Toniolo and Linder, Equation (2)

Percentage Accurate: 83.4% → 98.9%
Time: 6.1s
Alternatives: 7
Speedup: 0.7×

Specification

?
\[\begin{array}{l} \\ \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \end{array} \]
(FPCore (t l Om Omc)
 :precision binary64
 (asin
  (sqrt (/ (- 1.0 (pow (/ Om Omc) 2.0)) (+ 1.0 (* 2.0 (pow (/ t l) 2.0)))))))
double code(double t, double l, double Om, double Omc) {
	return asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t / l), 2.0))))));
}
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(t, l, om, omc)
use fmin_fmax_functions
    real(8), intent (in) :: t
    real(8), intent (in) :: l
    real(8), intent (in) :: om
    real(8), intent (in) :: omc
    code = asin(sqrt(((1.0d0 - ((om / omc) ** 2.0d0)) / (1.0d0 + (2.0d0 * ((t / l) ** 2.0d0))))))
end function
public static double code(double t, double l, double Om, double Omc) {
	return Math.asin(Math.sqrt(((1.0 - Math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * Math.pow((t / l), 2.0))))));
}
def code(t, l, Om, Omc):
	return math.asin(math.sqrt(((1.0 - math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * math.pow((t / l), 2.0))))))
function code(t, l, Om, Omc)
	return asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t / l) ^ 2.0))))))
end
function tmp = code(t, l, Om, Omc)
	tmp = asin(sqrt(((1.0 - ((Om / Omc) ^ 2.0)) / (1.0 + (2.0 * ((t / l) ^ 2.0))))));
end
code[t_, l_, Om_, Omc_] := N[ArcSin[N[Sqrt[N[(N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(2.0 * N[Power[N[(t / l), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right)
\end{array}

Sampling outcomes in binary64 precision:

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 7 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: 83.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \end{array} \]
(FPCore (t l Om Omc)
 :precision binary64
 (asin
  (sqrt (/ (- 1.0 (pow (/ Om Omc) 2.0)) (+ 1.0 (* 2.0 (pow (/ t l) 2.0)))))))
double code(double t, double l, double Om, double Omc) {
	return asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t / l), 2.0))))));
}
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(t, l, om, omc)
use fmin_fmax_functions
    real(8), intent (in) :: t
    real(8), intent (in) :: l
    real(8), intent (in) :: om
    real(8), intent (in) :: omc
    code = asin(sqrt(((1.0d0 - ((om / omc) ** 2.0d0)) / (1.0d0 + (2.0d0 * ((t / l) ** 2.0d0))))))
end function
public static double code(double t, double l, double Om, double Omc) {
	return Math.asin(Math.sqrt(((1.0 - Math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * Math.pow((t / l), 2.0))))));
}
def code(t, l, Om, Omc):
	return math.asin(math.sqrt(((1.0 - math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * math.pow((t / l), 2.0))))))
function code(t, l, Om, Omc)
	return asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t / l) ^ 2.0))))))
end
function tmp = code(t, l, Om, Omc)
	tmp = asin(sqrt(((1.0 - ((Om / Omc) ^ 2.0)) / (1.0 + (2.0 * ((t / l) ^ 2.0))))));
end
code[t_, l_, Om_, Omc_] := N[ArcSin[N[Sqrt[N[(N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(2.0 * N[Power[N[(t / l), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right)
\end{array}

Alternative 1: 98.9% accurate, 0.4× speedup?

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} t_1 := 1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}\\ t_2 := {\left(\frac{Om}{Omc}\right)}^{2}\\ \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - t\_2}{t\_1}}\right) \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \mathsf{fma}\left(-0.5, t\_2, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{\frac{1 - t\_2 \cdot t\_2}{1 + t\_2}}{t\_1}}\right)\\ \end{array} \end{array} \]
t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (let* ((t_1 (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0)))) (t_2 (pow (/ Om Omc) 2.0)))
   (if (<= (asin (sqrt (/ (- 1.0 t_2) t_1))) 0.0)
     (asin (* (/ (* (sqrt 0.5) l_m) t_m) (fma -0.5 t_2 1.0)))
     (asin (sqrt (/ (/ (- 1.0 (* t_2 t_2)) (+ 1.0 t_2)) t_1))))))
t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double t_1 = 1.0 + (2.0 * pow((t_m / l_m), 2.0));
	double t_2 = pow((Om / Omc), 2.0);
	double tmp;
	if (asin(sqrt(((1.0 - t_2) / t_1))) <= 0.0) {
		tmp = asin((((sqrt(0.5) * l_m) / t_m) * fma(-0.5, t_2, 1.0)));
	} else {
		tmp = asin(sqrt((((1.0 - (t_2 * t_2)) / (1.0 + t_2)) / t_1)));
	}
	return tmp;
}
t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	t_1 = Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))
	t_2 = Float64(Om / Omc) ^ 2.0
	tmp = 0.0
	if (asin(sqrt(Float64(Float64(1.0 - t_2) / t_1))) <= 0.0)
		tmp = asin(Float64(Float64(Float64(sqrt(0.5) * l_m) / t_m) * fma(-0.5, t_2, 1.0)));
	else
		tmp = asin(sqrt(Float64(Float64(Float64(1.0 - Float64(t_2 * t_2)) / Float64(1.0 + t_2)) / t_1)));
	end
	return tmp
end
t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := Block[{t$95$1 = N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[N[ArcSin[N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] / t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.0], N[ArcSin[N[(N[(N[(N[Sqrt[0.5], $MachinePrecision] * l$95$m), $MachinePrecision] / t$95$m), $MachinePrecision] * N[(-0.5 * t$95$2 + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(N[(N[(1.0 - N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] / N[(1.0 + t$95$2), $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]]]
\begin{array}{l}
t_m = \left|t\right|
\\
l_m = \left|\ell\right|

\\
\begin{array}{l}
t_1 := 1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}\\
t_2 := {\left(\frac{Om}{Omc}\right)}^{2}\\
\mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - t\_2}{t\_1}}\right) \leq 0:\\
\;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \mathsf{fma}\left(-0.5, t\_2, 1\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\sin^{-1} \left(\sqrt{\frac{\frac{1 - t\_2 \cdot t\_2}{1 + t\_2}}{t\_1}}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 0.0

    1. Initial program 46.9%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
    4. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      2. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      3. *-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      4. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      5. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      6. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      7. lower--.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      8. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      9. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      10. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      11. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      12. lower-*.f6457.3

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
    5. Applied rewrites57.3%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
    6. Taylor expanded in Om around 0

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \left(1 + \color{blue}{\frac{-1}{2} \cdot \frac{{Om}^{2}}{{Omc}^{2}}}\right)\right) \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \left(\frac{-1}{2} \cdot \frac{{Om}^{2}}{{Omc}^{2}} + 1\right)\right) \]
      2. lower-fma.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{{Om}^{2}}{\color{blue}{{Omc}^{2}}}, 1\right)\right) \]
      3. pow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om \cdot Om}{{Omc}^{2}}, 1\right)\right) \]
      4. pow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om \cdot Om}{Omc \cdot Omc}, 1\right)\right) \]
      5. times-fracN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om}{Omc} \cdot \frac{Om}{\color{blue}{Omc}}, 1\right)\right) \]
      6. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
      7. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
      8. lift-/.f6467.5

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \mathsf{fma}\left(-0.5, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
    8. Applied rewrites67.5%

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \mathsf{fma}\left(-0.5, \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}}, 1\right)\right) \]

    if 0.0 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

    1. Initial program 98.6%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift--.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      2. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\color{blue}{\left(\frac{Om}{Omc}\right)}}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      3. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      4. flip--N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\frac{1 \cdot 1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      5. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\frac{1 \cdot 1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      6. metadata-evalN/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{1} - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      7. lower--.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      8. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      9. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      10. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\color{blue}{\left(\frac{Om}{Omc}\right)}}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      11. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      12. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\color{blue}{\left(\frac{Om}{Omc}\right)}}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      13. lower-+.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      14. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      15. lift-/.f6498.6

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\color{blue}{\left(\frac{Om}{Omc}\right)}}^{2}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    4. Applied rewrites98.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2} \cdot {\left(\frac{Om}{Omc}\right)}^{2}}{1 + {\left(\frac{Om}{Omc}\right)}^{2}}}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 2: 98.9% accurate, 0.6× speedup?

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} t_1 := {\left(\frac{Om}{Omc}\right)}^{2}\\ t_2 := 1 - t\_1\\ \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{t\_2}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \mathsf{fma}\left(-0.5, t\_1, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{t\_2}{1 + 2 \cdot \left(\frac{t\_m}{l\_m} \cdot \frac{t\_m}{l\_m}\right)}}\right)\\ \end{array} \end{array} \]
t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (let* ((t_1 (pow (/ Om Omc) 2.0)) (t_2 (- 1.0 t_1)))
   (if (<= (asin (sqrt (/ t_2 (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0)))))) 0.0)
     (asin (* (/ (* (sqrt 0.5) l_m) t_m) (fma -0.5 t_1 1.0)))
     (asin (sqrt (/ t_2 (+ 1.0 (* 2.0 (* (/ t_m l_m) (/ t_m l_m))))))))))
t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double t_1 = pow((Om / Omc), 2.0);
	double t_2 = 1.0 - t_1;
	double tmp;
	if (asin(sqrt((t_2 / (1.0 + (2.0 * pow((t_m / l_m), 2.0)))))) <= 0.0) {
		tmp = asin((((sqrt(0.5) * l_m) / t_m) * fma(-0.5, t_1, 1.0)));
	} else {
		tmp = asin(sqrt((t_2 / (1.0 + (2.0 * ((t_m / l_m) * (t_m / l_m)))))));
	}
	return tmp;
}
t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	t_1 = Float64(Om / Omc) ^ 2.0
	t_2 = Float64(1.0 - t_1)
	tmp = 0.0
	if (asin(sqrt(Float64(t_2 / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))))) <= 0.0)
		tmp = asin(Float64(Float64(Float64(sqrt(0.5) * l_m) / t_m) * fma(-0.5, t_1, 1.0)));
	else
		tmp = asin(sqrt(Float64(t_2 / Float64(1.0 + Float64(2.0 * Float64(Float64(t_m / l_m) * Float64(t_m / l_m)))))));
	end
	return tmp
end
t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := Block[{t$95$1 = N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(1.0 - t$95$1), $MachinePrecision]}, If[LessEqual[N[ArcSin[N[Sqrt[N[(t$95$2 / N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.0], N[ArcSin[N[(N[(N[(N[Sqrt[0.5], $MachinePrecision] * l$95$m), $MachinePrecision] / t$95$m), $MachinePrecision] * N[(-0.5 * t$95$1 + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(t$95$2 / N[(1.0 + N[(2.0 * N[(N[(t$95$m / l$95$m), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]]]
\begin{array}{l}
t_m = \left|t\right|
\\
l_m = \left|\ell\right|

\\
\begin{array}{l}
t_1 := {\left(\frac{Om}{Omc}\right)}^{2}\\
t_2 := 1 - t\_1\\
\mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{t\_2}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0:\\
\;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \mathsf{fma}\left(-0.5, t\_1, 1\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\sin^{-1} \left(\sqrt{\frac{t\_2}{1 + 2 \cdot \left(\frac{t\_m}{l\_m} \cdot \frac{t\_m}{l\_m}\right)}}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 0.0

    1. Initial program 46.9%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
    4. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      2. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      3. *-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      4. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      5. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      6. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      7. lower--.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      8. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      9. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      10. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      11. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      12. lower-*.f6457.3

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
    5. Applied rewrites57.3%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
    6. Taylor expanded in Om around 0

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \left(1 + \color{blue}{\frac{-1}{2} \cdot \frac{{Om}^{2}}{{Omc}^{2}}}\right)\right) \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \left(\frac{-1}{2} \cdot \frac{{Om}^{2}}{{Omc}^{2}} + 1\right)\right) \]
      2. lower-fma.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{{Om}^{2}}{\color{blue}{{Omc}^{2}}}, 1\right)\right) \]
      3. pow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om \cdot Om}{{Omc}^{2}}, 1\right)\right) \]
      4. pow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om \cdot Om}{Omc \cdot Omc}, 1\right)\right) \]
      5. times-fracN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, \frac{Om}{Omc} \cdot \frac{Om}{\color{blue}{Omc}}, 1\right)\right) \]
      6. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
      7. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \mathsf{fma}\left(\frac{-1}{2}, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
      8. lift-/.f6467.5

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \mathsf{fma}\left(-0.5, {\left(\frac{Om}{Omc}\right)}^{2}, 1\right)\right) \]
    8. Applied rewrites67.5%

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \mathsf{fma}\left(-0.5, \color{blue}{{\left(\frac{Om}{Omc}\right)}^{2}}, 1\right)\right) \]

    if 0.0 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

    1. Initial program 98.6%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\color{blue}{\left(\frac{t}{\ell}\right)}}^{2}}}\right) \]
      2. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \color{blue}{{\left(\frac{t}{\ell}\right)}^{2}}}}\right) \]
      3. unpow2N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
      4. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
      5. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
      6. lift-/.f6498.6

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
    4. Applied rewrites98.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 3: 98.4% accurate, 0.6× speedup?

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} t_1 := 1 - {\left(\frac{Om}{Omc}\right)}^{2}\\ \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{t\_1}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 10^{-17}:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \sqrt{t\_1}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\ \end{array} \end{array} \]
t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (let* ((t_1 (- 1.0 (pow (/ Om Omc) 2.0))))
   (if (<= (asin (sqrt (/ t_1 (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0)))))) 1e-17)
     (asin (* (/ (* (sqrt 0.5) l_m) t_m) (sqrt t_1)))
     (asin (sqrt (/ 1.0 (fma (* 2.0 (/ t_m l_m)) (/ t_m l_m) 1.0)))))))
t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double t_1 = 1.0 - pow((Om / Omc), 2.0);
	double tmp;
	if (asin(sqrt((t_1 / (1.0 + (2.0 * pow((t_m / l_m), 2.0)))))) <= 1e-17) {
		tmp = asin((((sqrt(0.5) * l_m) / t_m) * sqrt(t_1)));
	} else {
		tmp = asin(sqrt((1.0 / fma((2.0 * (t_m / l_m)), (t_m / l_m), 1.0))));
	}
	return tmp;
}
t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	t_1 = Float64(1.0 - (Float64(Om / Omc) ^ 2.0))
	tmp = 0.0
	if (asin(sqrt(Float64(t_1 / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))))) <= 1e-17)
		tmp = asin(Float64(Float64(Float64(sqrt(0.5) * l_m) / t_m) * sqrt(t_1)));
	else
		tmp = asin(sqrt(Float64(1.0 / fma(Float64(2.0 * Float64(t_m / l_m)), Float64(t_m / l_m), 1.0))));
	end
	return tmp
end
t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := Block[{t$95$1 = N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[ArcSin[N[Sqrt[N[(t$95$1 / N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 1e-17], N[ArcSin[N[(N[(N[(N[Sqrt[0.5], $MachinePrecision] * l$95$m), $MachinePrecision] / t$95$m), $MachinePrecision] * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(1.0 / N[(N[(2.0 * N[(t$95$m / l$95$m), $MachinePrecision]), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]]
\begin{array}{l}
t_m = \left|t\right|
\\
l_m = \left|\ell\right|

\\
\begin{array}{l}
t_1 := 1 - {\left(\frac{Om}{Omc}\right)}^{2}\\
\mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{t\_1}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 10^{-17}:\\
\;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m} \cdot \sqrt{t\_1}\right)\\

\mathbf{else}:\\
\;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 1.00000000000000007e-17

    1. Initial program 67.4%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
    4. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      2. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
      3. *-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      4. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      5. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      6. lower-sqrt.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      7. lower--.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      8. lower-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
      9. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      10. lower-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
      11. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      12. lower-*.f6452.9

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
    5. Applied rewrites52.9%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
    6. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      2. lift-*.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      3. lift-/.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      4. times-fracN/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]
      5. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}\right) \]
      6. lift-pow.f64N/A

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}\right) \]
      7. lift-/.f6461.9

        \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}\right) \]
    7. Applied rewrites61.9%

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}\right) \]

    if 1.00000000000000007e-17 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

    1. Initial program 98.3%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in Om around 0

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
    4. Step-by-step derivation
      1. Applied rewrites97.6%

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      2. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot {\color{blue}{\left(\frac{t}{\ell}\right)}}^{2}}}\right) \]
        2. lift-pow.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{{\left(\frac{t}{\ell}\right)}^{2}}}}\right) \]
        3. unpow2N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        4. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        5. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
        6. lift-/.f6497.6

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
      3. Applied rewrites97.6%

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
      4. Step-by-step derivation
        1. lift-+.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        2. lift-*.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + \color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        3. lift-*.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        4. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
        5. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
        6. +-commutativeN/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right) + 1}}}\right) \]
        7. associate-*r*N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\left(2 \cdot \frac{t}{\ell}\right) \cdot \frac{t}{\ell}} + 1}}\right) \]
        8. lower-fma.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
        9. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(\color{blue}{2 \cdot \frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
        10. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \color{blue}{\frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
        11. lift-/.f6497.6

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \color{blue}{\frac{t}{\ell}}, 1\right)}}\right) \]
      5. Applied rewrites97.6%

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
    5. Recombined 2 regimes into one program.
    6. Add Preprocessing

    Alternative 4: 98.4% accurate, 0.7× speedup?

    \[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 10^{-17}:\\ \;\;\;\;\sin^{-1} \left(\left(l\_m \cdot \frac{\sqrt{0.5}}{t\_m}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\ \end{array} \end{array} \]
    t_m = (fabs.f64 t)
    l_m = (fabs.f64 l)
    (FPCore (t_m l_m Om Omc)
     :precision binary64
     (if (<=
          (asin
           (sqrt
            (/
             (- 1.0 (pow (/ Om Omc) 2.0))
             (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0))))))
          1e-17)
       (asin
        (* (* l_m (/ (sqrt 0.5) t_m)) (sqrt (- 1.0 (* (/ Om Omc) (/ Om Omc))))))
       (asin (sqrt (/ 1.0 (fma (* 2.0 (/ t_m l_m)) (/ t_m l_m) 1.0))))))
    t_m = fabs(t);
    l_m = fabs(l);
    double code(double t_m, double l_m, double Om, double Omc) {
    	double tmp;
    	if (asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t_m / l_m), 2.0)))))) <= 1e-17) {
    		tmp = asin(((l_m * (sqrt(0.5) / t_m)) * sqrt((1.0 - ((Om / Omc) * (Om / Omc))))));
    	} else {
    		tmp = asin(sqrt((1.0 / fma((2.0 * (t_m / l_m)), (t_m / l_m), 1.0))));
    	}
    	return tmp;
    }
    
    t_m = abs(t)
    l_m = abs(l)
    function code(t_m, l_m, Om, Omc)
    	tmp = 0.0
    	if (asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))))) <= 1e-17)
    		tmp = asin(Float64(Float64(l_m * Float64(sqrt(0.5) / t_m)) * sqrt(Float64(1.0 - Float64(Float64(Om / Omc) * Float64(Om / Omc))))));
    	else
    		tmp = asin(sqrt(Float64(1.0 / fma(Float64(2.0 * Float64(t_m / l_m)), Float64(t_m / l_m), 1.0))));
    	end
    	return tmp
    end
    
    t_m = N[Abs[t], $MachinePrecision]
    l_m = N[Abs[l], $MachinePrecision]
    code[t$95$m_, l$95$m_, Om_, Omc_] := If[LessEqual[N[ArcSin[N[Sqrt[N[(N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 1e-17], N[ArcSin[N[(N[(l$95$m * N[(N[Sqrt[0.5], $MachinePrecision] / t$95$m), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(1.0 - N[(N[(Om / Omc), $MachinePrecision] * N[(Om / Omc), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(1.0 / N[(N[(2.0 * N[(t$95$m / l$95$m), $MachinePrecision]), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]
    
    \begin{array}{l}
    t_m = \left|t\right|
    \\
    l_m = \left|\ell\right|
    
    \\
    \begin{array}{l}
    \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 10^{-17}:\\
    \;\;\;\;\sin^{-1} \left(\left(l\_m \cdot \frac{\sqrt{0.5}}{t\_m}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 1.00000000000000007e-17

      1. Initial program 67.4%

        \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      2. Add Preprocessing
      3. Taylor expanded in t around inf

        \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
      4. Step-by-step derivation
        1. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
        2. lower-/.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
        3. *-commutativeN/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        4. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        5. lower-sqrt.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        6. lower-sqrt.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        7. lower--.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        8. lower-/.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
        9. unpow2N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
        10. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
        11. unpow2N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        12. lower-*.f6452.9

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
      5. Applied rewrites52.9%

        \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
      6. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}}\right) \]
        2. lift-*.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        3. lift-sqrt.f64N/A

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        4. *-commutativeN/A

          \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1} - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        5. associate-/l*N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{\color{blue}{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}}\right) \]
        6. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{\color{blue}{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}}\right) \]
        7. lower-/.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \color{blue}{\frac{Om \cdot Om}{Omc \cdot Omc}}}\right) \]
        8. lift-sqrt.f6452.9

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{0.5}}{t}\right) \cdot \sqrt{1 - \frac{\color{blue}{Om \cdot Om}}{Omc \cdot Omc}}\right) \]
      7. Applied rewrites52.9%

        \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{0.5}}{t}\right) \cdot \sqrt{\color{blue}{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}}\right) \]
      8. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        2. lift-*.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        3. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        4. times-fracN/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]
        5. lower-*.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]
        6. lift-/.f64N/A

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{\frac{1}{2}}}{t}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]
        7. lift-/.f6461.8

          \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{0.5}}{t}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]
      9. Applied rewrites61.8%

        \[\leadsto \sin^{-1} \left(\left(\ell \cdot \frac{\sqrt{0.5}}{t}\right) \cdot \sqrt{1 - \frac{Om}{Omc} \cdot \frac{Om}{Omc}}\right) \]

      if 1.00000000000000007e-17 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

      1. Initial program 98.3%

        \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      2. Add Preprocessing
      3. Taylor expanded in Om around 0

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
      4. Step-by-step derivation
        1. Applied rewrites97.6%

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
        2. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot {\color{blue}{\left(\frac{t}{\ell}\right)}}^{2}}}\right) \]
          2. lift-pow.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{{\left(\frac{t}{\ell}\right)}^{2}}}}\right) \]
          3. unpow2N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          4. lower-*.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          5. lift-/.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
          6. lift-/.f6497.6

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
        3. Applied rewrites97.6%

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
        4. Step-by-step derivation
          1. lift-+.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          2. lift-*.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + \color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          3. lift-*.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          4. lift-/.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
          5. lift-/.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
          6. +-commutativeN/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right) + 1}}}\right) \]
          7. associate-*r*N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\left(2 \cdot \frac{t}{\ell}\right) \cdot \frac{t}{\ell}} + 1}}\right) \]
          8. lower-fma.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
          9. lower-*.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(\color{blue}{2 \cdot \frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
          10. lift-/.f64N/A

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \color{blue}{\frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
          11. lift-/.f6497.6

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \color{blue}{\frac{t}{\ell}}, 1\right)}}\right) \]
        5. Applied rewrites97.6%

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
      5. Recombined 2 regimes into one program.
      6. Add Preprocessing

      Alternative 5: 98.1% accurate, 0.7× speedup?

      \[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\ \end{array} \end{array} \]
      t_m = (fabs.f64 t)
      l_m = (fabs.f64 l)
      (FPCore (t_m l_m Om Omc)
       :precision binary64
       (if (<=
            (asin
             (sqrt
              (/
               (- 1.0 (pow (/ Om Omc) 2.0))
               (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0))))))
            0.0)
         (asin (/ (* (sqrt 0.5) l_m) t_m))
         (asin (sqrt (/ 1.0 (fma (* 2.0 (/ t_m l_m)) (/ t_m l_m) 1.0))))))
      t_m = fabs(t);
      l_m = fabs(l);
      double code(double t_m, double l_m, double Om, double Omc) {
      	double tmp;
      	if (asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t_m / l_m), 2.0)))))) <= 0.0) {
      		tmp = asin(((sqrt(0.5) * l_m) / t_m));
      	} else {
      		tmp = asin(sqrt((1.0 / fma((2.0 * (t_m / l_m)), (t_m / l_m), 1.0))));
      	}
      	return tmp;
      }
      
      t_m = abs(t)
      l_m = abs(l)
      function code(t_m, l_m, Om, Omc)
      	tmp = 0.0
      	if (asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))))) <= 0.0)
      		tmp = asin(Float64(Float64(sqrt(0.5) * l_m) / t_m));
      	else
      		tmp = asin(sqrt(Float64(1.0 / fma(Float64(2.0 * Float64(t_m / l_m)), Float64(t_m / l_m), 1.0))));
      	end
      	return tmp
      end
      
      t_m = N[Abs[t], $MachinePrecision]
      l_m = N[Abs[l], $MachinePrecision]
      code[t$95$m_, l$95$m_, Om_, Omc_] := If[LessEqual[N[ArcSin[N[Sqrt[N[(N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.0], N[ArcSin[N[(N[(N[Sqrt[0.5], $MachinePrecision] * l$95$m), $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(1.0 / N[(N[(2.0 * N[(t$95$m / l$95$m), $MachinePrecision]), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]
      
      \begin{array}{l}
      t_m = \left|t\right|
      \\
      l_m = \left|\ell\right|
      
      \\
      \begin{array}{l}
      \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0:\\
      \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m}\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 0.0

        1. Initial program 46.9%

          \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
        2. Add Preprocessing
        3. Taylor expanded in t around inf

          \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
        4. Step-by-step derivation
          1. lower-*.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
          2. lower-/.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
          3. *-commutativeN/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          4. lower-*.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          5. lower-sqrt.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          6. lower-sqrt.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          7. lower--.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          8. lower-/.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
          9. unpow2N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
          10. lower-*.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
          11. unpow2N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
          12. lower-*.f6457.3

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
        5. Applied rewrites57.3%

          \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
        6. Taylor expanded in Om around 0

          \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{\color{blue}{t}}\right) \]
        7. Step-by-step derivation
          1. lower-/.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t}\right) \]
          2. *-commutativeN/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t}\right) \]
          3. lift-sqrt.f64N/A

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t}\right) \]
          4. lift-*.f6467.5

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t}\right) \]
        8. Applied rewrites67.5%

          \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{\color{blue}{t}}\right) \]

        if 0.0 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

        1. Initial program 98.6%

          \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
        2. Add Preprocessing
        3. Taylor expanded in Om around 0

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
        4. Step-by-step derivation
          1. Applied rewrites97.5%

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{1}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
          2. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot {\color{blue}{\left(\frac{t}{\ell}\right)}}^{2}}}\right) \]
            2. lift-pow.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{{\left(\frac{t}{\ell}\right)}^{2}}}}\right) \]
            3. unpow2N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
            4. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
            5. lift-/.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
            6. lift-/.f6497.5

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
          3. Applied rewrites97.5%

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
          4. Step-by-step derivation
            1. lift-+.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
            2. lift-*.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + \color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
            3. lift-*.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \color{blue}{\left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right)}}}\right) \]
            4. lift-/.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\color{blue}{\frac{t}{\ell}} \cdot \frac{t}{\ell}\right)}}\right) \]
            5. lift-/.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{1 + 2 \cdot \left(\frac{t}{\ell} \cdot \color{blue}{\frac{t}{\ell}}\right)}}\right) \]
            6. +-commutativeN/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{2 \cdot \left(\frac{t}{\ell} \cdot \frac{t}{\ell}\right) + 1}}}\right) \]
            7. associate-*r*N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\left(2 \cdot \frac{t}{\ell}\right) \cdot \frac{t}{\ell}} + 1}}\right) \]
            8. lower-fma.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
            9. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(\color{blue}{2 \cdot \frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
            10. lift-/.f64N/A

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \color{blue}{\frac{t}{\ell}}, \frac{t}{\ell}, 1\right)}}\right) \]
            11. lift-/.f6497.5

              \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \color{blue}{\frac{t}{\ell}}, 1\right)}}\right) \]
          5. Applied rewrites97.5%

            \[\leadsto \sin^{-1} \left(\sqrt{\frac{1}{\color{blue}{\mathsf{fma}\left(2 \cdot \frac{t}{\ell}, \frac{t}{\ell}, 1\right)}}}\right) \]
        5. Recombined 2 regimes into one program.
        6. Add Preprocessing

        Alternative 6: 97.0% accurate, 0.7× speedup?

        \[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0.5:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} 1\\ \end{array} \end{array} \]
        t_m = (fabs.f64 t)
        l_m = (fabs.f64 l)
        (FPCore (t_m l_m Om Omc)
         :precision binary64
         (if (<=
              (asin
               (sqrt
                (/
                 (- 1.0 (pow (/ Om Omc) 2.0))
                 (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0))))))
              0.5)
           (asin (/ (* (sqrt 0.5) l_m) t_m))
           (asin 1.0)))
        t_m = fabs(t);
        l_m = fabs(l);
        double code(double t_m, double l_m, double Om, double Omc) {
        	double tmp;
        	if (asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t_m / l_m), 2.0)))))) <= 0.5) {
        		tmp = asin(((sqrt(0.5) * l_m) / t_m));
        	} else {
        		tmp = asin(1.0);
        	}
        	return tmp;
        }
        
        t_m =     private
        l_m =     private
        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(t_m, l_m, om, omc)
        use fmin_fmax_functions
            real(8), intent (in) :: t_m
            real(8), intent (in) :: l_m
            real(8), intent (in) :: om
            real(8), intent (in) :: omc
            real(8) :: tmp
            if (asin(sqrt(((1.0d0 - ((om / omc) ** 2.0d0)) / (1.0d0 + (2.0d0 * ((t_m / l_m) ** 2.0d0)))))) <= 0.5d0) then
                tmp = asin(((sqrt(0.5d0) * l_m) / t_m))
            else
                tmp = asin(1.0d0)
            end if
            code = tmp
        end function
        
        t_m = Math.abs(t);
        l_m = Math.abs(l);
        public static double code(double t_m, double l_m, double Om, double Omc) {
        	double tmp;
        	if (Math.asin(Math.sqrt(((1.0 - Math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * Math.pow((t_m / l_m), 2.0)))))) <= 0.5) {
        		tmp = Math.asin(((Math.sqrt(0.5) * l_m) / t_m));
        	} else {
        		tmp = Math.asin(1.0);
        	}
        	return tmp;
        }
        
        t_m = math.fabs(t)
        l_m = math.fabs(l)
        def code(t_m, l_m, Om, Omc):
        	tmp = 0
        	if math.asin(math.sqrt(((1.0 - math.pow((Om / Omc), 2.0)) / (1.0 + (2.0 * math.pow((t_m / l_m), 2.0)))))) <= 0.5:
        		tmp = math.asin(((math.sqrt(0.5) * l_m) / t_m))
        	else:
        		tmp = math.asin(1.0)
        	return tmp
        
        t_m = abs(t)
        l_m = abs(l)
        function code(t_m, l_m, Om, Omc)
        	tmp = 0.0
        	if (asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0)))))) <= 0.5)
        		tmp = asin(Float64(Float64(sqrt(0.5) * l_m) / t_m));
        	else
        		tmp = asin(1.0);
        	end
        	return tmp
        end
        
        t_m = abs(t);
        l_m = abs(l);
        function tmp_2 = code(t_m, l_m, Om, Omc)
        	tmp = 0.0;
        	if (asin(sqrt(((1.0 - ((Om / Omc) ^ 2.0)) / (1.0 + (2.0 * ((t_m / l_m) ^ 2.0)))))) <= 0.5)
        		tmp = asin(((sqrt(0.5) * l_m) / t_m));
        	else
        		tmp = asin(1.0);
        	end
        	tmp_2 = tmp;
        end
        
        t_m = N[Abs[t], $MachinePrecision]
        l_m = N[Abs[l], $MachinePrecision]
        code[t$95$m_, l$95$m_, Om_, Omc_] := If[LessEqual[N[ArcSin[N[Sqrt[N[(N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.5], N[ArcSin[N[(N[(N[Sqrt[0.5], $MachinePrecision] * l$95$m), $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision], N[ArcSin[1.0], $MachinePrecision]]
        
        \begin{array}{l}
        t_m = \left|t\right|
        \\
        l_m = \left|\ell\right|
        
        \\
        \begin{array}{l}
        \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0.5:\\
        \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5} \cdot l\_m}{t\_m}\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\sin^{-1} 1\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))))) < 0.5

          1. Initial program 68.2%

            \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
          2. Add Preprocessing
          3. Taylor expanded in t around inf

            \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right)} \]
          4. Step-by-step derivation
            1. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \color{blue}{\sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
            2. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t} \cdot \sqrt{\color{blue}{1 - \frac{{Om}^{2}}{{Omc}^{2}}}}\right) \]
            3. *-commutativeN/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            4. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{\color{blue}{1} - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            5. lower-sqrt.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            6. lower-sqrt.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            7. lower--.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            8. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{{Om}^{2}}{{Omc}^{2}}}\right) \]
            9. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
            10. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{{Omc}^{2}}}\right) \]
            11. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
            12. lower-*.f6451.6

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right) \]
          5. Applied rewrites51.6%

            \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5} \cdot \ell}{t} \cdot \sqrt{1 - \frac{Om \cdot Om}{Omc \cdot Omc}}\right)} \]
          6. Taylor expanded in Om around 0

            \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{\color{blue}{t}}\right) \]
          7. Step-by-step derivation
            1. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2}}}{t}\right) \]
            2. *-commutativeN/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t}\right) \]
            3. lift-sqrt.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2}} \cdot \ell}{t}\right) \]
            4. lift-*.f6459.5

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{t}\right) \]
          8. Applied rewrites59.5%

            \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5} \cdot \ell}{\color{blue}{t}}\right) \]

          if 0.5 < (asin.f64 (sqrt.f64 (/.f64 (-.f64 #s(literal 1 binary64) (pow.f64 (/.f64 Om Omc) #s(literal 2 binary64))) (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))))))

          1. Initial program 98.3%

            \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
          2. Add Preprocessing
          3. Taylor expanded in Om around 0

            \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{1}{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}\right)} \]
          4. Step-by-step derivation
            1. sqrt-divN/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{1}}{\color{blue}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            2. metadata-evalN/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\color{blue}{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            3. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\color{blue}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            4. lower-sqrt.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}\right) \]
            5. +-commutativeN/A

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

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

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{{t}^{2}}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            8. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{{t}^{2}}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            9. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            10. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            11. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right) \]
            12. lower-*.f6481.9

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right) \]
          5. Applied rewrites81.9%

            \[\leadsto \sin^{-1} \color{blue}{\left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right)} \]
          6. Taylor expanded in t around 0

            \[\leadsto \sin^{-1} 1 \]
          7. Step-by-step derivation
            1. Applied rewrites96.7%

              \[\leadsto \sin^{-1} 1 \]
          8. Recombined 2 regimes into one program.
          9. Add Preprocessing

          Alternative 7: 50.2% accurate, 3.5× speedup?

          \[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \sin^{-1} 1 \end{array} \]
          t_m = (fabs.f64 t)
          l_m = (fabs.f64 l)
          (FPCore (t_m l_m Om Omc) :precision binary64 (asin 1.0))
          t_m = fabs(t);
          l_m = fabs(l);
          double code(double t_m, double l_m, double Om, double Omc) {
          	return asin(1.0);
          }
          
          t_m =     private
          l_m =     private
          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(t_m, l_m, om, omc)
          use fmin_fmax_functions
              real(8), intent (in) :: t_m
              real(8), intent (in) :: l_m
              real(8), intent (in) :: om
              real(8), intent (in) :: omc
              code = asin(1.0d0)
          end function
          
          t_m = Math.abs(t);
          l_m = Math.abs(l);
          public static double code(double t_m, double l_m, double Om, double Omc) {
          	return Math.asin(1.0);
          }
          
          t_m = math.fabs(t)
          l_m = math.fabs(l)
          def code(t_m, l_m, Om, Omc):
          	return math.asin(1.0)
          
          t_m = abs(t)
          l_m = abs(l)
          function code(t_m, l_m, Om, Omc)
          	return asin(1.0)
          end
          
          t_m = abs(t);
          l_m = abs(l);
          function tmp = code(t_m, l_m, Om, Omc)
          	tmp = asin(1.0);
          end
          
          t_m = N[Abs[t], $MachinePrecision]
          l_m = N[Abs[l], $MachinePrecision]
          code[t$95$m_, l$95$m_, Om_, Omc_] := N[ArcSin[1.0], $MachinePrecision]
          
          \begin{array}{l}
          t_m = \left|t\right|
          \\
          l_m = \left|\ell\right|
          
          \\
          \sin^{-1} 1
          \end{array}
          
          Derivation
          1. Initial program 84.6%

            \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
          2. Add Preprocessing
          3. Taylor expanded in Om around 0

            \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{1}{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}\right)} \]
          4. Step-by-step derivation
            1. sqrt-divN/A

              \[\leadsto \sin^{-1} \left(\frac{\sqrt{1}}{\color{blue}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            2. metadata-evalN/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\color{blue}{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            3. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\color{blue}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}}\right) \]
            4. lower-sqrt.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{1 + 2 \cdot \frac{{t}^{2}}{{\ell}^{2}}}}\right) \]
            5. +-commutativeN/A

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

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

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{{t}^{2}}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            8. lower-/.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{{t}^{2}}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            9. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            10. lower-*.f64N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{{\ell}^{2}}, 2, 1\right)}}\right) \]
            11. unpow2N/A

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right) \]
            12. lower-*.f6464.5

              \[\leadsto \sin^{-1} \left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right) \]
          5. Applied rewrites64.5%

            \[\leadsto \sin^{-1} \color{blue}{\left(\frac{1}{\sqrt{\mathsf{fma}\left(\frac{t \cdot t}{\ell \cdot \ell}, 2, 1\right)}}\right)} \]
          6. Taylor expanded in t around 0

            \[\leadsto \sin^{-1} 1 \]
          7. Step-by-step derivation
            1. Applied rewrites55.1%

              \[\leadsto \sin^{-1} 1 \]
            2. Add Preprocessing

            Reproduce

            ?
            herbie shell --seed 2025085 
            (FPCore (t l Om Omc)
              :name "Toniolo and Linder, Equation (2)"
              :precision binary64
              (asin (sqrt (/ (- 1.0 (pow (/ Om Omc) 2.0)) (+ 1.0 (* 2.0 (pow (/ t l) 2.0)))))))