| Alternative 1 | |
|---|---|
| Accuracy | 98.4% |
| Cost | 32832 |
\[\sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \frac{t}{\ell} \cdot \sqrt{2}\right)}\right)
\]

(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)))))))
(FPCore (t l Om Omc) :precision binary64 (asin (/ (sqrt (- 1.0 (pow (/ Om Omc) 2.0))) (hypot 1.0 (* (/ t l) (sqrt 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))))));
}
double code(double t, double l, double Om, double Omc) {
return asin((sqrt((1.0 - pow((Om / Omc), 2.0))) / hypot(1.0, ((t / l) * sqrt(2.0)))));
}
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))))));
}
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))) / Math.hypot(1.0, ((t / l) * Math.sqrt(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))))))
def code(t, l, Om, Omc): return math.asin((math.sqrt((1.0 - math.pow((Om / Omc), 2.0))) / math.hypot(1.0, ((t / l) * math.sqrt(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 code(t, l, Om, Omc) return asin(Float64(sqrt(Float64(1.0 - (Float64(Om / Omc) ^ 2.0))) / hypot(1.0, Float64(Float64(t / l) * sqrt(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
function tmp = code(t, l, Om, Omc) tmp = asin((sqrt((1.0 - ((Om / Omc) ^ 2.0))) / hypot(1.0, ((t / l) * sqrt(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]
code[t_, l_, Om_, Omc_] := N[ArcSin[N[(N[Sqrt[N[(1.0 - N[Power[N[(Om / Omc), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[1.0 ^ 2 + N[(N[(t / l), $MachinePrecision] * N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right)
\sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \frac{t}{\ell} \cdot \sqrt{2}\right)}\right)
Herbie found 14 alternatives:
| Alternative | Accuracy | Speedup |
|---|
Results
Initial program 81.4%
Applied egg-rr98.7%
[Start]81.4% | \[ \sin^{-1} \left(\sqrt{\frac{1 - {\left(\frac{Om}{Omc}\right)}^{2}}{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right)
\] |
|---|---|
sqrt-div [=>]81.4% | \[ \sin^{-1} \color{blue}{\left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\sqrt{1 + 2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}\right)}
\] |
add-sqr-sqrt [=>]81.4% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\sqrt{1 + \color{blue}{\sqrt{2 \cdot {\left(\frac{t}{\ell}\right)}^{2}} \cdot \sqrt{2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}}}}\right)
\] |
hypot-1-def [=>]81.4% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\color{blue}{\mathsf{hypot}\left(1, \sqrt{2 \cdot {\left(\frac{t}{\ell}\right)}^{2}}\right)}}\right)
\] |
*-commutative [=>]81.4% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \sqrt{\color{blue}{{\left(\frac{t}{\ell}\right)}^{2} \cdot 2}}\right)}\right)
\] |
sqrt-prod [=>]81.4% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \color{blue}{\sqrt{{\left(\frac{t}{\ell}\right)}^{2}} \cdot \sqrt{2}}\right)}\right)
\] |
unpow2 [=>]81.4% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \sqrt{\color{blue}{\frac{t}{\ell} \cdot \frac{t}{\ell}}} \cdot \sqrt{2}\right)}\right)
\] |
sqrt-prod [=>]50.3% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \color{blue}{\left(\sqrt{\frac{t}{\ell}} \cdot \sqrt{\frac{t}{\ell}}\right)} \cdot \sqrt{2}\right)}\right)
\] |
add-sqr-sqrt [<=]98.7% | \[ \sin^{-1} \left(\frac{\sqrt{1 - {\left(\frac{Om}{Omc}\right)}^{2}}}{\mathsf{hypot}\left(1, \color{blue}{\frac{t}{\ell}} \cdot \sqrt{2}\right)}\right)
\] |
Final simplification98.7%
| Alternative 1 | |
|---|---|
| Accuracy | 98.4% |
| Cost | 32832 |
| Alternative 2 | |
|---|---|
| Accuracy | 97.4% |
| Cost | 19712 |
| Alternative 3 | |
|---|---|
| Accuracy | 97.5% |
| Cost | 19712 |
| Alternative 4 | |
|---|---|
| Accuracy | 97.2% |
| Cost | 14408 |
| Alternative 5 | |
|---|---|
| Accuracy | 97.2% |
| Cost | 14408 |
| Alternative 6 | |
|---|---|
| Accuracy | 97.1% |
| Cost | 13896 |
| Alternative 7 | |
|---|---|
| Accuracy | 78.8% |
| Cost | 13640 |
| Alternative 8 | |
|---|---|
| Accuracy | 78.8% |
| Cost | 13640 |
| Alternative 9 | |
|---|---|
| Accuracy | 96.8% |
| Cost | 13640 |
| Alternative 10 | |
|---|---|
| Accuracy | 96.8% |
| Cost | 13640 |
| Alternative 11 | |
|---|---|
| Accuracy | 63.0% |
| Cost | 13385 |
| Alternative 12 | |
|---|---|
| Accuracy | 63.0% |
| Cost | 13385 |
| Alternative 13 | |
|---|---|
| Accuracy | 49.8% |
| Cost | 7104 |
| Alternative 14 | |
|---|---|
| Accuracy | 49.5% |
| Cost | 6464 |
herbie shell --seed 2023271
(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)))))))