
      \;\;\;\;t\_0 \cdot 1 + U\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

        1. Initial program 86.3%

          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. Taylor expanded in l around 0

          \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          3. *-commutativeN/A

            \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. lower-fma.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          5. *-commutativeN/A

            \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          6. lower-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          7. unpow2N/A

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          8. lower-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          9. lower-*.f6484.8

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        4. Applied rewrites84.8%

          \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
        5. Taylor expanded in K around 0

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} + U \]
        6. Step-by-step derivation
          1. lift-*.f6484.8

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot \color{blue}{K}\right) + U \]
        7. Applied rewrites84.8%

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \color{blue}{\left(0.5 \cdot K\right)} + U \]
        8. Taylor expanded in J around 0

          \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        9. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          3. *-commutativeN/A

            \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          4. lower-*.f64N/A

            \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          5. +-commutativeN/A

            \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          6. *-commutativeN/A

            \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          7. lower-fma.f64N/A

            \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          8. pow2N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
          9. lift-*.f6487.5

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
        10. Applied rewrites87.5%

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot \cos \left(0.5 \cdot K\right) + U \]
        11. Taylor expanded in K around 0

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} + U \]
        12. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + {K}^{2} \cdot \color{blue}{\frac{-1}{8}}\right) + U \]
          2. pow2N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(1 + \left(K \cdot K\right) \cdot \frac{-1}{8}\right) + U \]
          3. +-commutativeN/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8} + \color{blue}{1}\right) + U \]
          4. lift-fma.f64N/A

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \color{blue}{\frac{-1}{8}}, 1\right) + U \]
          5. lift-*.f6459.1

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right) + U \]
        13. Applied rewrites59.1%

          \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} + U \]

        if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

        1. Initial program 86.2%

          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. Taylor expanded in l around 0

          \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
        3. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          3. *-commutativeN/A

            \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. lower-fma.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          5. *-commutativeN/A

            \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          6. lower-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          7. unpow2N/A

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          8. lower-*.f64N/A

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          9. lower-*.f6484.7

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        4. Applied rewrites84.7%

          \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
        5. Taylor expanded in K around 0

          \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
        6. Step-by-step derivation
          1. Applied rewrites80.1%

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
          2. Taylor expanded in J around 0

            \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot 1 + U \]
          3. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot 1 + U \]
            2. lower-*.f64N/A

              \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot 1 + U \]
            3. *-commutativeN/A

              \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            4. lower-*.f64N/A

              \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            5. +-commutativeN/A

              \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            6. *-commutativeN/A

              \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            7. lower-fma.f64N/A

              \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            8. pow2N/A

              \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            9. lift-*.f6482.6

              \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
          4. Applied rewrites82.6%

            \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot 1 + U \]
        7. Recombined 2 regimes into one program.
        8. Add Preprocessing

        Alternative 11: 74.9% accurate, 2.2× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U\\ \end{array} \end{array} \]
        (FPCore (J l K U)
         :precision binary64
         (if (<= (cos (/ K 2.0)) -0.064)
           (fma (* (* l J) (* (* K K) -0.125)) 2.0 U)
           (+ (* (* (* (fma (* l l) 0.3333333333333333 2.0) l) J) 1.0) U)))
        double code(double J, double l, double K, double U) {
        	double tmp;
        	if (cos((K / 2.0)) <= -0.064) {
        		tmp = fma(((l * J) * ((K * K) * -0.125)), 2.0, U);
        	} else {
        		tmp = (((fma((l * l), 0.3333333333333333, 2.0) * l) * J) * 1.0) + U;
        	}
        	return tmp;
        }
        
        function code(J, l, K, U)
        	tmp = 0.0
        	if (cos(Float64(K / 2.0)) <= -0.064)
        		tmp = fma(Float64(Float64(l * J) * Float64(Float64(K * K) * -0.125)), 2.0, U);
        	else
        		tmp = Float64(Float64(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * J) * 1.0) + U);
        	end
        	return tmp
        end
        
        code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(l * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125), $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision]]
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
        \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

          1. Initial program 86.3%

            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. Taylor expanded in l around 0

            \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
          3. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
            2. *-commutativeN/A

              \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
            3. lower-fma.f64N/A

              \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
            4. associate-*r*N/A

              \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
            5. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
            6. *-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
            7. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
            8. lower-cos.f64N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
            9. lower-*.f6464.2

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
          4. Applied rewrites64.2%

            \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
          5. Taylor expanded in K around 0

            \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(1 + \frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
          6. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2} + 1\right), 2, U\right) \]
            2. *-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8} + 1\right), 2, U\right) \]
            3. lower-fma.f64N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right), 2, U\right) \]
            4. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
            5. lower-*.f6451.1

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
          7. Applied rewrites51.1%

            \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
          8. Taylor expanded in K around inf

            \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
          9. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
            2. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
            3. pow2N/A

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8}\right), 2, U\right) \]
            4. lift-*.f6451.1

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]
          10. Applied rewrites51.1%

            \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]

          if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

          1. Initial program 86.2%

            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. Taylor expanded in l around 0

            \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
          3. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. lower-*.f64N/A

              \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            3. *-commutativeN/A

              \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            4. lower-fma.f64N/A

              \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            5. *-commutativeN/A

              \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            6. lower-*.f64N/A

              \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            7. unpow2N/A

              \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            8. lower-*.f64N/A

              \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            9. lower-*.f6484.7

              \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. Applied rewrites84.7%

            \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
          5. Taylor expanded in K around 0

            \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
          6. Step-by-step derivation
            1. Applied rewrites80.1%

              \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
            2. Taylor expanded in J around 0

              \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}\right) \cdot 1 + U \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot 1 + U \]
              2. lower-*.f64N/A

                \[\leadsto \left(\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot J\right) \cdot 1 + U \]
              3. *-commutativeN/A

                \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              4. lower-*.f64N/A

                \[\leadsto \left(\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              5. +-commutativeN/A

                \[\leadsto \left(\left(\left(\frac{1}{3} \cdot {\ell}^{2} + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              6. *-commutativeN/A

                \[\leadsto \left(\left(\left({\ell}^{2} \cdot \frac{1}{3} + 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              7. lower-fma.f64N/A

                \[\leadsto \left(\left(\mathsf{fma}\left({\ell}^{2}, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              8. pow2N/A

                \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, \frac{1}{3}, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
              9. lift-*.f6482.6

                \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot J\right) \cdot 1 + U \]
            4. Applied rewrites82.6%

              \[\leadsto \left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \color{blue}{J}\right) \cdot 1 + U \]
          7. Recombined 2 regimes into one program.
          8. Add Preprocessing

          Alternative 12: 61.1% accurate, 2.3× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U\\ \end{array} \end{array} \]
          (FPCore (J l K U)
           :precision binary64
           (if (<= (cos (/ K 2.0)) -0.064)
             (fma (* (* l J) (* (* K K) -0.125)) 2.0 U)
             (* (fma (/ (* l J) U) 2.0 1.0) U)))
          double code(double J, double l, double K, double U) {
          	double tmp;
          	if (cos((K / 2.0)) <= -0.064) {
          		tmp = fma(((l * J) * ((K * K) * -0.125)), 2.0, U);
          	} else {
          		tmp = fma(((l * J) / U), 2.0, 1.0) * U;
          	}
          	return tmp;
          }
          
          function code(J, l, K, U)
          	tmp = 0.0
          	if (cos(Float64(K / 2.0)) <= -0.064)
          		tmp = fma(Float64(Float64(l * J) * Float64(Float64(K * K) * -0.125)), 2.0, U);
          	else
          		tmp = Float64(fma(Float64(Float64(l * J) / U), 2.0, 1.0) * U);
          	end
          	return tmp
          end
          
          code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(l * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125), $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], N[(N[(N[(N[(l * J), $MachinePrecision] / U), $MachinePrecision] * 2.0 + 1.0), $MachinePrecision] * U), $MachinePrecision]]
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
          \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

            1. Initial program 86.3%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Taylor expanded in l around 0

              \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
              2. *-commutativeN/A

                \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
              4. associate-*r*N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              5. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              6. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              7. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              8. lower-cos.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              9. lower-*.f6464.2

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
            4. Applied rewrites64.2%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
            5. Taylor expanded in K around 0

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(1 + \frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2} + 1\right), 2, U\right) \]
              2. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8} + 1\right), 2, U\right) \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right), 2, U\right) \]
              4. unpow2N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
              5. lower-*.f6451.1

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
            7. Applied rewrites51.1%

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
            8. Taylor expanded in K around inf

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
            9. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
              2. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
              3. pow2N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8}\right), 2, U\right) \]
              4. lift-*.f6451.1

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]
            10. Applied rewrites51.1%

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]

            if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

            1. Initial program 86.2%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Taylor expanded in l around 0

              \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
              2. *-commutativeN/A

                \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
              4. associate-*r*N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              5. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              6. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              7. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              8. lower-cos.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              9. lower-*.f6464.7

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
            4. Applied rewrites64.7%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
            5. Taylor expanded in K around 0

              \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \ell\right) + U \]
              2. associate-*r*N/A

                \[\leadsto \left(2 \cdot J\right) \cdot \ell + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
              4. lift-*.f6460.3

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
            7. Applied rewrites60.3%

              \[\leadsto \mathsf{fma}\left(2 \cdot J, \color{blue}{\ell}, U\right) \]
            8. Taylor expanded in U around inf

              \[\leadsto U \cdot \left(1 + \color{blue}{2 \cdot \frac{J \cdot \ell}{U}}\right) \]
            9. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(1 + 2 \cdot \frac{J \cdot \ell}{U}\right) \cdot U \]
              2. lower-*.f64N/A

                \[\leadsto \left(1 + 2 \cdot \frac{J \cdot \ell}{U}\right) \cdot U \]
              3. +-commutativeN/A

                \[\leadsto \left(2 \cdot \frac{J \cdot \ell}{U} + 1\right) \cdot U \]
              4. *-commutativeN/A

                \[\leadsto \left(\frac{J \cdot \ell}{U} \cdot 2 + 1\right) \cdot U \]
              5. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(\frac{J \cdot \ell}{U}, 2, 1\right) \cdot U \]
              6. lower-/.f64N/A

                \[\leadsto \mathsf{fma}\left(\frac{J \cdot \ell}{U}, 2, 1\right) \cdot U \]
              7. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U \]
              8. lift-*.f6464.3

                \[\leadsto \mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U \]
            10. Applied rewrites64.3%

              \[\leadsto \mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U \]
          3. Recombined 2 regimes into one program.
          4. Add Preprocessing

          Alternative 13: 58.1% accurate, 2.3× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\ \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\ \end{array} \end{array} \]
          (FPCore (J l K U)
           :precision binary64
           (if (<= (cos (/ K 2.0)) -0.064)
             (fma (* (* l J) (* (* K K) -0.125)) 2.0 U)
             (fma (+ J J) l U)))
          double code(double J, double l, double K, double U) {
          	double tmp;
          	if (cos((K / 2.0)) <= -0.064) {
          		tmp = fma(((l * J) * ((K * K) * -0.125)), 2.0, U);
          	} else {
          		tmp = fma((J + J), l, U);
          	}
          	return tmp;
          }
          
          function code(J, l, K, U)
          	tmp = 0.0
          	if (cos(Float64(K / 2.0)) <= -0.064)
          		tmp = fma(Float64(Float64(l * J) * Float64(Float64(K * K) * -0.125)), 2.0, U);
          	else
          		tmp = fma(Float64(J + J), l, U);
          	end
          	return tmp
          end
          
          code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.064], N[(N[(N[(l * J), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.125), $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], N[(N[(J + J), $MachinePrecision] * l + U), $MachinePrecision]]
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.064:\\
          \;\;\;\;\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.064000000000000001

            1. Initial program 86.3%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Taylor expanded in l around 0

              \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
              2. *-commutativeN/A

                \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
              4. associate-*r*N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              5. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              6. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              7. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              8. lower-cos.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              9. lower-*.f6464.2

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
            4. Applied rewrites64.2%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
            5. Taylor expanded in K around 0

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(1 + \frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2} + 1\right), 2, U\right) \]
              2. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8} + 1\right), 2, U\right) \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right), 2, U\right) \]
              4. unpow2N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
              5. lower-*.f6451.1

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
            7. Applied rewrites51.1%

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
            8. Taylor expanded in K around inf

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
            9. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
              2. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8}\right), 2, U\right) \]
              3. pow2N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot \frac{-1}{8}\right), 2, U\right) \]
              4. lift-*.f6451.1

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]
            10. Applied rewrites51.1%

              \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\left(K \cdot K\right) \cdot -0.125\right), 2, U\right) \]

            if -0.064000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

            1. Initial program 86.2%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Taylor expanded in l around 0

              \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
            3. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
              2. *-commutativeN/A

                \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
              4. associate-*r*N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              5. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              6. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              7. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              8. lower-cos.f64N/A

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
              9. lower-*.f6464.7

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
            4. Applied rewrites64.7%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
            5. Taylor expanded in K around 0

              \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto 2 \cdot \left(J \cdot \ell\right) + U \]
              2. associate-*r*N/A

                \[\leadsto \left(2 \cdot J\right) \cdot \ell + U \]
              3. lower-fma.f64N/A

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
              4. lift-*.f6460.3

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
            7. Applied rewrites60.3%

              \[\leadsto \mathsf{fma}\left(2 \cdot J, \color{blue}{\ell}, U\right) \]
            8. Step-by-step derivation
              1. lift-*.f64N/A

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
              2. count-2-revN/A

                \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
              3. lower-+.f6460.3

                \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
            9. Applied rewrites60.3%

              \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
          3. Recombined 2 regimes into one program.
          4. Add Preprocessing

          Alternative 14: 69.2% accurate, 7.0× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\ell \leq -4.8 \cdot 10^{+81}:\\ \;\;\;\;\left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\ \mathbf{elif}\;\ell \leq -330000:\\ \;\;\;\;\mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right)\\ \mathbf{elif}\;\ell \leq 2.1 \cdot 10^{+23}:\\ \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\ \end{array} \end{array} \]
          (FPCore (J l K U)
           :precision binary64
           (if (<= l -4.8e+81)
             (+ (* (* (* (* (* l J) l) 0.3333333333333333) l) 1.0) U)
             (if (<= l -330000.0)
               (fma (* l (* J (fma (* K K) -0.125 1.0))) 2.0 U)
               (if (<= l 2.1e+23)
                 (fma (+ J J) l U)
                 (+ (* (* (* (* (* l l) J) 0.3333333333333333) l) 1.0) U)))))
          double code(double J, double l, double K, double U) {
          	double tmp;
          	if (l <= -4.8e+81) {
          		tmp = (((((l * J) * l) * 0.3333333333333333) * l) * 1.0) + U;
          	} else if (l <= -330000.0) {
          		tmp = fma((l * (J * fma((K * K), -0.125, 1.0))), 2.0, U);
          	} else if (l <= 2.1e+23) {
          		tmp = fma((J + J), l, U);
          	} else {
          		tmp = (((((l * l) * J) * 0.3333333333333333) * l) * 1.0) + U;
          	}
          	return tmp;
          }
          
          function code(J, l, K, U)
          	tmp = 0.0
          	if (l <= -4.8e+81)
          		tmp = Float64(Float64(Float64(Float64(Float64(Float64(l * J) * l) * 0.3333333333333333) * l) * 1.0) + U);
          	elseif (l <= -330000.0)
          		tmp = fma(Float64(l * Float64(J * fma(Float64(K * K), -0.125, 1.0))), 2.0, U);
          	elseif (l <= 2.1e+23)
          		tmp = fma(Float64(J + J), l, U);
          	else
          		tmp = Float64(Float64(Float64(Float64(Float64(Float64(l * l) * J) * 0.3333333333333333) * l) * 1.0) + U);
          	end
          	return tmp
          end
          
          code[J_, l_, K_, U_] := If[LessEqual[l, -4.8e+81], N[(N[(N[(N[(N[(N[(l * J), $MachinePrecision] * l), $MachinePrecision] * 0.3333333333333333), $MachinePrecision] * l), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision], If[LessEqual[l, -330000.0], N[(N[(l * N[(J * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], If[LessEqual[l, 2.1e+23], N[(N[(J + J), $MachinePrecision] * l + U), $MachinePrecision], N[(N[(N[(N[(N[(N[(l * l), $MachinePrecision] * J), $MachinePrecision] * 0.3333333333333333), $MachinePrecision] * l), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision]]]]
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;\ell \leq -4.8 \cdot 10^{+81}:\\
          \;\;\;\;\left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\
          
          \mathbf{elif}\;\ell \leq -330000:\\
          \;\;\;\;\mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right)\\
          
          \mathbf{elif}\;\ell \leq 2.1 \cdot 10^{+23}:\\
          \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 4 regimes
          2. if l < -4.79999999999999979e81

            1. Initial program 100.0%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Taylor expanded in l around 0

              \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
            3. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. lower-*.f64N/A

                \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              3. *-commutativeN/A

                \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              4. lower-fma.f64N/A

                \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              5. *-commutativeN/A

                \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              6. lower-*.f64N/A

                \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              7. unpow2N/A

                \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              8. lower-*.f64N/A

                \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              9. lower-*.f6487.3

                \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            4. Applied rewrites87.3%

              \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
            5. Taylor expanded in K around 0

              \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
            6. Step-by-step derivation
              1. Applied rewrites66.1%

                \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
              2. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                2. lift-*.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                3. associate-*l*N/A

                  \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                4. *-commutativeN/A

                  \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(J \cdot \ell\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                5. lower-*.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(J \cdot \ell\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                6. *-commutativeN/A

                  \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                7. lift-*.f6463.9

                  \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
              3. Applied rewrites63.9%

                \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
              4. Taylor expanded in l around inf

                \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right)\right) \cdot \ell\right) \cdot 1 + U \]
              5. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                2. lower-*.f64N/A

                  \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                3. *-commutativeN/A

                  \[\leadsto \left(\left(\left({\ell}^{2} \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                4. pow2N/A

                  \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                5. associate-*r*N/A

                  \[\leadsto \left(\left(\left(\ell \cdot \left(\ell \cdot J\right)\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                6. *-commutativeN/A

                  \[\leadsto \left(\left(\left(\ell \cdot \left(J \cdot \ell\right)\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                7. *-commutativeN/A

                  \[\leadsto \left(\left(\left(\left(J \cdot \ell\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                8. lower-*.f64N/A

                  \[\leadsto \left(\left(\left(\left(J \cdot \ell\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                9. *-commutativeN/A

                  \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                10. lift-*.f6463.9

                  \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]
              6. Applied rewrites63.9%

                \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]

              if -4.79999999999999979e81 < l < -3.3e5

              1. Initial program 100.0%

                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. Taylor expanded in l around 0

                \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
              3. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
                2. *-commutativeN/A

                  \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
                3. lower-fma.f64N/A

                  \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
                4. associate-*r*N/A

                  \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                5. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                6. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                8. lower-cos.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                9. lower-*.f6410.0

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
              4. Applied rewrites10.0%

                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
              5. Taylor expanded in K around 0

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(1 + \frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2} + 1\right), 2, U\right) \]
                2. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8} + 1\right), 2, U\right) \]
                3. lower-fma.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right), 2, U\right) \]
                4. unpow2N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                5. lower-*.f6420.0

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
              7. Applied rewrites20.0%

                \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                2. lift-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                3. associate-*l*N/A

                  \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right)\right), 2, U\right) \]
                4. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right)\right), 2, U\right) \]
                5. lower-*.f6420.0

                  \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right) \]
              9. Applied rewrites20.0%

                \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right) \]

              if -3.3e5 < l < 2.1000000000000001e23

              1. Initial program 74.1%

                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. Taylor expanded in l around 0

                \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
              3. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
                2. *-commutativeN/A

                  \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
                3. lower-fma.f64N/A

                  \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
                4. associate-*r*N/A

                  \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                5. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                6. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                7. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                8. lower-cos.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                9. lower-*.f6495.5

                  \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
              4. Applied rewrites95.5%

                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
              5. Taylor expanded in K around 0

                \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto 2 \cdot \left(J \cdot \ell\right) + U \]
                2. associate-*r*N/A

                  \[\leadsto \left(2 \cdot J\right) \cdot \ell + U \]
                3. lower-fma.f64N/A

                  \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                4. lift-*.f6482.9

                  \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
              7. Applied rewrites82.9%

                \[\leadsto \mathsf{fma}\left(2 \cdot J, \color{blue}{\ell}, U\right) \]
              8. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                2. count-2-revN/A

                  \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                3. lower-+.f6482.9

                  \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
              9. Applied rewrites82.9%

                \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]

              if 2.1000000000000001e23 < l

              1. Initial program 100.0%

                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. Taylor expanded in l around 0

                \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
              3. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. lower-*.f64N/A

                  \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                3. *-commutativeN/A

                  \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                4. lower-fma.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                5. *-commutativeN/A

                  \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                6. lower-*.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                7. unpow2N/A

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                8. lower-*.f64N/A

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                9. lower-*.f6474.0

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              4. Applied rewrites74.0%

                \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
              5. Taylor expanded in K around 0

                \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
              6. Step-by-step derivation
                1. Applied rewrites55.2%

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
                2. Taylor expanded in l around inf

                  \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right)\right) \cdot \ell\right) \cdot 1 + U \]
                3. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                  2. lower-*.f64N/A

                    \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                  3. *-commutativeN/A

                    \[\leadsto \left(\left(\left({\ell}^{2} \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                  4. pow2N/A

                    \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                  5. lift-*.f64N/A

                    \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                  6. lift-*.f6455.2

                    \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]
                4. Applied rewrites55.2%

                  \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]
              7. Recombined 4 regimes into one program.
              8. Add Preprocessing

              Alternative 15: 68.8% accurate, 7.0× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\ \mathbf{if}\;\ell \leq -4.8 \cdot 10^{+81}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;\ell \leq -330000:\\ \;\;\;\;\mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right)\\ \mathbf{elif}\;\ell \leq 2.1 \cdot 10^{+23}:\\ \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
              (FPCore (J l K U)
               :precision binary64
               (let* ((t_0 (+ (* (* (* (* (* l J) l) 0.3333333333333333) l) 1.0) U)))
                 (if (<= l -4.8e+81)
                   t_0
                   (if (<= l -330000.0)
                     (fma (* l (* J (fma (* K K) -0.125 1.0))) 2.0 U)
                     (if (<= l 2.1e+23) (fma (+ J J) l U) t_0)))))
              double code(double J, double l, double K, double U) {
              	double t_0 = (((((l * J) * l) * 0.3333333333333333) * l) * 1.0) + U;
              	double tmp;
              	if (l <= -4.8e+81) {
              		tmp = t_0;
              	} else if (l <= -330000.0) {
              		tmp = fma((l * (J * fma((K * K), -0.125, 1.0))), 2.0, U);
              	} else if (l <= 2.1e+23) {
              		tmp = fma((J + J), l, U);
              	} else {
              		tmp = t_0;
              	}
              	return tmp;
              }
              
              function code(J, l, K, U)
              	t_0 = Float64(Float64(Float64(Float64(Float64(Float64(l * J) * l) * 0.3333333333333333) * l) * 1.0) + U)
              	tmp = 0.0
              	if (l <= -4.8e+81)
              		tmp = t_0;
              	elseif (l <= -330000.0)
              		tmp = fma(Float64(l * Float64(J * fma(Float64(K * K), -0.125, 1.0))), 2.0, U);
              	elseif (l <= 2.1e+23)
              		tmp = fma(Float64(J + J), l, U);
              	else
              		tmp = t_0;
              	end
              	return tmp
              end
              
              code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[(N[(N[(N[(N[(l * J), $MachinePrecision] * l), $MachinePrecision] * 0.3333333333333333), $MachinePrecision] * l), $MachinePrecision] * 1.0), $MachinePrecision] + U), $MachinePrecision]}, If[LessEqual[l, -4.8e+81], t$95$0, If[LessEqual[l, -330000.0], N[(N[(l * N[(J * N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * 2.0 + U), $MachinePrecision], If[LessEqual[l, 2.1e+23], N[(N[(J + J), $MachinePrecision] * l + U), $MachinePrecision], t$95$0]]]]
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              t_0 := \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U\\
              \mathbf{if}\;\ell \leq -4.8 \cdot 10^{+81}:\\
              \;\;\;\;t\_0\\
              
              \mathbf{elif}\;\ell \leq -330000:\\
              \;\;\;\;\mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right)\\
              
              \mathbf{elif}\;\ell \leq 2.1 \cdot 10^{+23}:\\
              \;\;\;\;\mathsf{fma}\left(J + J, \ell, U\right)\\
              
              \mathbf{else}:\\
              \;\;\;\;t\_0\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 3 regimes
              2. if l < -4.79999999999999979e81 or 2.1000000000000001e23 < l

                1. Initial program 100.0%

                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. Taylor expanded in l around 0

                  \[\leadsto \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                3. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  2. lower-*.f64N/A

                    \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right) + 2 \cdot J\right) \cdot \color{blue}{\ell}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  3. *-commutativeN/A

                    \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3} + 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  4. lower-fma.f64N/A

                    \[\leadsto \left(\mathsf{fma}\left(J \cdot {\ell}^{2}, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  5. *-commutativeN/A

                    \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  6. lower-*.f64N/A

                    \[\leadsto \left(\mathsf{fma}\left({\ell}^{2} \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  7. unpow2N/A

                    \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  8. lower-*.f64N/A

                    \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  9. lower-*.f6479.9

                    \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                4. Applied rewrites79.9%

                  \[\leadsto \color{blue}{\left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                5. Taylor expanded in K around 0

                  \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
                6. Step-by-step derivation
                  1. Applied rewrites60.0%

                    \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot \color{blue}{1} + U \]
                  2. Step-by-step derivation
                    1. lift-*.f64N/A

                      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    2. lift-*.f64N/A

                      \[\leadsto \left(\mathsf{fma}\left(\left(\ell \cdot \ell\right) \cdot J, \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    3. associate-*l*N/A

                      \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    4. *-commutativeN/A

                      \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(J \cdot \ell\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    5. lower-*.f64N/A

                      \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(J \cdot \ell\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    6. *-commutativeN/A

                      \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), \frac{1}{3}, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                    7. lift-*.f6458.2

                      \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                  3. Applied rewrites58.2%

                    \[\leadsto \left(\mathsf{fma}\left(\ell \cdot \left(\ell \cdot J\right), 0.3333333333333333, 2 \cdot J\right) \cdot \ell\right) \cdot 1 + U \]
                  4. Taylor expanded in l around inf

                    \[\leadsto \left(\left(\frac{1}{3} \cdot \left(J \cdot {\ell}^{2}\right)\right) \cdot \ell\right) \cdot 1 + U \]
                  5. Step-by-step derivation
                    1. *-commutativeN/A

                      \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    2. lower-*.f64N/A

                      \[\leadsto \left(\left(\left(J \cdot {\ell}^{2}\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    3. *-commutativeN/A

                      \[\leadsto \left(\left(\left({\ell}^{2} \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    4. pow2N/A

                      \[\leadsto \left(\left(\left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    5. associate-*r*N/A

                      \[\leadsto \left(\left(\left(\ell \cdot \left(\ell \cdot J\right)\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    6. *-commutativeN/A

                      \[\leadsto \left(\left(\left(\ell \cdot \left(J \cdot \ell\right)\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    7. *-commutativeN/A

                      \[\leadsto \left(\left(\left(\left(J \cdot \ell\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    8. lower-*.f64N/A

                      \[\leadsto \left(\left(\left(\left(J \cdot \ell\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    9. *-commutativeN/A

                      \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot \frac{1}{3}\right) \cdot \ell\right) \cdot 1 + U \]
                    10. lift-*.f6458.2

                      \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]
                  6. Applied rewrites58.2%

                    \[\leadsto \left(\left(\left(\left(\ell \cdot J\right) \cdot \ell\right) \cdot 0.3333333333333333\right) \cdot \ell\right) \cdot 1 + U \]

                  if -4.79999999999999979e81 < l < -3.3e5

                  1. Initial program 100.0%

                    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  2. Taylor expanded in l around 0

                    \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                  3. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
                    2. *-commutativeN/A

                      \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
                    3. lower-fma.f64N/A

                      \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
                    4. associate-*r*N/A

                      \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    5. lower-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    6. *-commutativeN/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    7. lower-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    8. lower-cos.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    9. lower-*.f6410.0

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
                  4. Applied rewrites10.0%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
                  5. Taylor expanded in K around 0

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(1 + \frac{-1}{8} \cdot {K}^{2}\right), 2, U\right) \]
                  6. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left(\frac{-1}{8} \cdot {K}^{2} + 1\right), 2, U\right) \]
                    2. *-commutativeN/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \left({K}^{2} \cdot \frac{-1}{8} + 1\right), 2, U\right) \]
                    3. lower-fma.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right), 2, U\right) \]
                    4. unpow2N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                    5. lower-*.f6420.0

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
                  7. Applied rewrites20.0%

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right), 2, U\right) \]
                  8. Step-by-step derivation
                    1. lift-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                    2. lift-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right), 2, U\right) \]
                    3. associate-*l*N/A

                      \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right)\right), 2, U\right) \]
                    4. lower-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, \frac{-1}{8}, 1\right)\right), 2, U\right) \]
                    5. lower-*.f6420.0

                      \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right) \]
                  9. Applied rewrites20.0%

                    \[\leadsto \mathsf{fma}\left(\ell \cdot \left(J \cdot \mathsf{fma}\left(K \cdot K, -0.125, 1\right)\right), 2, U\right) \]

                  if -3.3e5 < l < 2.1000000000000001e23

                  1. Initial program 74.1%

                    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  2. Taylor expanded in l around 0

                    \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                  3. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
                    2. *-commutativeN/A

                      \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
                    3. lower-fma.f64N/A

                      \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
                    4. associate-*r*N/A

                      \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    5. lower-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    6. *-commutativeN/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    7. lower-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    8. lower-cos.f64N/A

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                    9. lower-*.f6495.5

                      \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
                  4. Applied rewrites95.5%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
                  5. Taylor expanded in K around 0

                    \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                  6. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto 2 \cdot \left(J \cdot \ell\right) + U \]
                    2. associate-*r*N/A

                      \[\leadsto \left(2 \cdot J\right) \cdot \ell + U \]
                    3. lower-fma.f64N/A

                      \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                    4. lift-*.f6482.9

                      \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                  7. Applied rewrites82.9%

                    \[\leadsto \mathsf{fma}\left(2 \cdot J, \color{blue}{\ell}, U\right) \]
                  8. Step-by-step derivation
                    1. lift-*.f64N/A

                      \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                    2. count-2-revN/A

                      \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                    3. lower-+.f6482.9

                      \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                  9. Applied rewrites82.9%

                    \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                7. Recombined 3 regimes into one program.
                8. Add Preprocessing

                Alternative 16: 54.7% accurate, 33.0× speedup?

                \[\begin{array}{l} \\ \mathsf{fma}\left(J + J, \ell, U\right) \end{array} \]
                (FPCore (J l K U) :precision binary64 (fma (+ J J) l U))
                double code(double J, double l, double K, double U) {
                	return fma((J + J), l, U);
                }
                
                function code(J, l, K, U)
                	return fma(Float64(J + J), l, U)
                end
                
                code[J_, l_, K_, U_] := N[(N[(J + J), $MachinePrecision] * l + U), $MachinePrecision]
                
                \begin{array}{l}
                
                \\
                \mathsf{fma}\left(J + J, \ell, U\right)
                \end{array}
                
                Derivation
                1. Initial program 86.2%

                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. Taylor expanded in l around 0

                  \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                3. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + \color{blue}{U} \]
                  2. *-commutativeN/A

                    \[\leadsto \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot 2 + U \]
                  3. lower-fma.f64N/A

                    \[\leadsto \mathsf{fma}\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \color{blue}{2}, U\right) \]
                  4. associate-*r*N/A

                    \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                  5. lower-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                  6. *-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                  7. lower-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                  8. lower-cos.f64N/A

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right), 2, U\right) \]
                  9. lower-*.f6464.5

                    \[\leadsto \mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right) \]
                4. Applied rewrites64.5%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\ell \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), 2, U\right)} \]
                5. Taylor expanded in K around 0

                  \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                6. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto 2 \cdot \left(J \cdot \ell\right) + U \]
                  2. associate-*r*N/A

                    \[\leadsto \left(2 \cdot J\right) \cdot \ell + U \]
                  3. lower-fma.f64N/A

                    \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                  4. lift-*.f6454.7

                    \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                7. Applied rewrites54.7%

                  \[\leadsto \mathsf{fma}\left(2 \cdot J, \color{blue}{\ell}, U\right) \]
                8. Step-by-step derivation
                  1. lift-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(2 \cdot J, \ell, U\right) \]
                  2. count-2-revN/A

                    \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                  3. lower-+.f6454.7

                    \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                9. Applied rewrites54.7%

                  \[\leadsto \mathsf{fma}\left(J + J, \ell, U\right) \]
                10. Add Preprocessing

                Alternative 17: 37.3% accurate, 330.0× speedup?

                \[\begin{array}{l} \\ U \end{array} \]
                (FPCore (J l K U) :precision binary64 U)
                double code(double J, double l, double K, double U) {
                	return U;
                }
                
                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(j, l, k, u)
                use fmin_fmax_functions
                    real(8), intent (in) :: j
                    real(8), intent (in) :: l
                    real(8), intent (in) :: k
                    real(8), intent (in) :: u
                    code = u
                end function
                
                public static double code(double J, double l, double K, double U) {
                	return U;
                }
                
                def code(J, l, K, U):
                	return U
                
                function code(J, l, K, U)
                	return U
                end
                
                function tmp = code(J, l, K, U)
                	tmp = U;
                end
                
                code[J_, l_, K_, U_] := U
                
                \begin{array}{l}
                
                \\
                U
                \end{array}
                
                Derivation
                1. Initial program 86.2%

                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. Taylor expanded in J around 0

                  \[\leadsto \color{blue}{U} \]
                3. Step-by-step derivation
                  1. Applied rewrites37.3%

                    \[\leadsto \color{blue}{U} \]
                  2. Add Preprocessing

                  Reproduce

                  ?
                  herbie shell --seed 2025107 
                  (FPCore (J l K U)
                    :name "Maksimov and Kolovsky, Equation (4)"
                    :precision binary64
                    (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))