Migdal et al, Equation (51)

Percentage Accurate: 99.5% → 99.4%
Time: 21.6s
Alternatives: 8
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ \frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \end{array} \]
(FPCore (k n)
 :precision binary64
 (* (/ 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:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 8 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 99.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \end{array} \]
(FPCore (k n)
 :precision binary64
 (* (/ 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}

Alternative 1: 99.4% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(n \cdot 2\right)\\ \frac{\sqrt{\frac{t_0}{{t_0}^{k}}}}{\sqrt{k}} \end{array} \end{array} \]
(FPCore (k n)
 :precision binary64
 (let* ((t_0 (* PI (* n 2.0)))) (/ (sqrt (/ t_0 (pow t_0 k))) (sqrt k))))
double code(double k, double n) {
	double t_0 = ((double) M_PI) * (n * 2.0);
	return sqrt((t_0 / pow(t_0, k))) / sqrt(k);
}
public static double code(double k, double n) {
	double t_0 = Math.PI * (n * 2.0);
	return Math.sqrt((t_0 / Math.pow(t_0, k))) / Math.sqrt(k);
}
def code(k, n):
	t_0 = math.pi * (n * 2.0)
	return math.sqrt((t_0 / math.pow(t_0, k))) / math.sqrt(k)
function code(k, n)
	t_0 = Float64(pi * Float64(n * 2.0))
	return Float64(sqrt(Float64(t_0 / (t_0 ^ k))) / sqrt(k))
end
function tmp = code(k, n)
	t_0 = pi * (n * 2.0);
	tmp = sqrt((t_0 / (t_0 ^ k))) / sqrt(k);
end
code[k_, n_] := Block[{t$95$0 = N[(Pi * N[(n * 2.0), $MachinePrecision]), $MachinePrecision]}, N[(N[Sqrt[N[(t$95$0 / N[Power[t$95$0, k], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \pi \cdot \left(n \cdot 2\right)\\
\frac{\sqrt{\frac{t_0}{{t_0}^{k}}}}{\sqrt{k}}
\end{array}
\end{array}
Derivation
  1. Initial program 99.4%

    \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
  2. Step-by-step derivation
    1. *-commutative99.4%

      \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
    2. div-sub99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
    3. metadata-eval99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
    4. div-inv99.5%

      \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
    5. expm1-log1p-u96.2%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
    6. expm1-udef85.6%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
  3. Applied egg-rr74.6%

    \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
  4. Step-by-step derivation
    1. expm1-def85.3%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
    2. expm1-log1p87.2%

      \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
    3. *-commutative87.2%

      \[\leadsto \sqrt{\frac{{\left(2 \cdot \color{blue}{\left(n \cdot \pi\right)}\right)}^{\left(1 - k\right)}}{k}} \]
    4. associate-*r*87.2%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot n\right) \cdot \pi\right)}}^{\left(1 - k\right)}}{k}} \]
  5. Simplified87.2%

    \[\leadsto \color{blue}{\sqrt{\frac{{\left(\left(2 \cdot n\right) \cdot \pi\right)}^{\left(1 - k\right)}}{k}}} \]
  6. Step-by-step derivation
    1. sqrt-div99.5%

      \[\leadsto \color{blue}{\frac{\sqrt{{\left(\left(2 \cdot n\right) \cdot \pi\right)}^{\left(1 - k\right)}}}{\sqrt{k}}} \]
    2. associate-*r*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(2 \cdot \left(n \cdot \pi\right)\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    3. sqrt-pow199.5%

      \[\leadsto \frac{\color{blue}{{\left(2 \cdot \left(n \cdot \pi\right)\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    4. *-commutative99.5%

      \[\leadsto \frac{{\left(2 \cdot \color{blue}{\left(\pi \cdot n\right)}\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}} \]
    5. sqrt-pow199.5%

      \[\leadsto \frac{\color{blue}{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}} \]
    6. add-sqr-sqrt99.2%

      \[\leadsto \frac{\color{blue}{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}} \cdot \sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}}{\sqrt{k}} \]
    7. *-un-lft-identity99.2%

      \[\leadsto \frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}} \cdot \sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\color{blue}{1 \cdot \sqrt{k}}} \]
    8. times-frac99.3%

      \[\leadsto \color{blue}{\frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{1} \cdot \frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}}} \]
  7. Applied egg-rr99.3%

    \[\leadsto \color{blue}{\frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{1} \cdot \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}}} \]
  8. Step-by-step derivation
    1. /-rgt-identity99.3%

      \[\leadsto \color{blue}{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}} \cdot \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}} \]
    2. associate-*r/99.3%

      \[\leadsto \color{blue}{\frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25} \cdot {\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}}} \]
    3. pow-sqr99.5%

      \[\leadsto \frac{\color{blue}{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{\left(2 \cdot 0.25\right)}}}{\sqrt{k}} \]
    4. metadata-eval99.5%

      \[\leadsto \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{\color{blue}{0.5}}}{\sqrt{k}} \]
    5. unpow1/299.5%

      \[\leadsto \frac{\color{blue}{\sqrt{{\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}} \]
    6. associate-*r*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(\left(n \cdot \pi\right) \cdot 2\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    7. *-commutative99.5%

      \[\leadsto \frac{\sqrt{{\left(\color{blue}{\left(\pi \cdot n\right)} \cdot 2\right)}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    8. associate-*l*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(\pi \cdot \left(n \cdot 2\right)\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
  9. Simplified99.5%

    \[\leadsto \color{blue}{\frac{\sqrt{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}}{\sqrt{k}}} \]
  10. Step-by-step derivation
    1. pow-sub99.7%

      \[\leadsto \frac{\sqrt{\color{blue}{\frac{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{1}}{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{k}}}}}{\sqrt{k}} \]
    2. pow199.7%

      \[\leadsto \frac{\sqrt{\frac{\color{blue}{\pi \cdot \left(n \cdot 2\right)}}{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{k}}}}{\sqrt{k}} \]
  11. Applied egg-rr99.7%

    \[\leadsto \frac{\sqrt{\color{blue}{\frac{\pi \cdot \left(n \cdot 2\right)}{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{k}}}}}{\sqrt{k}} \]
  12. Final simplification99.7%

    \[\leadsto \frac{\sqrt{\frac{\pi \cdot \left(n \cdot 2\right)}{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{k}}}}{\sqrt{k}} \]

Alternative 2: 99.4% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \frac{\sqrt{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}}{\sqrt{k}} \end{array} \]
(FPCore (k n)
 :precision binary64
 (/ (sqrt (pow (* PI (* n 2.0)) (- 1.0 k))) (sqrt k)))
double code(double k, double n) {
	return sqrt(pow((((double) M_PI) * (n * 2.0)), (1.0 - k))) / sqrt(k);
}
public static double code(double k, double n) {
	return Math.sqrt(Math.pow((Math.PI * (n * 2.0)), (1.0 - k))) / Math.sqrt(k);
}
def code(k, n):
	return math.sqrt(math.pow((math.pi * (n * 2.0)), (1.0 - k))) / math.sqrt(k)
function code(k, n)
	return Float64(sqrt((Float64(pi * Float64(n * 2.0)) ^ Float64(1.0 - k))) / sqrt(k))
end
function tmp = code(k, n)
	tmp = sqrt(((pi * (n * 2.0)) ^ (1.0 - k))) / sqrt(k);
end
code[k_, n_] := N[(N[Sqrt[N[Power[N[(Pi * N[(n * 2.0), $MachinePrecision]), $MachinePrecision], N[(1.0 - k), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\sqrt{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}}{\sqrt{k}}
\end{array}
Derivation
  1. Initial program 99.4%

    \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
  2. Step-by-step derivation
    1. *-commutative99.4%

      \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
    2. div-sub99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
    3. metadata-eval99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
    4. div-inv99.5%

      \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
    5. expm1-log1p-u96.2%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
    6. expm1-udef85.6%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
  3. Applied egg-rr74.6%

    \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
  4. Step-by-step derivation
    1. expm1-def85.3%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
    2. expm1-log1p87.2%

      \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
    3. *-commutative87.2%

      \[\leadsto \sqrt{\frac{{\left(2 \cdot \color{blue}{\left(n \cdot \pi\right)}\right)}^{\left(1 - k\right)}}{k}} \]
    4. associate-*r*87.2%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot n\right) \cdot \pi\right)}}^{\left(1 - k\right)}}{k}} \]
  5. Simplified87.2%

    \[\leadsto \color{blue}{\sqrt{\frac{{\left(\left(2 \cdot n\right) \cdot \pi\right)}^{\left(1 - k\right)}}{k}}} \]
  6. Step-by-step derivation
    1. sqrt-div99.5%

      \[\leadsto \color{blue}{\frac{\sqrt{{\left(\left(2 \cdot n\right) \cdot \pi\right)}^{\left(1 - k\right)}}}{\sqrt{k}}} \]
    2. associate-*r*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(2 \cdot \left(n \cdot \pi\right)\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    3. sqrt-pow199.5%

      \[\leadsto \frac{\color{blue}{{\left(2 \cdot \left(n \cdot \pi\right)\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    4. *-commutative99.5%

      \[\leadsto \frac{{\left(2 \cdot \color{blue}{\left(\pi \cdot n\right)}\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}} \]
    5. sqrt-pow199.5%

      \[\leadsto \frac{\color{blue}{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}} \]
    6. add-sqr-sqrt99.2%

      \[\leadsto \frac{\color{blue}{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}} \cdot \sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}}{\sqrt{k}} \]
    7. *-un-lft-identity99.2%

      \[\leadsto \frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}} \cdot \sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\color{blue}{1 \cdot \sqrt{k}}} \]
    8. times-frac99.3%

      \[\leadsto \color{blue}{\frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{1} \cdot \frac{\sqrt{\sqrt{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}}} \]
  7. Applied egg-rr99.3%

    \[\leadsto \color{blue}{\frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{1} \cdot \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}}} \]
  8. Step-by-step derivation
    1. /-rgt-identity99.3%

      \[\leadsto \color{blue}{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}} \cdot \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}} \]
    2. associate-*r/99.3%

      \[\leadsto \color{blue}{\frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25} \cdot {\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{0.25}}{\sqrt{k}}} \]
    3. pow-sqr99.5%

      \[\leadsto \frac{\color{blue}{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{\left(2 \cdot 0.25\right)}}}{\sqrt{k}} \]
    4. metadata-eval99.5%

      \[\leadsto \frac{{\left({\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}\right)}^{\color{blue}{0.5}}}{\sqrt{k}} \]
    5. unpow1/299.5%

      \[\leadsto \frac{\color{blue}{\sqrt{{\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 - k\right)}}}}{\sqrt{k}} \]
    6. associate-*r*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(\left(n \cdot \pi\right) \cdot 2\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    7. *-commutative99.5%

      \[\leadsto \frac{\sqrt{{\left(\color{blue}{\left(\pi \cdot n\right)} \cdot 2\right)}^{\left(1 - k\right)}}}{\sqrt{k}} \]
    8. associate-*l*99.5%

      \[\leadsto \frac{\sqrt{{\color{blue}{\left(\pi \cdot \left(n \cdot 2\right)\right)}}^{\left(1 - k\right)}}}{\sqrt{k}} \]
  9. Simplified99.5%

    \[\leadsto \color{blue}{\frac{\sqrt{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}}{\sqrt{k}}} \]
  10. Final simplification99.5%

    \[\leadsto \frac{\sqrt{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}}{\sqrt{k}} \]

Alternative 3: 99.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(n \cdot 2\right)\\ \mathbf{if}\;k \leq 1.3 \cdot 10^{-47}:\\ \;\;\;\;\frac{\sqrt{t_0}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{t_0}^{\left(1 - k\right)}}{k}}\\ \end{array} \end{array} \]
(FPCore (k n)
 :precision binary64
 (let* ((t_0 (* PI (* n 2.0))))
   (if (<= k 1.3e-47)
     (/ (sqrt t_0) (sqrt k))
     (sqrt (/ (pow t_0 (- 1.0 k)) k)))))
double code(double k, double n) {
	double t_0 = ((double) M_PI) * (n * 2.0);
	double tmp;
	if (k <= 1.3e-47) {
		tmp = sqrt(t_0) / sqrt(k);
	} else {
		tmp = sqrt((pow(t_0, (1.0 - k)) / k));
	}
	return tmp;
}
public static double code(double k, double n) {
	double t_0 = Math.PI * (n * 2.0);
	double tmp;
	if (k <= 1.3e-47) {
		tmp = Math.sqrt(t_0) / Math.sqrt(k);
	} else {
		tmp = Math.sqrt((Math.pow(t_0, (1.0 - k)) / k));
	}
	return tmp;
}
def code(k, n):
	t_0 = math.pi * (n * 2.0)
	tmp = 0
	if k <= 1.3e-47:
		tmp = math.sqrt(t_0) / math.sqrt(k)
	else:
		tmp = math.sqrt((math.pow(t_0, (1.0 - k)) / k))
	return tmp
function code(k, n)
	t_0 = Float64(pi * Float64(n * 2.0))
	tmp = 0.0
	if (k <= 1.3e-47)
		tmp = Float64(sqrt(t_0) / sqrt(k));
	else
		tmp = sqrt(Float64((t_0 ^ Float64(1.0 - k)) / k));
	end
	return tmp
end
function tmp_2 = code(k, n)
	t_0 = pi * (n * 2.0);
	tmp = 0.0;
	if (k <= 1.3e-47)
		tmp = sqrt(t_0) / sqrt(k);
	else
		tmp = sqrt(((t_0 ^ (1.0 - k)) / k));
	end
	tmp_2 = tmp;
end
code[k_, n_] := Block[{t$95$0 = N[(Pi * N[(n * 2.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, 1.3e-47], N[(N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision], N[Sqrt[N[(N[Power[t$95$0, N[(1.0 - k), $MachinePrecision]], $MachinePrecision] / k), $MachinePrecision]], $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \pi \cdot \left(n \cdot 2\right)\\
\mathbf{if}\;k \leq 1.3 \cdot 10^{-47}:\\
\;\;\;\;\frac{\sqrt{t_0}}{\sqrt{k}}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\frac{{t_0}^{\left(1 - k\right)}}{k}}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if k < 1.3e-47

    1. Initial program 99.2%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Taylor expanded in k around 0 99.1%

      \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)} \]
    3. Step-by-step derivation
      1. expm1-log1p-u93.1%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{1}{\sqrt{k}} \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)\right)\right)} \]
      2. expm1-udef76.6%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{1}{\sqrt{k}} \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)\right)} - 1} \]
      3. associate-*l/76.6%

        \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\frac{1 \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)}{\sqrt{k}}}\right)} - 1 \]
      4. *-un-lft-identity76.6%

        \[\leadsto e^{\mathsf{log1p}\left(\frac{\color{blue}{\sqrt{2} \cdot \sqrt{n \cdot \pi}}}{\sqrt{k}}\right)} - 1 \]
      5. sqrt-unprod76.6%

        \[\leadsto e^{\mathsf{log1p}\left(\frac{\color{blue}{\sqrt{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}}\right)} - 1 \]
    4. Applied egg-rr76.6%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}\right)} - 1} \]
    5. Step-by-step derivation
      1. expm1-def93.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}\right)\right)} \]
      2. expm1-log1p99.4%

        \[\leadsto \color{blue}{\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}} \]
      3. associate-*r*99.4%

        \[\leadsto \frac{\sqrt{\color{blue}{\left(2 \cdot n\right) \cdot \pi}}}{\sqrt{k}} \]
    6. Simplified99.4%

      \[\leadsto \color{blue}{\frac{\sqrt{\left(2 \cdot n\right) \cdot \pi}}{\sqrt{k}}} \]

    if 1.3e-47 < k

    1. Initial program 99.5%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Step-by-step derivation
      1. *-commutative99.5%

        \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
      2. div-sub99.5%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
      3. metadata-eval99.5%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
      4. div-inv99.6%

        \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
      5. expm1-log1p-u99.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
      6. expm1-udef94.3%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
    3. Applied egg-rr94.3%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
    4. Step-by-step derivation
      1. expm1-def99.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
      2. expm1-log1p99.6%

        \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
      3. *-commutative99.6%

        \[\leadsto \sqrt{\frac{{\left(2 \cdot \color{blue}{\left(n \cdot \pi\right)}\right)}^{\left(1 - k\right)}}{k}} \]
      4. associate-*r*99.6%

        \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot n\right) \cdot \pi\right)}}^{\left(1 - k\right)}}{k}} \]
    5. Simplified99.6%

      \[\leadsto \color{blue}{\sqrt{\frac{{\left(\left(2 \cdot n\right) \cdot \pi\right)}^{\left(1 - k\right)}}{k}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq 1.3 \cdot 10^{-47}:\\ \;\;\;\;\frac{\sqrt{\pi \cdot \left(n \cdot 2\right)}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{\left(\pi \cdot \left(n \cdot 2\right)\right)}^{\left(1 - k\right)}}{k}}\\ \end{array} \]

Alternative 4: 99.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{{\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \end{array} \]
(FPCore (k n)
 :precision binary64
 (/ (pow (* n (* PI 2.0)) (- 0.5 (/ k 2.0))) (sqrt k)))
double code(double k, double n) {
	return pow((n * (((double) M_PI) * 2.0)), (0.5 - (k / 2.0))) / sqrt(k);
}
public static double code(double k, double n) {
	return Math.pow((n * (Math.PI * 2.0)), (0.5 - (k / 2.0))) / Math.sqrt(k);
}
def code(k, n):
	return math.pow((n * (math.pi * 2.0)), (0.5 - (k / 2.0))) / math.sqrt(k)
function code(k, n)
	return Float64((Float64(n * Float64(pi * 2.0)) ^ Float64(0.5 - Float64(k / 2.0))) / sqrt(k))
end
function tmp = code(k, n)
	tmp = ((n * (pi * 2.0)) ^ (0.5 - (k / 2.0))) / sqrt(k);
end
code[k_, n_] := N[(N[Power[N[(n * N[(Pi * 2.0), $MachinePrecision]), $MachinePrecision], N[(0.5 - N[(k / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{{\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}
\end{array}
Derivation
  1. Initial program 99.4%

    \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
  2. Step-by-step derivation
    1. associate-*l/99.5%

      \[\leadsto \color{blue}{\frac{1 \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}} \]
    2. *-lft-identity99.5%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    3. sqr-pow99.3%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)}}}{\sqrt{k}} \]
    4. pow-sqr99.5%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(2 \cdot \frac{\frac{1 - k}{2}}{2}\right)}}}{\sqrt{k}} \]
    5. *-commutative99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{2} \cdot 2\right)}}}{\sqrt{k}} \]
    6. associate-*l/99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2} \cdot 2}{2}\right)}}}{\sqrt{k}} \]
    7. associate-/l*99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{\frac{2}{2}}\right)}}}{\sqrt{k}} \]
    8. metadata-eval99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{\color{blue}{1}}\right)}}{\sqrt{k}} \]
    9. /-rgt-identity99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    10. div-sub99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}}}{\sqrt{k}} \]
    11. metadata-eval99.5%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
  3. Simplified99.5%

    \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
  4. Final simplification99.5%

    \[\leadsto \frac{{\left(n \cdot \left(\pi \cdot 2\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]

Alternative 5: 50.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{\pi}{k}} \cdot \sqrt{n \cdot 2} \end{array} \]
(FPCore (k n) :precision binary64 (* (sqrt (/ PI k)) (sqrt (* n 2.0))))
double code(double k, double n) {
	return sqrt((((double) M_PI) / k)) * sqrt((n * 2.0));
}
public static double code(double k, double n) {
	return Math.sqrt((Math.PI / k)) * Math.sqrt((n * 2.0));
}
def code(k, n):
	return math.sqrt((math.pi / k)) * math.sqrt((n * 2.0))
function code(k, n)
	return Float64(sqrt(Float64(pi / k)) * sqrt(Float64(n * 2.0)))
end
function tmp = code(k, n)
	tmp = sqrt((pi / k)) * sqrt((n * 2.0));
end
code[k_, n_] := N[(N[Sqrt[N[(Pi / k), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(n * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt{\frac{\pi}{k}} \cdot \sqrt{n \cdot 2}
\end{array}
Derivation
  1. Initial program 99.4%

    \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
  2. Step-by-step derivation
    1. *-commutative99.4%

      \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
    2. div-sub99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
    3. metadata-eval99.4%

      \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
    4. div-inv99.5%

      \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
    5. add-cube-cbrt98.7%

      \[\leadsto \color{blue}{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right) \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}} \]
    6. pow398.7%

      \[\leadsto \color{blue}{{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right)}^{3}} \]
  3. Applied egg-rr86.5%

    \[\leadsto \color{blue}{{\left(\sqrt[3]{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}}\right)}^{3}} \]
  4. Taylor expanded in k around 0 49.9%

    \[\leadsto \color{blue}{{\left(e^{0.16666666666666666 \cdot \left(-1 \cdot \log k + \log \left(2 \cdot \left(n \cdot \pi\right)\right)\right)}\right)}^{3}} \]
  5. Step-by-step derivation
    1. Simplified39.5%

      \[\leadsto \color{blue}{{\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}} \]
    2. Step-by-step derivation
      1. pow-pow42.6%

        \[\leadsto \color{blue}{{\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{\left(0.16666666666666666 \cdot 3\right)}} \]
      2. metadata-eval42.6%

        \[\leadsto {\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{\color{blue}{0.5}} \]
      3. pow-to-exp40.0%

        \[\leadsto \color{blue}{e^{\log \left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right) \cdot 0.5}} \]
      4. associate-/l*40.0%

        \[\leadsto e^{\log \color{blue}{\left(\frac{\pi}{\frac{k}{n \cdot 2}}\right)} \cdot 0.5} \]
      5. *-commutative40.0%

        \[\leadsto e^{\log \left(\frac{\pi}{\frac{k}{\color{blue}{2 \cdot n}}}\right) \cdot 0.5} \]
    3. Applied egg-rr40.0%

      \[\leadsto \color{blue}{e^{\log \left(\frac{\pi}{\frac{k}{2 \cdot n}}\right) \cdot 0.5}} \]
    4. Step-by-step derivation
      1. exp-to-pow42.6%

        \[\leadsto \color{blue}{{\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}} \]
      2. associate-/r/42.6%

        \[\leadsto {\color{blue}{\left(\frac{\pi}{k} \cdot \left(2 \cdot n\right)\right)}}^{0.5} \]
      3. unpow-prod-down54.9%

        \[\leadsto \color{blue}{{\left(\frac{\pi}{k}\right)}^{0.5} \cdot {\left(2 \cdot n\right)}^{0.5}} \]
      4. pow1/254.9%

        \[\leadsto {\left(\frac{\pi}{k}\right)}^{0.5} \cdot \color{blue}{\sqrt{2 \cdot n}} \]
      5. *-commutative54.9%

        \[\leadsto {\left(\frac{\pi}{k}\right)}^{0.5} \cdot \sqrt{\color{blue}{n \cdot 2}} \]
    5. Applied egg-rr54.9%

      \[\leadsto \color{blue}{{\left(\frac{\pi}{k}\right)}^{0.5} \cdot \sqrt{n \cdot 2}} \]
    6. Step-by-step derivation
      1. unpow1/254.9%

        \[\leadsto \color{blue}{\sqrt{\frac{\pi}{k}}} \cdot \sqrt{n \cdot 2} \]
    7. Simplified54.9%

      \[\leadsto \color{blue}{\sqrt{\frac{\pi}{k}} \cdot \sqrt{n \cdot 2}} \]
    8. Final simplification54.9%

      \[\leadsto \sqrt{\frac{\pi}{k}} \cdot \sqrt{n \cdot 2} \]

    Alternative 6: 50.1% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \frac{\sqrt{\pi \cdot \left(n \cdot 2\right)}}{\sqrt{k}} \end{array} \]
    (FPCore (k n) :precision binary64 (/ (sqrt (* PI (* n 2.0))) (sqrt k)))
    double code(double k, double n) {
    	return sqrt((((double) M_PI) * (n * 2.0))) / sqrt(k);
    }
    
    public static double code(double k, double n) {
    	return Math.sqrt((Math.PI * (n * 2.0))) / Math.sqrt(k);
    }
    
    def code(k, n):
    	return math.sqrt((math.pi * (n * 2.0))) / math.sqrt(k)
    
    function code(k, n)
    	return Float64(sqrt(Float64(pi * Float64(n * 2.0))) / sqrt(k))
    end
    
    function tmp = code(k, n)
    	tmp = sqrt((pi * (n * 2.0))) / sqrt(k);
    end
    
    code[k_, n_] := N[(N[Sqrt[N[(Pi * N[(n * 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
    
    \begin{array}{l}
    
    \\
    \frac{\sqrt{\pi \cdot \left(n \cdot 2\right)}}{\sqrt{k}}
    \end{array}
    
    Derivation
    1. Initial program 99.4%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Taylor expanded in k around 0 54.7%

      \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)} \]
    3. Step-by-step derivation
      1. expm1-log1p-u51.7%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{1}{\sqrt{k}} \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)\right)\right)} \]
      2. expm1-udef50.4%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{1}{\sqrt{k}} \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)\right)} - 1} \]
      3. associate-*l/50.4%

        \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\frac{1 \cdot \left(\sqrt{2} \cdot \sqrt{n \cdot \pi}\right)}{\sqrt{k}}}\right)} - 1 \]
      4. *-un-lft-identity50.4%

        \[\leadsto e^{\mathsf{log1p}\left(\frac{\color{blue}{\sqrt{2} \cdot \sqrt{n \cdot \pi}}}{\sqrt{k}}\right)} - 1 \]
      5. sqrt-unprod50.4%

        \[\leadsto e^{\mathsf{log1p}\left(\frac{\color{blue}{\sqrt{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}}\right)} - 1 \]
    4. Applied egg-rr50.4%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}\right)} - 1} \]
    5. Step-by-step derivation
      1. expm1-def51.7%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}\right)\right)} \]
      2. expm1-log1p54.9%

        \[\leadsto \color{blue}{\frac{\sqrt{2 \cdot \left(n \cdot \pi\right)}}{\sqrt{k}}} \]
      3. associate-*r*54.9%

        \[\leadsto \frac{\sqrt{\color{blue}{\left(2 \cdot n\right) \cdot \pi}}}{\sqrt{k}} \]
    6. Simplified54.9%

      \[\leadsto \color{blue}{\frac{\sqrt{\left(2 \cdot n\right) \cdot \pi}}{\sqrt{k}}} \]
    7. Final simplification54.9%

      \[\leadsto \frac{\sqrt{\pi \cdot \left(n \cdot 2\right)}}{\sqrt{k}} \]

    Alternative 7: 38.5% accurate, 1.5× speedup?

    \[\begin{array}{l} \\ \sqrt{2 \cdot \left(\pi \cdot \frac{n}{k}\right)} \end{array} \]
    (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}
    
    Derivation
    1. Initial program 99.4%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Step-by-step derivation
      1. *-commutative99.4%

        \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
      2. div-sub99.4%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
      3. metadata-eval99.4%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
      4. div-inv99.5%

        \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
      5. add-cube-cbrt98.7%

        \[\leadsto \color{blue}{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right) \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}} \]
      6. pow398.7%

        \[\leadsto \color{blue}{{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right)}^{3}} \]
    3. Applied egg-rr86.5%

      \[\leadsto \color{blue}{{\left(\sqrt[3]{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}}\right)}^{3}} \]
    4. Taylor expanded in k around 0 49.9%

      \[\leadsto \color{blue}{{\left(e^{0.16666666666666666 \cdot \left(-1 \cdot \log k + \log \left(2 \cdot \left(n \cdot \pi\right)\right)\right)}\right)}^{3}} \]
    5. Step-by-step derivation
      1. Simplified39.5%

        \[\leadsto \color{blue}{{\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}} \]
      2. Step-by-step derivation
        1. expm1-log1p-u39.7%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left({\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}\right)\right)} \]
        2. expm1-udef39.2%

          \[\leadsto \color{blue}{e^{\mathsf{log1p}\left({\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}\right)} - 1} \]
        3. pow-pow39.4%

          \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{{\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{\left(0.16666666666666666 \cdot 3\right)}}\right)} - 1 \]
        4. associate-/l*39.4%

          \[\leadsto e^{\mathsf{log1p}\left({\color{blue}{\left(\frac{\pi}{\frac{k}{n \cdot 2}}\right)}}^{\left(0.16666666666666666 \cdot 3\right)}\right)} - 1 \]
        5. *-commutative39.4%

          \[\leadsto e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{\color{blue}{2 \cdot n}}}\right)}^{\left(0.16666666666666666 \cdot 3\right)}\right)} - 1 \]
        6. metadata-eval39.4%

          \[\leadsto e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{\color{blue}{0.5}}\right)} - 1 \]
      3. Applied egg-rr39.4%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}\right)} - 1} \]
      4. Step-by-step derivation
        1. expm1-def40.7%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}\right)\right)} \]
        2. expm1-log1p42.6%

          \[\leadsto \color{blue}{{\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}} \]
        3. unpow1/242.6%

          \[\leadsto \color{blue}{\sqrt{\frac{\pi}{\frac{k}{2 \cdot n}}}} \]
        4. associate-/r/42.6%

          \[\leadsto \sqrt{\color{blue}{\frac{\pi}{k} \cdot \left(2 \cdot n\right)}} \]
        5. associate-*l/42.6%

          \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
        6. *-commutative42.6%

          \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot n\right) \cdot \pi}}{k}} \]
        7. associate-*r*42.6%

          \[\leadsto \sqrt{\frac{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}{k}} \]
        8. associate-*r/42.6%

          \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
        9. associate-/l*42.6%

          \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n}{\frac{k}{\pi}}}} \]
        10. associate-/r/42.6%

          \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
      5. Simplified42.6%

        \[\leadsto \color{blue}{\sqrt{2 \cdot \left(\frac{n}{k} \cdot \pi\right)}} \]
      6. Final simplification42.6%

        \[\leadsto \sqrt{2 \cdot \left(\pi \cdot \frac{n}{k}\right)} \]

      Alternative 8: 38.5% accurate, 1.5× speedup?

      \[\begin{array}{l} \\ \sqrt{2 \cdot \frac{\pi \cdot n}{k}} \end{array} \]
      (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(Float64(pi * 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[(N[(Pi * n), $MachinePrecision] / k), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      \sqrt{2 \cdot \frac{\pi \cdot n}{k}}
      \end{array}
      
      Derivation
      1. Initial program 99.4%

        \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
      2. Step-by-step derivation
        1. *-commutative99.4%

          \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
        2. div-sub99.4%

          \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
        3. metadata-eval99.4%

          \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
        4. div-inv99.5%

          \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
        5. add-cube-cbrt98.7%

          \[\leadsto \color{blue}{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right) \cdot \sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}} \]
        6. pow398.7%

          \[\leadsto \color{blue}{{\left(\sqrt[3]{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}}\right)}^{3}} \]
      3. Applied egg-rr86.5%

        \[\leadsto \color{blue}{{\left(\sqrt[3]{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}}\right)}^{3}} \]
      4. Taylor expanded in k around 0 49.9%

        \[\leadsto \color{blue}{{\left(e^{0.16666666666666666 \cdot \left(-1 \cdot \log k + \log \left(2 \cdot \left(n \cdot \pi\right)\right)\right)}\right)}^{3}} \]
      5. Step-by-step derivation
        1. Simplified39.5%

          \[\leadsto \color{blue}{{\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}} \]
        2. Step-by-step derivation
          1. expm1-log1p-u39.7%

            \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left({\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}\right)\right)} \]
          2. expm1-udef39.2%

            \[\leadsto \color{blue}{e^{\mathsf{log1p}\left({\left({\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{0.16666666666666666}\right)}^{3}\right)} - 1} \]
          3. pow-pow39.4%

            \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{{\left(\frac{\pi \cdot \left(n \cdot 2\right)}{k}\right)}^{\left(0.16666666666666666 \cdot 3\right)}}\right)} - 1 \]
          4. associate-/l*39.4%

            \[\leadsto e^{\mathsf{log1p}\left({\color{blue}{\left(\frac{\pi}{\frac{k}{n \cdot 2}}\right)}}^{\left(0.16666666666666666 \cdot 3\right)}\right)} - 1 \]
          5. *-commutative39.4%

            \[\leadsto e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{\color{blue}{2 \cdot n}}}\right)}^{\left(0.16666666666666666 \cdot 3\right)}\right)} - 1 \]
          6. metadata-eval39.4%

            \[\leadsto e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{\color{blue}{0.5}}\right)} - 1 \]
        3. Applied egg-rr39.4%

          \[\leadsto \color{blue}{e^{\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}\right)} - 1} \]
        4. Step-by-step derivation
          1. expm1-def40.7%

            \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}\right)\right)} \]
          2. expm1-log1p42.6%

            \[\leadsto \color{blue}{{\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.5}} \]
          3. unpow1/242.6%

            \[\leadsto \color{blue}{\sqrt{\frac{\pi}{\frac{k}{2 \cdot n}}}} \]
          4. associate-/r/42.6%

            \[\leadsto \sqrt{\color{blue}{\frac{\pi}{k} \cdot \left(2 \cdot n\right)}} \]
          5. associate-*l/42.6%

            \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
          6. *-commutative42.6%

            \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot n\right) \cdot \pi}}{k}} \]
          7. associate-*r*42.6%

            \[\leadsto \sqrt{\frac{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}{k}} \]
          8. associate-*r/42.6%

            \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
          9. associate-/l*42.6%

            \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n}{\frac{k}{\pi}}}} \]
          10. associate-/r/42.6%

            \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
        5. Simplified42.6%

          \[\leadsto \color{blue}{\sqrt{2 \cdot \left(\frac{n}{k} \cdot \pi\right)}} \]
        6. Taylor expanded in n around 0 42.6%

          \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n \cdot \pi}{k}}} \]
        7. Final simplification42.6%

          \[\leadsto \sqrt{2 \cdot \frac{\pi \cdot n}{k}} \]

        Reproduce

        ?
        herbie shell --seed 2023274 
        (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))))