
(FPCore (k n) :precision binary64 (* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))
double code(double k, double n) {
return (1.0 / sqrt(k)) * pow(((2.0 * ((double) M_PI)) * n), ((1.0 - k) / 2.0));
}
public static double code(double k, double n) {
return (1.0 / Math.sqrt(k)) * Math.pow(((2.0 * Math.PI) * n), ((1.0 - k) / 2.0));
}
def code(k, n): return (1.0 / math.sqrt(k)) * math.pow(((2.0 * math.pi) * n), ((1.0 - k) / 2.0))
function code(k, n) return Float64(Float64(1.0 / sqrt(k)) * (Float64(Float64(2.0 * pi) * n) ^ Float64(Float64(1.0 - k) / 2.0))) end
function tmp = code(k, n) tmp = (1.0 / sqrt(k)) * (((2.0 * pi) * n) ^ ((1.0 - k) / 2.0)); end
code[k_, n_] := N[(N[(1.0 / N[Sqrt[k], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(2.0 * Pi), $MachinePrecision] * n), $MachinePrecision], N[(N[(1.0 - k), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 9 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (k n) :precision binary64 (* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))
double code(double k, double n) {
return (1.0 / sqrt(k)) * pow(((2.0 * ((double) M_PI)) * n), ((1.0 - k) / 2.0));
}
public static double code(double k, double n) {
return (1.0 / Math.sqrt(k)) * Math.pow(((2.0 * Math.PI) * n), ((1.0 - k) / 2.0));
}
def code(k, n): return (1.0 / math.sqrt(k)) * math.pow(((2.0 * math.pi) * n), ((1.0 - k) / 2.0))
function code(k, n) return Float64(Float64(1.0 / sqrt(k)) * (Float64(Float64(2.0 * pi) * n) ^ Float64(Float64(1.0 - k) / 2.0))) end
function tmp = code(k, n) tmp = (1.0 / sqrt(k)) * (((2.0 * pi) * n) ^ ((1.0 - k) / 2.0)); end
code[k_, n_] := N[(N[(1.0 / N[Sqrt[k], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(2.0 * Pi), $MachinePrecision] * n), $MachinePrecision], N[(N[(1.0 - k), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}
\end{array}
(FPCore (k n) :precision binary64 (let* ((t_0 (* PI (* 2.0 n)))) (/ (/ (sqrt t_0) (sqrt k)) (pow t_0 (* k 0.5)))))
double code(double k, double n) {
double t_0 = ((double) M_PI) * (2.0 * n);
return (sqrt(t_0) / sqrt(k)) / pow(t_0, (k * 0.5));
}
public static double code(double k, double n) {
double t_0 = Math.PI * (2.0 * n);
return (Math.sqrt(t_0) / Math.sqrt(k)) / Math.pow(t_0, (k * 0.5));
}
def code(k, n): t_0 = math.pi * (2.0 * n) return (math.sqrt(t_0) / math.sqrt(k)) / math.pow(t_0, (k * 0.5))
function code(k, n) t_0 = Float64(pi * Float64(2.0 * n)) return Float64(Float64(sqrt(t_0) / sqrt(k)) / (t_0 ^ Float64(k * 0.5))) end
function tmp = code(k, n) t_0 = pi * (2.0 * n); tmp = (sqrt(t_0) / sqrt(k)) / (t_0 ^ (k * 0.5)); end
code[k_, n_] := Block[{t$95$0 = N[(Pi * N[(2.0 * n), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision] / N[Power[t$95$0, N[(k * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \pi \cdot \left(2 \cdot n\right)\\
\frac{\frac{\sqrt{t_0}}{\sqrt{k}}}{{t_0}^{\left(k \cdot 0.5\right)}}
\end{array}
\end{array}
Initial program 99.5%
associate-/r/99.5%
clear-num99.6%
*-commutative99.6%
associate-*r*99.6%
div-sub99.6%
metadata-eval99.6%
pow-sub99.7%
pow1/299.7%
associate-/l/99.7%
associate-*r*99.7%
*-commutative99.7%
associate-*l*99.7%
Applied egg-rr99.7%
associate-/r*99.7%
associate-*r*99.7%
*-commutative99.7%
associate-*l*99.7%
associate-*r*99.7%
*-commutative99.7%
associate-*l*99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (k n) :precision binary64 (if (<= k 9e+264) (/ (sqrt (* 2.0 (* PI n))) (sqrt k)) (cbrt (pow (* (/ n k) (* PI 2.0)) 1.5))))
double code(double k, double n) {
double tmp;
if (k <= 9e+264) {
tmp = sqrt((2.0 * (((double) M_PI) * n))) / sqrt(k);
} else {
tmp = cbrt(pow(((n / k) * (((double) M_PI) * 2.0)), 1.5));
}
return tmp;
}
public static double code(double k, double n) {
double tmp;
if (k <= 9e+264) {
tmp = Math.sqrt((2.0 * (Math.PI * n))) / Math.sqrt(k);
} else {
tmp = Math.cbrt(Math.pow(((n / k) * (Math.PI * 2.0)), 1.5));
}
return tmp;
}
function code(k, n) tmp = 0.0 if (k <= 9e+264) tmp = Float64(sqrt(Float64(2.0 * Float64(pi * n))) / sqrt(k)); else tmp = cbrt((Float64(Float64(n / k) * Float64(pi * 2.0)) ^ 1.5)); end return tmp end
code[k_, n_] := If[LessEqual[k, 9e+264], N[(N[Sqrt[N[(2.0 * N[(Pi * n), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision], N[Power[N[Power[N[(N[(n / k), $MachinePrecision] * N[(Pi * 2.0), $MachinePrecision]), $MachinePrecision], 1.5], $MachinePrecision], 1/3], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;k \leq 9 \cdot 10^{+264}:\\
\;\;\;\;\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}\\
\mathbf{else}:\\
\;\;\;\;\sqrt[3]{{\left(\frac{n}{k} \cdot \left(\pi \cdot 2\right)\right)}^{1.5}}\\
\end{array}
\end{array}
if k < 9.00000000000000006e264Initial program 99.4%
Taylor expanded in k around 0 54.2%
associate-*l/54.2%
*-un-lft-identity54.2%
sqrt-unprod54.3%
*-commutative54.3%
*-commutative54.3%
Applied egg-rr54.3%
if 9.00000000000000006e264 < k Initial program 100.0%
Taylor expanded in k around 0 3.4%
associate-*l/3.4%
*-un-lft-identity3.4%
sqrt-unprod3.4%
*-commutative3.4%
*-commutative3.4%
sqrt-undiv3.3%
Applied egg-rr3.3%
div-inv3.3%
associate-*r*3.3%
*-commutative3.3%
associate-*l*3.3%
*-commutative3.3%
Applied egg-rr3.3%
add-cbrt-cube37.0%
add-sqr-sqrt37.0%
pow137.0%
pow1/237.0%
pow-prod-up37.0%
*-commutative37.0%
associate-*r*37.0%
div-inv37.0%
*-commutative37.0%
metadata-eval37.0%
Applied egg-rr37.0%
Final simplification53.1%
(FPCore (k n) :precision binary64 (/ (pow (* PI (* 2.0 n)) (- 0.5 (/ k 2.0))) (sqrt k)))
double code(double k, double n) {
return pow((((double) M_PI) * (2.0 * n)), (0.5 - (k / 2.0))) / sqrt(k);
}
public static double code(double k, double n) {
return Math.pow((Math.PI * (2.0 * n)), (0.5 - (k / 2.0))) / Math.sqrt(k);
}
def code(k, n): return math.pow((math.pi * (2.0 * n)), (0.5 - (k / 2.0))) / math.sqrt(k)
function code(k, n) return Float64((Float64(pi * Float64(2.0 * n)) ^ Float64(0.5 - Float64(k / 2.0))) / sqrt(k)) end
function tmp = code(k, n) tmp = ((pi * (2.0 * n)) ^ (0.5 - (k / 2.0))) / sqrt(k); end
code[k_, n_] := N[(N[Power[N[(Pi * N[(2.0 * n), $MachinePrecision]), $MachinePrecision], N[(0.5 - N[(k / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}
\end{array}
Initial program 99.5%
associate-*l/99.6%
*-lft-identity99.6%
sqr-pow99.4%
pow-sqr99.6%
*-commutative99.6%
associate-*l*99.6%
associate-*r/99.6%
*-commutative99.6%
associate-/l*99.6%
metadata-eval99.6%
/-rgt-identity99.6%
div-sub99.6%
metadata-eval99.6%
Simplified99.6%
Final simplification99.6%
(FPCore (k n) :precision binary64 (* (sqrt (* 2.0 (/ PI k))) (sqrt n)))
double code(double k, double n) {
return sqrt((2.0 * (((double) M_PI) / k))) * sqrt(n);
}
public static double code(double k, double n) {
return Math.sqrt((2.0 * (Math.PI / k))) * Math.sqrt(n);
}
def code(k, n): return math.sqrt((2.0 * (math.pi / k))) * math.sqrt(n)
function code(k, n) return Float64(sqrt(Float64(2.0 * Float64(pi / k))) * sqrt(n)) end
function tmp = code(k, n) tmp = sqrt((2.0 * (pi / k))) * sqrt(n); end
code[k_, n_] := N[(N[Sqrt[N[(2.0 * N[(Pi / k), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[n], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{2 \cdot \frac{\pi}{k}} \cdot \sqrt{n}
\end{array}
Initial program 99.5%
Taylor expanded in k around 0 50.8%
associate-*l/50.8%
*-un-lft-identity50.8%
sqrt-unprod50.9%
*-commutative50.9%
*-commutative50.9%
sqrt-undiv40.3%
Applied egg-rr40.3%
div-inv40.3%
associate-*r*40.3%
*-commutative40.3%
associate-*l*40.3%
*-commutative40.3%
Applied egg-rr40.3%
*-commutative40.3%
sqrt-prod50.9%
un-div-inv50.9%
*-commutative50.9%
*-un-lft-identity50.9%
times-frac50.9%
metadata-eval50.9%
Applied egg-rr50.9%
Final simplification50.9%
(FPCore (k n) :precision binary64 (/ (sqrt (* 2.0 (* PI n))) (sqrt k)))
double code(double k, double n) {
return sqrt((2.0 * (((double) M_PI) * n))) / sqrt(k);
}
public static double code(double k, double n) {
return Math.sqrt((2.0 * (Math.PI * n))) / Math.sqrt(k);
}
def code(k, n): return math.sqrt((2.0 * (math.pi * n))) / math.sqrt(k)
function code(k, n) return Float64(sqrt(Float64(2.0 * Float64(pi * n))) / sqrt(k)) end
function tmp = code(k, n) tmp = sqrt((2.0 * (pi * n))) / sqrt(k); end
code[k_, n_] := N[(N[Sqrt[N[(2.0 * N[(Pi * n), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}
\end{array}
Initial program 99.5%
Taylor expanded in k around 0 50.8%
associate-*l/50.8%
*-un-lft-identity50.8%
sqrt-unprod50.9%
*-commutative50.9%
*-commutative50.9%
Applied egg-rr50.9%
Final simplification50.9%
(FPCore (k n) :precision binary64 (/ 1.0 (sqrt (* (/ 0.5 PI) (/ k n)))))
double code(double k, double n) {
return 1.0 / sqrt(((0.5 / ((double) M_PI)) * (k / n)));
}
public static double code(double k, double n) {
return 1.0 / Math.sqrt(((0.5 / Math.PI) * (k / n)));
}
def code(k, n): return 1.0 / math.sqrt(((0.5 / math.pi) * (k / n)))
function code(k, n) return Float64(1.0 / sqrt(Float64(Float64(0.5 / pi) * Float64(k / n)))) end
function tmp = code(k, n) tmp = 1.0 / sqrt(((0.5 / pi) * (k / n))); end
code[k_, n_] := N[(1.0 / N[Sqrt[N[(N[(0.5 / Pi), $MachinePrecision] * N[(k / n), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{\frac{0.5}{\pi} \cdot \frac{k}{n}}}
\end{array}
Initial program 99.5%
Applied egg-rr99.3%
Taylor expanded in k around 0 40.2%
associate-*r/40.2%
*-commutative40.2%
associate-*r*40.2%
*-commutative40.2%
associate-*l*40.2%
associate-/l*40.2%
Simplified40.2%
pow-pow40.3%
metadata-eval40.3%
pow1/240.3%
clear-num40.3%
sqrt-div41.4%
metadata-eval41.4%
*-un-lft-identity41.4%
times-frac41.4%
metadata-eval41.4%
Applied egg-rr41.4%
associate-/l*40.3%
associate-/r/41.3%
Simplified41.3%
Final simplification41.3%
(FPCore (k n) :precision binary64 (/ 1.0 (sqrt (/ k (* n (/ PI 0.5))))))
double code(double k, double n) {
return 1.0 / sqrt((k / (n * (((double) M_PI) / 0.5))));
}
public static double code(double k, double n) {
return 1.0 / Math.sqrt((k / (n * (Math.PI / 0.5))));
}
def code(k, n): return 1.0 / math.sqrt((k / (n * (math.pi / 0.5))))
function code(k, n) return Float64(1.0 / sqrt(Float64(k / Float64(n * Float64(pi / 0.5))))) end
function tmp = code(k, n) tmp = 1.0 / sqrt((k / (n * (pi / 0.5)))); end
code[k_, n_] := N[(1.0 / N[Sqrt[N[(k / N[(n * N[(Pi / 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{\frac{k}{n \cdot \frac{\pi}{0.5}}}}
\end{array}
Initial program 99.5%
Taylor expanded in k around 0 50.8%
associate-*l/50.8%
*-un-lft-identity50.8%
sqrt-unprod50.9%
*-commutative50.9%
*-commutative50.9%
sqrt-undiv40.3%
Applied egg-rr40.3%
div-inv40.3%
associate-*r*40.3%
*-commutative40.3%
associate-*l*40.3%
*-commutative40.3%
Applied egg-rr40.3%
associate-*r*40.3%
sqrt-prod50.8%
associate-*r*50.8%
*-commutative50.8%
*-commutative50.8%
sqrt-div50.8%
metadata-eval50.8%
div-inv50.9%
clear-num50.8%
sqrt-undiv41.4%
*-commutative41.4%
*-commutative41.4%
associate-*r*41.4%
*-commutative41.4%
Applied egg-rr41.4%
*-commutative41.4%
*-commutative41.4%
associate-*r*41.4%
/-rgt-identity41.4%
associate-/r/41.3%
associate-/r*41.3%
metadata-eval41.3%
associate-/r/41.4%
Simplified41.4%
Final simplification41.4%
(FPCore (k n) :precision binary64 (sqrt (* 2.0 (* PI (/ n k)))))
double code(double k, double n) {
return sqrt((2.0 * (((double) M_PI) * (n / k))));
}
public static double code(double k, double n) {
return Math.sqrt((2.0 * (Math.PI * (n / k))));
}
def code(k, n): return math.sqrt((2.0 * (math.pi * (n / k))))
function code(k, n) return sqrt(Float64(2.0 * Float64(pi * Float64(n / k)))) end
function tmp = code(k, n) tmp = sqrt((2.0 * (pi * (n / k)))); end
code[k_, n_] := N[Sqrt[N[(2.0 * N[(Pi * N[(n / k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{2 \cdot \left(\pi \cdot \frac{n}{k}\right)}
\end{array}
Initial program 99.5%
Taylor expanded in k around 0 50.8%
associate-*l/50.8%
*-un-lft-identity50.8%
sqrt-unprod50.9%
*-commutative50.9%
*-commutative50.9%
sqrt-undiv40.3%
Applied egg-rr40.3%
Taylor expanded in n around 0 40.3%
associate-/l*40.3%
Simplified40.3%
associate-/r/40.3%
Applied egg-rr40.3%
Final simplification40.3%
(FPCore (k n) :precision binary64 (sqrt (/ (* 2.0 (* PI n)) k)))
double code(double k, double n) {
return sqrt(((2.0 * (((double) M_PI) * n)) / k));
}
public static double code(double k, double n) {
return Math.sqrt(((2.0 * (Math.PI * n)) / k));
}
def code(k, n): return math.sqrt(((2.0 * (math.pi * n)) / k))
function code(k, n) return sqrt(Float64(Float64(2.0 * Float64(pi * n)) / k)) end
function tmp = code(k, n) tmp = sqrt(((2.0 * (pi * n)) / k)); end
code[k_, n_] := N[Sqrt[N[(N[(2.0 * N[(Pi * n), $MachinePrecision]), $MachinePrecision] / k), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}
\end{array}
Initial program 99.5%
Taylor expanded in k around 0 50.8%
associate-*l/50.8%
*-un-lft-identity50.8%
sqrt-unprod50.9%
*-commutative50.9%
*-commutative50.9%
sqrt-undiv40.3%
Applied egg-rr40.3%
Final simplification40.3%
herbie shell --seed 2024011
(FPCore (k n)
:name "Migdal et al, Equation (51)"
:precision binary64
(* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))