Toniolo and Linder, Equation (2)

Percentage Accurate: 84.5% → 97.1%

Time: 9.8s

Alternatives: 8

Speedup: 1.1×

Specification

Math

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

FPCore

(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)))))))

C

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))))));
}

Fortran

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

Java

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))))));
}

Python

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))))))

Julia

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

MATLAB

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

Wolfram

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]

Initial Program: 84.5% accurate, 1.0× speedup

Math

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

FPCore

(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)))))))

C

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))))));
}

Fortran

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

Java

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))))));
}

Python

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))))))

Julia

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

MATLAB

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

Wolfram

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]

Alternative 1: 97.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 2 \cdot 10^{-154}:\\ \;\;\;\;\sin^{-1} \left(\frac{l\_m \cdot \sqrt{0.5 \cdot \frac{Omc - \frac{{Om}^{2}}{Omc}}{Omc}}}{t\_m}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1 - \left(-Om\right) \cdot \frac{\frac{-Om}{Omc}}{Omc}}{\mathsf{fma}\left(\frac{t\_m + t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\ \end{array} \end{array} \]

FPCore

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))))))
      2e-154)
   (asin (/ (* l_m (sqrt (* 0.5 (/ (- Omc (/ (pow Om 2.0) Omc)) Omc)))) t_m))
   (asin
    (sqrt
     (/
      (- 1.0 (* (- Om) (/ (/ (- Om) Omc) Omc)))
      (fma (/ (+ t_m t_m) l_m) (/ t_m l_m) 1.0))))))

C

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)))))) <= 2e-154) {
		tmp = asin(((l_m * sqrt((0.5 * ((Omc - (pow(Om, 2.0) / Omc)) / Omc)))) / t_m));
	} else {
		tmp = asin(sqrt(((1.0 - (-Om * ((-Om / Omc) / Omc))) / fma(((t_m + t_m) / l_m), (t_m / l_m), 1.0))));
	}
	return tmp;
}

Julia

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)))))) <= 2e-154)
		tmp = asin(Float64(Float64(l_m * sqrt(Float64(0.5 * Float64(Float64(Omc - Float64((Om ^ 2.0) / Omc)) / Omc)))) / t_m));
	else
		tmp = asin(sqrt(Float64(Float64(1.0 - Float64(Float64(-Om) * Float64(Float64(Float64(-Om) / Omc) / Omc))) / fma(Float64(Float64(t_m + t_m) / l_m), Float64(t_m / l_m), 1.0))));
	end
	return tmp
end

Wolfram

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], 2e-154], N[ArcSin[N[(N[(l$95$m * N[Sqrt[N[(0.5 * N[(N[(Omc - N[(N[Power[Om, 2.0], $MachinePrecision] / Omc), $MachinePrecision]), $MachinePrecision] / Omc), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(N[(1.0 - N[((-Om) * N[(N[((-Om) / Omc), $MachinePrecision] / Omc), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(t$95$m + t$95$m), $MachinePrecision] / l$95$m), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]

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))))))) < 1.9999999999999999e-154

   1. Initial program 84.5%

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

   2. Taylor expanded in t around inf

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

      1. lower-/.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-*.f64 N/A

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

      5. lower-pow.f64 N/A

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

      6. lower--.f64 N/A

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

      7. lower-/.f64 N/A

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

      8. lower-pow.f64 N/A

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

      9. lower-pow.f64 30.7

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

   4. Applied rewrites 30.7%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5 \cdot \left({\ell}^{2} \cdot \left(1 - \frac{{Om}^{2}}{{Omc}^{2}}\right)\right)}}{t}\right)} \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-pow.f64 N/A

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

      4. pow2 N/A

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

      5. lift-*.f64 N/A

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

      6. associate-*r* N/A

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

      7. lift--.f64 N/A

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

      8. lift-/.f64 N/A

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

      9. sub-to-fraction N/A

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

      10. associate-*r/ N/A

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

      11. lift-pow.f64 N/A

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

      12. unpow2 N/A

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

      13. times-frac N/A

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

      14. lower-*.f64 N/A

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

      15. lower-/.f64 N/A

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

      16. lower-*.f64 N/A

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

      17. *-lft-identity N/A

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

      18. lift-pow.f64 N/A

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

      19. unpow2 N/A

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

   6. Applied rewrites 29.2%

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

   7. Taylor expanded in l around 0

      \[\leadsto \sin^{-1} \left(\frac{\ell \cdot \sqrt{\frac{1}{2} \cdot \frac{Omc - \frac{{Om}^{2}}{Omc}}{Omc}}}{t}\right) \]
   8. Step-by-step derivation

      1. lower-*.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-/.f64 N/A

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

      5. lower--.f64 N/A

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

      6. lower-/.f64 N/A

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

      7. lower-pow.f64 45.3

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

   9. Applied rewrites 45.3%

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

   if 1.9999999999999999e-154 < (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 84.5%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
   2. Step-by-step derivation

      1. lift-pow.f64 N/A

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

      2. unpow2 N/A

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

      3. lift-/.f64 N/A

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

      4. frac-2neg N/A

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

      5. associate-*l/ N/A

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

      6. associate-/l* N/A

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

      7. lower-*.f64 N/A

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

      8. lower-neg.f64 N/A

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

      9. frac-2neg N/A

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

      10. remove-double-neg N/A

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

      11. lower-/.f64 N/A

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

      12. lift-/.f64 N/A

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

      13. distribute-neg-frac N/A

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

      14. lower-/.f64 N/A

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

      15. lower-neg.f64 84.5

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

   3. Applied rewrites 84.5%

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

      1. remove-double-neg N/A

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

      2. lift-+.f64 N/A

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

      3. +-commutative N/A

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

      4. distribute-neg-in N/A

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

      5. distribute-neg-in N/A

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

      6. remove-double-neg N/A

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

      7. lift-*.f64 N/A

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

      8. lift-pow.f64 N/A

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

      9. unpow2 N/A

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

      10. associate-*r* N/A

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

      11. count-2-rev N/A

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

      12. remove-double-neg N/A

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

      13. lower-fma.f64 N/A

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

   5. Applied rewrites 84.5%

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

Alternative 2: 92.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right) \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{\left(\left(l\_m \cdot l\_m\right) \cdot \left(1 - \frac{Om}{Omc \cdot Omc} \cdot Om\right)\right) \cdot 0.5}}{t\_m}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{1 - \left(-Om\right) \cdot \frac{\frac{-Om}{Omc}}{Omc}}{\mathsf{fma}\left(\frac{t\_m + t\_m}{l\_m}, \frac{t\_m}{l\_m}, 1\right)}}\right)\\ \end{array} \end{array} \]

FPCore

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 (* (* (* l_m l_m) (- 1.0 (* (/ Om (* Omc Omc)) Om))) 0.5)) t_m))
   (asin
    (sqrt
     (/
      (- 1.0 (* (- Om) (/ (/ (- Om) Omc) Omc)))
      (fma (/ (+ t_m t_m) l_m) (/ t_m l_m) 1.0))))))

C

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((((l_m * l_m) * (1.0 - ((Om / (Omc * Omc)) * Om))) * 0.5)) / t_m));
	} else {
		tmp = asin(sqrt(((1.0 - (-Om * ((-Om / Omc) / Omc))) / fma(((t_m + t_m) / l_m), (t_m / l_m), 1.0))));
	}
	return tmp;
}

Julia

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(sqrt(Float64(Float64(Float64(l_m * l_m) * Float64(1.0 - Float64(Float64(Om / Float64(Omc * Omc)) * Om))) * 0.5)) / t_m));
	else
		tmp = asin(sqrt(Float64(Float64(1.0 - Float64(Float64(-Om) * Float64(Float64(Float64(-Om) / Omc) / Omc))) / fma(Float64(Float64(t_m + t_m) / l_m), Float64(t_m / l_m), 1.0))));
	end
	return tmp
end

Wolfram

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[Sqrt[N[(N[(N[(l$95$m * l$95$m), $MachinePrecision] * N[(1.0 - N[(N[(Om / N[(Omc * Omc), $MachinePrecision]), $MachinePrecision] * Om), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(N[(1.0 - N[((-Om) * N[(N[((-Om) / Omc), $MachinePrecision] / Omc), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(t$95$m + t$95$m), $MachinePrecision] / l$95$m), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]

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 84.5%

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

   2. Taylor expanded in t around inf

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

      1. lower-/.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-*.f64 N/A

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

      5. lower-pow.f64 N/A

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

      6. lower--.f64 N/A

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

      7. lower-/.f64 N/A

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

      8. lower-pow.f64 N/A

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

      9. lower-pow.f64 30.7

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

   4. Applied rewrites 30.7%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5 \cdot \left({\ell}^{2} \cdot \left(1 - \frac{{Om}^{2}}{{Omc}^{2}}\right)\right)}}{t}\right)} \]
   5. Step-by-step derivation

   6. Applied rewrites 33.0%

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

   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 84.5%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
   2. Step-by-step derivation

      1. lift-pow.f64 N/A

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

      2. unpow2 N/A

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

      3. lift-/.f64 N/A

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

      4. frac-2neg N/A

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

      5. associate-*l/ N/A

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

      6. associate-/l* N/A

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

      7. lower-*.f64 N/A

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

      8. lower-neg.f64 N/A

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

      9. frac-2neg N/A

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

      10. remove-double-neg N/A

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

      11. lower-/.f64 N/A

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

      12. lift-/.f64 N/A

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

      13. distribute-neg-frac N/A

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

      14. lower-/.f64 N/A

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

      15. lower-neg.f64 84.5

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

   3. Applied rewrites 84.5%

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

      1. remove-double-neg N/A

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

      2. lift-+.f64 N/A

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

      3. +-commutative N/A

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

      4. distribute-neg-in N/A

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

      5. distribute-neg-in N/A

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

      6. remove-double-neg N/A

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

      7. lift-*.f64 N/A

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

      8. lift-pow.f64 N/A

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

      9. unpow2 N/A

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

      10. associate-*r* N/A

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

      11. count-2-rev N/A

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

      12. remove-double-neg N/A

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

      13. lower-fma.f64 N/A

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

   5. Applied rewrites 84.5%

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

Alternative 3: 91.3% accurate, 0.4× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} t_1 := \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2}}}\right)\\ t_2 := \frac{Om}{Omc \cdot Omc}\\ \mathbf{if}\;t\_1 \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{\left(\left(l\_m \cdot l\_m\right) \cdot \left(1 - t\_2 \cdot Om\right)\right) \cdot 0.5}}{t\_m}\right)\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{-10}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(t\_2, Om, -1\right)}{\mathsf{fma}\left(\frac{-2 \cdot t\_m}{l\_m}, \frac{t\_m}{l\_m}, -1\right)}}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\mathsf{fma}\left(\frac{t\_m + t\_m}{l\_m}, \frac{t\_m}{l\_m} \cdot Omc, Omc\right)}}\right)\\ \end{array} \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (let* ((t_1
         (asin
          (sqrt
           (/
            (- 1.0 (pow (/ Om Omc) 2.0))
            (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0)))))))
        (t_2 (/ Om (* Omc Omc))))
   (if (<= t_1 0.0)
     (asin (/ (sqrt (* (* (* l_m l_m) (- 1.0 (* t_2 Om))) 0.5)) t_m))
     (if (<= t_1 5e-10)
       (asin
        (sqrt
         (/ (fma t_2 Om -1.0) (fma (/ (* -2.0 t_m) l_m) (/ t_m l_m) -1.0))))
       (asin
        (sqrt
         (/
          (- Omc (* (/ Om Omc) Om))
          (fma (/ (+ t_m t_m) l_m) (* (/ t_m l_m) Omc) Omc))))))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double t_1 = asin(sqrt(((1.0 - pow((Om / Omc), 2.0)) / (1.0 + (2.0 * pow((t_m / l_m), 2.0))))));
	double t_2 = Om / (Omc * Omc);
	double tmp;
	if (t_1 <= 0.0) {
		tmp = asin((sqrt((((l_m * l_m) * (1.0 - (t_2 * Om))) * 0.5)) / t_m));
	} else if (t_1 <= 5e-10) {
		tmp = asin(sqrt((fma(t_2, Om, -1.0) / fma(((-2.0 * t_m) / l_m), (t_m / l_m), -1.0))));
	} else {
		tmp = asin(sqrt(((Omc - ((Om / Omc) * Om)) / fma(((t_m + t_m) / l_m), ((t_m / l_m) * Omc), Omc))));
	}
	return tmp;
}

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	t_1 = asin(sqrt(Float64(Float64(1.0 - (Float64(Om / Omc) ^ 2.0)) / Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0))))))
	t_2 = Float64(Om / Float64(Omc * Omc))
	tmp = 0.0
	if (t_1 <= 0.0)
		tmp = asin(Float64(sqrt(Float64(Float64(Float64(l_m * l_m) * Float64(1.0 - Float64(t_2 * Om))) * 0.5)) / t_m));
	elseif (t_1 <= 5e-10)
		tmp = asin(sqrt(Float64(fma(t_2, Om, -1.0) / fma(Float64(Float64(-2.0 * t_m) / l_m), Float64(t_m / l_m), -1.0))));
	else
		tmp = asin(sqrt(Float64(Float64(Omc - Float64(Float64(Om / Omc) * Om)) / fma(Float64(Float64(t_m + t_m) / l_m), Float64(Float64(t_m / l_m) * Omc), Omc))));
	end
	return tmp
end

Wolfram

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[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]}, Block[{t$95$2 = N[(Om / N[(Omc * Omc), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, 0.0], N[ArcSin[N[(N[Sqrt[N[(N[(N[(l$95$m * l$95$m), $MachinePrecision] * N[(1.0 - N[(t$95$2 * Om), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision], If[LessEqual[t$95$1, 5e-10], N[ArcSin[N[Sqrt[N[(N[(t$95$2 * Om + -1.0), $MachinePrecision] / N[(N[(N[(-2.0 * t$95$m), $MachinePrecision] / l$95$m), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], N[ArcSin[N[Sqrt[N[(N[(Omc - N[(N[(Om / Omc), $MachinePrecision] * Om), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(t$95$m + t$95$m), $MachinePrecision] / l$95$m), $MachinePrecision] * N[(N[(t$95$m / l$95$m), $MachinePrecision] * Omc), $MachinePrecision] + Omc), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]]]]]

Derivation

1. Split input into 3 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 84.5%

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

   2. Taylor expanded in t around inf

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

      1. lower-/.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-*.f64 N/A

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

      5. lower-pow.f64 N/A

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

      6. lower--.f64 N/A

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

      7. lower-/.f64 N/A

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

      8. lower-pow.f64 N/A

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

      9. lower-pow.f64 30.7

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

   4. Applied rewrites 30.7%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5 \cdot \left({\ell}^{2} \cdot \left(1 - \frac{{Om}^{2}}{{Omc}^{2}}\right)\right)}}{t}\right)} \]
   5. Step-by-step derivation

   6. Applied rewrites 33.0%

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

   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))))))) < 5.00000000000000031e-10

   1. Initial program 84.5%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
   2. Step-by-step derivation

      1. lift-/.f64 N/A

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

      2. frac-2neg N/A

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

      3. lower-/.f64 N/A

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

   3. Applied rewrites 69.4%

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

   5. Applied rewrites 80.1%

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

   if 5.00000000000000031e-10 < (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 84.5%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
   2. Step-by-step derivation

      1. lift-pow.f64 N/A

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

      2. unpow2 N/A

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

      3. lift-/.f64 N/A

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

      4. frac-2neg N/A

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

      5. associate-*l/ N/A

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

      6. associate-/l* N/A

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

      7. lower-*.f64 N/A

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

      8. lower-neg.f64 N/A

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

      9. frac-2neg N/A

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

      10. remove-double-neg N/A

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

      11. lower-/.f64 N/A

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

      12. lift-/.f64 N/A

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

      13. distribute-neg-frac N/A

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

      14. lower-/.f64 N/A

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

      15. lower-neg.f64 84.5

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

   3. Applied rewrites 84.5%

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

   5. Applied rewrites 68.0%

      \[\leadsto \sin^{-1} \left(\sqrt{\color{blue}{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\mathsf{fma}\left(\frac{t + t}{\ell \cdot \ell} \cdot t, Omc, Omc\right)}}}\right) \]
   6. Step-by-step derivation

      1. lift-fma.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-/.f64 N/A

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

      4. associate-*l/ N/A

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

      5. lift-*.f64 N/A

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

      6. frac-times N/A

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

      7. lift-/.f64 N/A

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

      8. lift-/.f64 N/A

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

      9. associate-*l* N/A

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

      10. lower-fma.f64 N/A

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

      11. lower-*.f64 76.3

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

   7. Applied rewrites 76.3%

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

Alternative 4: 91.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} t_1 := \frac{Om}{Omc \cdot Omc}\\ \mathbf{if}\;\frac{t\_m}{l\_m} \leq 2 \cdot 10^{-11}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\frac{-Om}{Omc}, Om, Omc\right)}{Omc}}\right)\\ \mathbf{elif}\;\frac{t\_m}{l\_m} \leq 5 \cdot 10^{+153}:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(t\_1, Om, -1\right)}{\mathsf{fma}\left(\frac{-2 \cdot t\_m}{l\_m}, \frac{t\_m}{l\_m}, -1\right)}}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{\left(\left(l\_m \cdot l\_m\right) \cdot \left(1 - t\_1 \cdot Om\right)\right) \cdot 0.5}}{t\_m}\right)\\ \end{array} \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (let* ((t_1 (/ Om (* Omc Omc))))
   (if (<= (/ t_m l_m) 2e-11)
     (asin (sqrt (/ (fma (/ (- Om) Omc) Om Omc) Omc)))
     (if (<= (/ t_m l_m) 5e+153)
       (asin
        (sqrt
         (/ (fma t_1 Om -1.0) (fma (/ (* -2.0 t_m) l_m) (/ t_m l_m) -1.0))))
       (asin (/ (sqrt (* (* (* l_m l_m) (- 1.0 (* t_1 Om))) 0.5)) t_m))))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double t_1 = Om / (Omc * Omc);
	double tmp;
	if ((t_m / l_m) <= 2e-11) {
		tmp = asin(sqrt((fma((-Om / Omc), Om, Omc) / Omc)));
	} else if ((t_m / l_m) <= 5e+153) {
		tmp = asin(sqrt((fma(t_1, Om, -1.0) / fma(((-2.0 * t_m) / l_m), (t_m / l_m), -1.0))));
	} else {
		tmp = asin((sqrt((((l_m * l_m) * (1.0 - (t_1 * Om))) * 0.5)) / t_m));
	}
	return tmp;
}

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	t_1 = Float64(Om / Float64(Omc * Omc))
	tmp = 0.0
	if (Float64(t_m / l_m) <= 2e-11)
		tmp = asin(sqrt(Float64(fma(Float64(Float64(-Om) / Omc), Om, Omc) / Omc)));
	elseif (Float64(t_m / l_m) <= 5e+153)
		tmp = asin(sqrt(Float64(fma(t_1, Om, -1.0) / fma(Float64(Float64(-2.0 * t_m) / l_m), Float64(t_m / l_m), -1.0))));
	else
		tmp = asin(Float64(sqrt(Float64(Float64(Float64(l_m * l_m) * Float64(1.0 - Float64(t_1 * Om))) * 0.5)) / t_m));
	end
	return tmp
end

Wolfram

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[(Om / N[(Omc * Omc), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$m / l$95$m), $MachinePrecision], 2e-11], N[ArcSin[N[Sqrt[N[(N[(N[((-Om) / Omc), $MachinePrecision] * Om + Omc), $MachinePrecision] / Omc), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], If[LessEqual[N[(t$95$m / l$95$m), $MachinePrecision], 5e+153], N[ArcSin[N[Sqrt[N[(N[(t$95$1 * Om + -1.0), $MachinePrecision] / N[(N[(N[(-2.0 * t$95$m), $MachinePrecision] / l$95$m), $MachinePrecision] * N[(t$95$m / l$95$m), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], N[ArcSin[N[(N[Sqrt[N[(N[(N[(l$95$m * l$95$m), $MachinePrecision] * N[(1.0 - N[(t$95$1 * Om), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (/.f64 t l) < 1.99999999999999988e-11

   1. Initial program 84.5%

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

   2. Taylor expanded in t around 0

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]
   3. Step-by-step derivation

   4. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]

   6. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc \cdot 1}}\right)} \]

   7. Taylor expanded in t around 0

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
   8. Step-by-step derivation

   9. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
   10. Step-by-step derivation

       1. lift--.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc - \frac{Om}{Omc} \cdot Om}}{Omc}}\right) \]

       2. sub-flip N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc + \left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right)}}{Omc}}\right) \]

       3. +-commutative N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right) + Omc}}{Omc}}\right) \]

       4. lift-*.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc} \cdot Om}\right)\right) + Omc}{Omc}}\right) \]

       5. distribute-lft-neg-out N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc}\right)\right) \cdot Om} + Omc}{Omc}}\right) \]

       6. lower-fma.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\frac{Om}{Omc}\right), Om, Omc\right)}}{Omc}}\right) \]

       7. lift-/.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc}}\right), Om, Omc\right)}{Omc}}\right) \]

       8. distribute-neg-frac N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\color{blue}{\frac{\mathsf{neg}\left(Om\right)}{Omc}}, Om, Omc\right)}{Omc}}\right) \]

       9. lift-neg.f64 N/A

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

       10. lower-/.f64 51.6

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

   11. Applied rewrites 51.6%

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

   if 1.99999999999999988e-11 < (/.f64 t l) < 5.00000000000000018e153

   1. Initial program 84.5%

      \[\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right) \]
   2. Step-by-step derivation

      1. lift-/.f64 N/A

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

      2. frac-2neg N/A

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

      3. lower-/.f64 N/A

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

   3. Applied rewrites 69.4%

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

   5. Applied rewrites 80.1%

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

   if 5.00000000000000018e153 < (/.f64 t l)

   1. Initial program 84.5%

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

   2. Taylor expanded in t around inf

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

      1. lower-/.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-*.f64 N/A

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

      5. lower-pow.f64 N/A

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

      6. lower--.f64 N/A

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

      7. lower-/.f64 N/A

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

      8. lower-pow.f64 N/A

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

      9. lower-pow.f64 30.7

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

   4. Applied rewrites 30.7%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{\sqrt{0.5 \cdot \left({\ell}^{2} \cdot \left(1 - \frac{{Om}^{2}}{{Omc}^{2}}\right)\right)}}{t}\right)} \]
   5. Step-by-step derivation

   6. Applied rewrites 33.0%

      \[\leadsto \color{blue}{\sin^{-1} \left(\frac{\sqrt{\left(\left(\ell \cdot \ell\right) \cdot \left(1 - \frac{Om}{Omc \cdot Omc} \cdot Om\right)\right) \cdot 0.5}}{t}\right)} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 5: 83.6% accurate, 1.0× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \begin{array}{l} \mathbf{if}\;1 + 2 \cdot {\left(\frac{t\_m}{l\_m}\right)}^{2} \leq 2:\\ \;\;\;\;\sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\frac{-Om}{Omc}, Om, Omc\right)}{Omc}}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\frac{\sqrt{0.5 \cdot {l\_m}^{2}}}{t\_m}\right)\\ \end{array} \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (if (<= (+ 1.0 (* 2.0 (pow (/ t_m l_m) 2.0))) 2.0)
   (asin (sqrt (/ (fma (/ (- Om) Omc) Om Omc) Omc)))
   (asin (/ (sqrt (* 0.5 (pow l_m 2.0))) t_m))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	double tmp;
	if ((1.0 + (2.0 * pow((t_m / l_m), 2.0))) <= 2.0) {
		tmp = asin(sqrt((fma((-Om / Omc), Om, Omc) / Omc)));
	} else {
		tmp = asin((sqrt((0.5 * pow(l_m, 2.0))) / t_m));
	}
	return tmp;
}

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	tmp = 0.0
	if (Float64(1.0 + Float64(2.0 * (Float64(t_m / l_m) ^ 2.0))) <= 2.0)
		tmp = asin(sqrt(Float64(fma(Float64(Float64(-Om) / Omc), Om, Omc) / Omc)));
	else
		tmp = asin(Float64(sqrt(Float64(0.5 * (l_m ^ 2.0))) / t_m));
	end
	return tmp
end

Wolfram

t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := If[LessEqual[N[(1.0 + N[(2.0 * N[Power[N[(t$95$m / l$95$m), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], N[ArcSin[N[Sqrt[N[(N[(N[((-Om) / Omc), $MachinePrecision] * Om + Omc), $MachinePrecision] / Omc), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], N[ArcSin[N[(N[Sqrt[N[(0.5 * N[Power[l$95$m, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$m), $MachinePrecision]], $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64)))) < 2

   1. Initial program 84.5%

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

   2. Taylor expanded in t around 0

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]
   3. Step-by-step derivation

   4. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]

   6. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc \cdot 1}}\right)} \]

   7. Taylor expanded in t around 0

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
   8. Step-by-step derivation

   9. Applied rewrites 51.6%

      \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
   10. Step-by-step derivation

       1. lift--.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc - \frac{Om}{Omc} \cdot Om}}{Omc}}\right) \]

       2. sub-flip N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc + \left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right)}}{Omc}}\right) \]

       3. +-commutative N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right) + Omc}}{Omc}}\right) \]

       4. lift-*.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc} \cdot Om}\right)\right) + Omc}{Omc}}\right) \]

       5. distribute-lft-neg-out N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc}\right)\right) \cdot Om} + Omc}{Omc}}\right) \]

       6. lower-fma.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\frac{Om}{Omc}\right), Om, Omc\right)}}{Omc}}\right) \]

       7. lift-/.f64 N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc}}\right), Om, Omc\right)}{Omc}}\right) \]

       8. distribute-neg-frac N/A

          \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\color{blue}{\frac{\mathsf{neg}\left(Om\right)}{Omc}}, Om, Omc\right)}{Omc}}\right) \]

       9. lift-neg.f64 N/A

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

       10. lower-/.f64 51.6

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

   11. Applied rewrites 51.6%

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

   if 2 < (+.f64 #s(literal 1 binary64) (*.f64 #s(literal 2 binary64) (pow.f64 (/.f64 t l) #s(literal 2 binary64))))

   1. Initial program 84.5%

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

   2. Taylor expanded in t around inf

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

      1. lower-/.f64 N/A

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

      2. lower-sqrt.f64 N/A

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

      3. lower-*.f64 N/A

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

      4. lower-*.f64 N/A

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

      5. lower-pow.f64 N/A

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

      6. lower--.f64 N/A

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

      7. lower-/.f64 N/A

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

      8. lower-pow.f64 N/A

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

      9. lower-pow.f64 30.7

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

   4. Applied rewrites 30.7%

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

   5. Taylor expanded in Om around 0

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{\frac{1}{2} \cdot {\ell}^{2}}}{t}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

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

      2. lower-pow.f64 34.5

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

   7. Applied rewrites 34.5%

      \[\leadsto \sin^{-1} \left(\frac{\sqrt{0.5 \cdot {\ell}^{2}}}{t}\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 6: 51.6% accurate, 2.6× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \sin^{-1} \left(\sqrt{\frac{\left(Omc + Om\right) \cdot \frac{Omc - Om}{Omc}}{Omc}}\right) \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (asin (sqrt (/ (* (+ Omc Om) (/ (- Omc Om) Omc)) Omc))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	return asin(sqrt((((Omc + Om) * ((Omc - Om) / Omc)) / Omc)));
}

Fortran

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(sqrt((((omc + om) * ((omc - om) / omc)) / omc)))
end function

Java

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(Math.sqrt((((Omc + Om) * ((Omc - Om) / Omc)) / Omc)));
}

Python

t_m = math.fabs(t)
l_m = math.fabs(l)
def code(t_m, l_m, Om, Omc):
	return math.asin(math.sqrt((((Omc + Om) * ((Omc - Om) / Omc)) / Omc)))

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	return asin(sqrt(Float64(Float64(Float64(Omc + Om) * Float64(Float64(Omc - Om) / Omc)) / Omc)))
end

MATLAB

t_m = abs(t);
l_m = abs(l);
function tmp = code(t_m, l_m, Om, Omc)
	tmp = asin(sqrt((((Omc + Om) * ((Omc - Om) / Omc)) / Omc)));
end

Wolfram

t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := N[ArcSin[N[Sqrt[N[(N[(N[(Omc + Om), $MachinePrecision] * N[(N[(Omc - Om), $MachinePrecision] / Omc), $MachinePrecision]), $MachinePrecision] / Omc), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]

Derivation

1. Initial program 84.5%

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

2. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]
3. Step-by-step derivation

4. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]

6. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc \cdot 1}}\right)} \]

7. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
8. Step-by-step derivation

9. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
10. Step-by-step derivation

    1. lift--.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc - \frac{Om}{Omc} \cdot Om}}{Omc}}\right) \]

    2. lift-*.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \color{blue}{\frac{Om}{Omc} \cdot Om}}{Omc}}\right) \]

    3. lift-/.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \color{blue}{\frac{Om}{Omc}} \cdot Om}{Omc}}\right) \]

    4. associate-*l/ N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \color{blue}{\frac{Om \cdot Om}{Omc}}}{Omc}}\right) \]

    5. lift-*.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{\color{blue}{Om \cdot Om}}{Omc}}{Omc}}\right) \]

    6. sub-to-fraction-rev N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\frac{Omc \cdot Omc - Om \cdot Om}{Omc}}}{Omc}}\right) \]

    7. lift-*.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{Omc \cdot Omc} - Om \cdot Om}{Omc}}{Omc}}\right) \]

    8. lift--.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{Omc \cdot Omc - Om \cdot Om}}{Omc}}{Omc}}\right) \]

    9. lift--.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{Omc \cdot Omc - Om \cdot Om}}{Omc}}{Omc}}\right) \]

    10. lift-*.f64 N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{Omc \cdot Omc} - Om \cdot Om}{Omc}}{Omc}}\right) \]

    11. lift-*.f64 N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{Omc \cdot Omc - \color{blue}{Om \cdot Om}}{Omc}}{Omc}}\right) \]

    12. difference-of-squares N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\frac{\color{blue}{\left(Omc + Om\right) \cdot \left(Omc - Om\right)}}{Omc}}{Omc}}\right) \]

    13. associate-/l* N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(Omc + Om\right) \cdot \frac{Omc - Om}{Omc}}}{Omc}}\right) \]

    14. lower-*.f64 N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(Omc + Om\right) \cdot \frac{Omc - Om}{Omc}}}{Omc}}\right) \]

    15. lower-+.f64 N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(Omc + Om\right)} \cdot \frac{Omc - Om}{Omc}}{Omc}}\right) \]

    16. lower-/.f64 N/A

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\left(Omc + Om\right) \cdot \color{blue}{\frac{Omc - Om}{Omc}}}{Omc}}\right) \]

    17. lower--.f64 51.6

        \[\leadsto \sin^{-1} \left(\sqrt{\frac{\left(Omc + Om\right) \cdot \frac{\color{blue}{Omc - Om}}{Omc}}{Omc}}\right) \]

11. Applied rewrites 51.6%

    \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(Omc + Om\right) \cdot \frac{Omc - Om}{Omc}}}{Omc}}\right) \]
12. Add Preprocessing

Alternative 7: 51.6% accurate, 2.9× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\frac{-Om}{Omc}, Om, Omc\right)}{Omc}}\right) \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (asin (sqrt (/ (fma (/ (- Om) Omc) Om Omc) Omc))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	return asin(sqrt((fma((-Om / Omc), Om, Omc) / Omc)));
}

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	return asin(sqrt(Float64(fma(Float64(Float64(-Om) / Omc), Om, Omc) / Omc)))
end

Wolfram

t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := N[ArcSin[N[Sqrt[N[(N[(N[((-Om) / Omc), $MachinePrecision] * Om + Omc), $MachinePrecision] / Omc), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]

Derivation

1. Initial program 84.5%

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

2. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]
3. Step-by-step derivation

4. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]

6. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc \cdot 1}}\right)} \]

7. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
8. Step-by-step derivation

9. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
10. Step-by-step derivation

    1. lift--.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc - \frac{Om}{Omc} \cdot Om}}{Omc}}\right) \]

    2. sub-flip N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{Omc + \left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right)}}{Omc}}\right) \]

    3. +-commutative N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc} \cdot Om\right)\right) + Omc}}{Omc}}\right) \]

    4. lift-*.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc} \cdot Om}\right)\right) + Omc}{Omc}}\right) \]

    5. distribute-lft-neg-out N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{Om}{Omc}\right)\right) \cdot Om} + Omc}{Omc}}\right) \]

    6. lower-fma.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\frac{Om}{Omc}\right), Om, Omc\right)}}{Omc}}\right) \]

    7. lift-/.f64 N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\mathsf{neg}\left(\color{blue}{\frac{Om}{Omc}}\right), Om, Omc\right)}{Omc}}\right) \]

    8. distribute-neg-frac N/A

       \[\leadsto \sin^{-1} \left(\sqrt{\frac{\mathsf{fma}\left(\color{blue}{\frac{\mathsf{neg}\left(Om\right)}{Omc}}, Om, Omc\right)}{Omc}}\right) \]

    9. lift-neg.f64 N/A

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

    10. lower-/.f64 51.6

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

11. Applied rewrites 51.6%

    \[\leadsto \sin^{-1} \left(\sqrt{\frac{\color{blue}{\mathsf{fma}\left(\frac{-Om}{Omc}, Om, Omc\right)}}{Omc}}\right) \]
12. Add Preprocessing

Alternative 8: 51.6% accurate, 2.9× speedup

Math

\[\begin{array}{l} t_m = \left|t\right| \\ l_m = \left|\ell\right| \\ \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc}}\right) \end{array} \]

FPCore

t_m = (fabs.f64 t)
l_m = (fabs.f64 l)
(FPCore (t_m l_m Om Omc)
 :precision binary64
 (asin (sqrt (/ (- Omc (* (/ Om Omc) Om)) Omc))))

C

t_m = fabs(t);
l_m = fabs(l);
double code(double t_m, double l_m, double Om, double Omc) {
	return asin(sqrt(((Omc - ((Om / Omc) * Om)) / Omc)));
}

Fortran

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(sqrt(((omc - ((om / omc) * om)) / omc)))
end function

Java

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(Math.sqrt(((Omc - ((Om / Omc) * Om)) / Omc)));
}

Python

t_m = math.fabs(t)
l_m = math.fabs(l)
def code(t_m, l_m, Om, Omc):
	return math.asin(math.sqrt(((Omc - ((Om / Omc) * Om)) / Omc)))

Julia

t_m = abs(t)
l_m = abs(l)
function code(t_m, l_m, Om, Omc)
	return asin(sqrt(Float64(Float64(Omc - Float64(Float64(Om / Omc) * Om)) / Omc)))
end

MATLAB

t_m = abs(t);
l_m = abs(l);
function tmp = code(t_m, l_m, Om, Omc)
	tmp = asin(sqrt(((Omc - ((Om / Omc) * Om)) / Omc)));
end

Wolfram

t_m = N[Abs[t], $MachinePrecision]
l_m = N[Abs[l], $MachinePrecision]
code[t$95$m_, l$95$m_, Om_, Omc_] := N[ArcSin[N[Sqrt[N[(N[(Omc - N[(N[(Om / Omc), $MachinePrecision] * Om), $MachinePrecision]), $MachinePrecision] / Omc), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]

Derivation

1. Initial program 84.5%

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

2. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]
3. Step-by-step derivation

4. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{\color{blue}{1}}}\right) \]

6. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \color{blue}{\left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{Omc \cdot 1}}\right)} \]

7. Taylor expanded in t around 0

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
8. Step-by-step derivation

9. Applied rewrites 51.6%

   \[\leadsto \sin^{-1} \left(\sqrt{\frac{Omc - \frac{Om}{Omc} \cdot Om}{\color{blue}{Omc}}}\right) \]
10. Add Preprocessing

Reproduce

herbie shell --seed 2025147 
(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)))))))