Migdal et al, Equation (51)

Percentage Accurate: 99.4% → 99.5%
Time: 17.6s
Alternatives: 6
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 6 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: 99.4% 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: 99.5% accurate, 1.0× speedup?

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

\\
\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}
\end{array}
Derivation
  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. associate-*l/99.6%

      \[\leadsto \color{blue}{\frac{1 \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}} \]
    2. *-lft-identity99.6%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    3. sqr-pow99.4%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)}}}{\sqrt{k}} \]
    4. pow-sqr99.6%

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

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

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

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{\frac{2}{2}}\right)}}}{\sqrt{k}} \]
    8. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{\color{blue}{1}}\right)}}{\sqrt{k}} \]
    9. /-rgt-identity99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    10. div-sub99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}}}{\sqrt{k}} \]
    11. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
  3. Simplified99.6%

    \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
  4. Final simplification99.6%

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

Alternative 2: 99.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(2 \cdot n\right)\\ \mathbf{if}\;k \leq 1.42 \cdot 10^{-19}:\\ \;\;\;\;\frac{\sqrt{t_0}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{t_0}^{\left(1 - k\right)}}{k}}\\ \end{array} \end{array} \]
(FPCore (k n)
 :precision binary64
 (let* ((t_0 (* PI (* 2.0 n))))
   (if (<= k 1.42e-19)
     (/ (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) * (2.0 * n);
	double tmp;
	if (k <= 1.42e-19) {
		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 * (2.0 * n);
	double tmp;
	if (k <= 1.42e-19) {
		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 * (2.0 * n)
	tmp = 0
	if k <= 1.42e-19:
		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(2.0 * n))
	tmp = 0.0
	if (k <= 1.42e-19)
		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 * (2.0 * n);
	tmp = 0.0;
	if (k <= 1.42e-19)
		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[(2.0 * n), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, 1.42e-19], 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(2 \cdot n\right)\\
\mathbf{if}\;k \leq 1.42 \cdot 10^{-19}:\\
\;\;\;\;\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 < 1.42e-19

    1. Initial program 99.3%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Step-by-step derivation
      1. associate-*l/99.4%

        \[\leadsto \color{blue}{\frac{1 \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}} \]
      2. *-lft-identity99.4%

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

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

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

        \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{2} \cdot 2\right)}}}{\sqrt{k}} \]
      6. associate-*l/99.4%

        \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2} \cdot 2}{2}\right)}}}{\sqrt{k}} \]
      7. associate-/l*99.4%

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

        \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{\color{blue}{1}}\right)}}{\sqrt{k}} \]
      9. /-rgt-identity99.4%

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

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

        \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
    3. Simplified99.4%

      \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
    4. Step-by-step derivation
      1. add-sqr-sqrt99.5%

        \[\leadsto \frac{{\color{blue}{\left(\sqrt{\left(2 \cdot \pi\right) \cdot n} \cdot \sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
      2. pow299.5%

        \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
      3. associate-*l*99.5%

        \[\leadsto \frac{{\left({\left(\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}\right)}^{2}\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    5. Applied egg-rr99.5%

      \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{2 \cdot \left(\pi \cdot n\right)}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    6. Taylor expanded in k around 0 99.2%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    7. Step-by-step derivation
      1. expm1-log1p-u96.3%

        \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)\right)}}{\sqrt{k}} \]
      2. expm1-udef45.0%

        \[\leadsto \frac{\color{blue}{e^{\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} - 1}}{\sqrt{k}} \]
      3. sqrt-unprod45.0%

        \[\leadsto \frac{e^{\mathsf{log1p}\left(\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}\right)} - 1}{\sqrt{k}} \]
      4. *-commutative45.0%

        \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}\right)} - 1}{\sqrt{k}} \]
      5. associate-*r*45.0%

        \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\pi \cdot \left(n \cdot 2\right)}}\right)} - 1}{\sqrt{k}} \]
      6. *-commutative45.0%

        \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\pi \cdot \color{blue}{\left(2 \cdot n\right)}}\right)} - 1}{\sqrt{k}} \]
    8. Applied egg-rr45.0%

      \[\leadsto \frac{\color{blue}{e^{\mathsf{log1p}\left(\sqrt{\pi \cdot \left(2 \cdot n\right)}\right)} - 1}}{\sqrt{k}} \]
    9. Step-by-step derivation
      1. expm1-def96.4%

        \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\pi \cdot \left(2 \cdot n\right)}\right)\right)}}{\sqrt{k}} \]
      2. expm1-log1p99.5%

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

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

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

    if 1.42e-19 < k

    1. Initial program 99.7%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Step-by-step derivation
      1. *-commutative99.7%

        \[\leadsto \color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \cdot \frac{1}{\sqrt{k}}} \]
      2. div-sub99.7%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}} \cdot \frac{1}{\sqrt{k}} \]
      3. metadata-eval99.7%

        \[\leadsto {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)} \cdot \frac{1}{\sqrt{k}} \]
      4. div-inv99.7%

        \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
      5. expm1-log1p-u99.6%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
      6. expm1-udef97.3%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
    3. Applied egg-rr96.7%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
    4. Step-by-step derivation
      1. expm1-def99.0%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
      2. expm1-log1p99.0%

        \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
      3. associate-*r*99.0%

        \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)}}^{\left(1 - k\right)}}{k}} \]
      4. *-commutative99.0%

        \[\leadsto \sqrt{\frac{{\left(\color{blue}{\left(\pi \cdot 2\right)} \cdot n\right)}^{\left(1 - k\right)}}{k}} \]
      5. associate-*l*99.0%

        \[\leadsto \sqrt{\frac{{\color{blue}{\left(\pi \cdot \left(2 \cdot n\right)\right)}}^{\left(1 - k\right)}}{k}} \]
    5. Simplified99.0%

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

    \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq 1.42 \cdot 10^{-19}:\\ \;\;\;\;\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\\ \end{array} \]

Alternative 3: 49.8% accurate, 1.0× speedup?

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

\\
\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}
\end{array}
Derivation
  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. associate-*l/99.6%

      \[\leadsto \color{blue}{\frac{1 \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}} \]
    2. *-lft-identity99.6%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    3. sqr-pow99.4%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)}}}{\sqrt{k}} \]
    4. pow-sqr99.6%

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

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

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

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{\frac{2}{2}}\right)}}}{\sqrt{k}} \]
    8. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{\color{blue}{1}}\right)}}{\sqrt{k}} \]
    9. /-rgt-identity99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    10. div-sub99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}}}{\sqrt{k}} \]
    11. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
  3. Simplified99.6%

    \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
  4. Step-by-step derivation
    1. add-sqr-sqrt99.6%

      \[\leadsto \frac{{\color{blue}{\left(\sqrt{\left(2 \cdot \pi\right) \cdot n} \cdot \sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    2. pow299.6%

      \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    3. associate-*l*99.6%

      \[\leadsto \frac{{\left({\left(\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}\right)}^{2}\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
  5. Applied egg-rr99.6%

    \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{2 \cdot \left(\pi \cdot n\right)}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
  6. Taylor expanded in k around 0 52.6%

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

      \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)\right)}}{\sqrt{k}} \]
    2. expm1-udef24.5%

      \[\leadsto \frac{\color{blue}{e^{\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} - 1}}{\sqrt{k}} \]
    3. sqrt-unprod24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}\right)} - 1}{\sqrt{k}} \]
    4. *-commutative24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}\right)} - 1}{\sqrt{k}} \]
    5. associate-*r*24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\pi \cdot \left(n \cdot 2\right)}}\right)} - 1}{\sqrt{k}} \]
    6. *-commutative24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\pi \cdot \color{blue}{\left(2 \cdot n\right)}}\right)} - 1}{\sqrt{k}} \]
  8. Applied egg-rr24.5%

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

      \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\pi \cdot \left(2 \cdot n\right)}\right)\right)}}{\sqrt{k}} \]
    2. expm1-log1p52.7%

      \[\leadsto \frac{\color{blue}{\sqrt{\pi \cdot \left(2 \cdot n\right)}}}{\sqrt{k}} \]
    3. *-commutative52.7%

      \[\leadsto \frac{\sqrt{\pi \cdot \color{blue}{\left(n \cdot 2\right)}}}{\sqrt{k}} \]
  10. Simplified52.7%

    \[\leadsto \frac{\color{blue}{\sqrt{\pi \cdot \left(n \cdot 2\right)}}}{\sqrt{k}} \]
  11. Final simplification52.7%

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

Alternative 4: 38.5% accurate, 1.5× speedup?

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

\\
\frac{1}{\sqrt{\frac{\frac{k}{2}}{\pi \cdot n}}}
\end{array}
Derivation
  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. associate-*l/99.6%

      \[\leadsto \color{blue}{\frac{1 \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}} \]
    2. *-lft-identity99.6%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    3. sqr-pow99.4%

      \[\leadsto \frac{\color{blue}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{2}\right)}}}{\sqrt{k}} \]
    4. pow-sqr99.6%

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

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

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

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{\frac{1 - k}{2}}{\frac{2}{2}}\right)}}}{\sqrt{k}} \]
    8. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{\frac{1 - k}{2}}{\color{blue}{1}}\right)}}{\sqrt{k}} \]
    9. /-rgt-identity99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1 - k}{2}\right)}}}{\sqrt{k}} \]
    10. div-sub99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\color{blue}{\left(\frac{1}{2} - \frac{k}{2}\right)}}}{\sqrt{k}} \]
    11. metadata-eval99.6%

      \[\leadsto \frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
  3. Simplified99.6%

    \[\leadsto \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}} \]
  4. Step-by-step derivation
    1. add-sqr-sqrt99.6%

      \[\leadsto \frac{{\color{blue}{\left(\sqrt{\left(2 \cdot \pi\right) \cdot n} \cdot \sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    2. pow299.6%

      \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{\left(2 \cdot \pi\right) \cdot n}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
    3. associate-*l*99.6%

      \[\leadsto \frac{{\left({\left(\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}\right)}^{2}\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
  5. Applied egg-rr99.6%

    \[\leadsto \frac{{\color{blue}{\left({\left(\sqrt{2 \cdot \left(\pi \cdot n\right)}\right)}^{2}\right)}}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \]
  6. Taylor expanded in k around 0 52.6%

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

      \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)\right)}}{\sqrt{k}} \]
    2. expm1-udef24.5%

      \[\leadsto \frac{\color{blue}{e^{\mathsf{log1p}\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} - 1}}{\sqrt{k}} \]
    3. sqrt-unprod24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}\right)} - 1}{\sqrt{k}} \]
    4. *-commutative24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}\right)} - 1}{\sqrt{k}} \]
    5. associate-*r*24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\color{blue}{\pi \cdot \left(n \cdot 2\right)}}\right)} - 1}{\sqrt{k}} \]
    6. *-commutative24.5%

      \[\leadsto \frac{e^{\mathsf{log1p}\left(\sqrt{\pi \cdot \color{blue}{\left(2 \cdot n\right)}}\right)} - 1}{\sqrt{k}} \]
  8. Applied egg-rr24.5%

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

      \[\leadsto \frac{\color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\pi \cdot \left(2 \cdot n\right)}\right)\right)}}{\sqrt{k}} \]
    2. expm1-log1p52.7%

      \[\leadsto \frac{\color{blue}{\sqrt{\pi \cdot \left(2 \cdot n\right)}}}{\sqrt{k}} \]
    3. *-commutative52.7%

      \[\leadsto \frac{\sqrt{\pi \cdot \color{blue}{\left(n \cdot 2\right)}}}{\sqrt{k}} \]
  10. Simplified52.7%

    \[\leadsto \frac{\color{blue}{\sqrt{\pi \cdot \left(n \cdot 2\right)}}}{\sqrt{k}} \]
  11. Step-by-step derivation
    1. clear-num52.6%

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{k}}{\sqrt{\pi \cdot \left(n \cdot 2\right)}}}} \]
    2. inv-pow52.6%

      \[\leadsto \color{blue}{{\left(\frac{\sqrt{k}}{\sqrt{\pi \cdot \left(n \cdot 2\right)}}\right)}^{-1}} \]
    3. sqrt-prod52.4%

      \[\leadsto {\left(\frac{\sqrt{k}}{\color{blue}{\sqrt{\pi} \cdot \sqrt{n \cdot 2}}}\right)}^{-1} \]
    4. *-commutative52.4%

      \[\leadsto {\left(\frac{\sqrt{k}}{\sqrt{\pi} \cdot \sqrt{\color{blue}{2 \cdot n}}}\right)}^{-1} \]
    5. sqrt-prod52.6%

      \[\leadsto {\left(\frac{\sqrt{k}}{\color{blue}{\sqrt{\pi \cdot \left(2 \cdot n\right)}}}\right)}^{-1} \]
    6. sqrt-undiv43.0%

      \[\leadsto {\color{blue}{\left(\sqrt{\frac{k}{\pi \cdot \left(2 \cdot n\right)}}\right)}}^{-1} \]
    7. associate-*r*43.0%

      \[\leadsto {\left(\sqrt{\frac{k}{\color{blue}{\left(\pi \cdot 2\right) \cdot n}}}\right)}^{-1} \]
    8. *-commutative43.0%

      \[\leadsto {\left(\sqrt{\frac{k}{\color{blue}{\left(2 \cdot \pi\right)} \cdot n}}\right)}^{-1} \]
    9. associate-*l*43.0%

      \[\leadsto {\left(\sqrt{\frac{k}{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}\right)}^{-1} \]
  12. Applied egg-rr43.0%

    \[\leadsto \color{blue}{{\left(\sqrt{\frac{k}{2 \cdot \left(\pi \cdot n\right)}}\right)}^{-1}} \]
  13. Step-by-step derivation
    1. unpow-143.0%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k}{2 \cdot \left(\pi \cdot n\right)}}}} \]
    2. associate-/r*43.0%

      \[\leadsto \frac{1}{\sqrt{\color{blue}{\frac{\frac{k}{2}}{\pi \cdot n}}}} \]
    3. *-commutative43.0%

      \[\leadsto \frac{1}{\sqrt{\frac{\frac{k}{2}}{\color{blue}{n \cdot \pi}}}} \]
  14. Simplified43.0%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{\frac{k}{2}}{n \cdot \pi}}}} \]
  15. Final simplification43.0%

    \[\leadsto \frac{1}{\sqrt{\frac{\frac{k}{2}}{\pi \cdot n}}} \]

Alternative 5: 37.7% 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 99.5%

    \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
  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-u96.8%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
    6. expm1-udef84.8%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
  3. Applied egg-rr74.7%

    \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
  4. Step-by-step derivation
    1. expm1-def86.8%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
    2. expm1-log1p88.4%

      \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
    3. associate-*r*88.4%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)}}^{\left(1 - k\right)}}{k}} \]
    4. *-commutative88.4%

      \[\leadsto \sqrt{\frac{{\left(\color{blue}{\left(\pi \cdot 2\right)} \cdot n\right)}^{\left(1 - k\right)}}{k}} \]
    5. associate-*l*88.4%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\pi \cdot \left(2 \cdot n\right)\right)}}^{\left(1 - k\right)}}{k}} \]
  5. Simplified88.4%

    \[\leadsto \color{blue}{\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
  6. Taylor expanded in k around 0 41.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  7. Step-by-step derivation
    1. associate-/l*41.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n}{\frac{k}{\pi}}}} \]
    2. associate-/r/41.7%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
  8. Simplified41.7%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \left(\frac{n}{k} \cdot \pi\right)}} \]
  9. Final simplification41.7%

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

Alternative 6: 37.7% accurate, 1.5× speedup?

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

\\
\sqrt{2 \cdot \frac{\pi}{\frac{k}{n}}}
\end{array}
Derivation
  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-u96.8%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)\right)} \]
    6. expm1-udef84.8%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}\right)} - 1} \]
  3. Applied egg-rr74.7%

    \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)} - 1} \]
  4. Step-by-step derivation
    1. expm1-def86.8%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\right)\right)} \]
    2. expm1-log1p88.4%

      \[\leadsto \color{blue}{\sqrt{\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
    3. associate-*r*88.4%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)}}^{\left(1 - k\right)}}{k}} \]
    4. *-commutative88.4%

      \[\leadsto \sqrt{\frac{{\left(\color{blue}{\left(\pi \cdot 2\right)} \cdot n\right)}^{\left(1 - k\right)}}{k}} \]
    5. associate-*l*88.4%

      \[\leadsto \sqrt{\frac{{\color{blue}{\left(\pi \cdot \left(2 \cdot n\right)\right)}}^{\left(1 - k\right)}}{k}} \]
  5. Simplified88.4%

    \[\leadsto \color{blue}{\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}} \]
  6. Taylor expanded in k around 0 41.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  7. Step-by-step derivation
    1. associate-/l*41.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n}{\frac{k}{\pi}}}} \]
    2. associate-/r/41.7%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
  8. Simplified41.7%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \left(\frac{n}{k} \cdot \pi\right)}} \]
  9. Taylor expanded in n around 0 41.8%

    \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n \cdot \pi}{k}}} \]
  10. Step-by-step derivation
    1. *-commutative41.8%

      \[\leadsto \sqrt{2 \cdot \frac{\color{blue}{\pi \cdot n}}{k}} \]
    2. associate-/l*41.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{\pi}{\frac{k}{n}}}} \]
  11. Simplified41.8%

    \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{\pi}{\frac{k}{n}}}} \]
  12. Final simplification41.8%

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

Reproduce

?
herbie shell --seed 2023278 
(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))))