Migdal et al, Equation (51)

Percentage Accurate: 99.4% → 99.5%
Time: 15.1s
Alternatives: 9
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 9 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, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \pi \cdot \left(2 \cdot n\right)\\ \frac{\frac{\sqrt{t_0}}{\sqrt{k}}}{{t_0}^{\left(k \cdot 0.5\right)}} \end{array} \end{array} \]
(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}
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. Add Preprocessing
  3. Step-by-step derivation
    1. associate-/r/99.5%

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{k}}{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}}} \]
    2. clear-num99.6%

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

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

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

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

      \[\leadsto \frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(\color{blue}{0.5} - \frac{k}{2}\right)}}{\sqrt{k}} \]
    7. pow-sub99.7%

      \[\leadsto \frac{\color{blue}{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{0.5}}{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(\frac{k}{2}\right)}}}}{\sqrt{k}} \]
    8. pow1/299.7%

      \[\leadsto \frac{\frac{\color{blue}{\sqrt{\pi \cdot \left(2 \cdot n\right)}}}{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(\frac{k}{2}\right)}}}{\sqrt{k}} \]
    9. associate-/l/99.7%

      \[\leadsto \color{blue}{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k} \cdot {\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(\frac{k}{2}\right)}}} \]
    10. associate-*r*99.7%

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

      \[\leadsto \frac{\sqrt{\color{blue}{\left(2 \cdot \pi\right)} \cdot n}}{\sqrt{k} \cdot {\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(\frac{k}{2}\right)}} \]
    12. associate-*l*99.7%

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

    \[\leadsto \color{blue}{\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k} \cdot {\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}}} \]
  5. Step-by-step derivation
    1. associate-/r*99.7%

      \[\leadsto \color{blue}{\frac{\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}}{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}}} \]
    2. associate-*r*99.7%

      \[\leadsto \frac{\frac{\sqrt{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}}{\sqrt{k}}}{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}} \]
    3. *-commutative99.7%

      \[\leadsto \frac{\frac{\sqrt{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}}{\sqrt{k}}}{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}} \]
    4. associate-*l*99.7%

      \[\leadsto \frac{\frac{\sqrt{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}}{\sqrt{k}}}{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}} \]
    5. associate-*r*99.7%

      \[\leadsto \frac{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}}{{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)}}^{\left(k \cdot 0.5\right)}} \]
    6. *-commutative99.7%

      \[\leadsto \frac{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}}{{\left(\color{blue}{\left(\pi \cdot 2\right)} \cdot n\right)}^{\left(k \cdot 0.5\right)}} \]
    7. associate-*l*99.7%

      \[\leadsto \frac{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}}{{\color{blue}{\left(\pi \cdot \left(2 \cdot n\right)\right)}}^{\left(k \cdot 0.5\right)}} \]
  6. Simplified99.7%

    \[\leadsto \color{blue}{\frac{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}}{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}}} \]
  7. Final simplification99.7%

    \[\leadsto \frac{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}}{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(k \cdot 0.5\right)}} \]
  8. Add Preprocessing

Alternative 2: 51.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq 9 \cdot 10^{+264}:\\ \;\;\;\;\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt[3]{{\left(\frac{n}{k} \cdot \left(\pi \cdot 2\right)\right)}^{1.5}}\\ \end{array} \end{array} \]
(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}
Derivation
  1. Split input into 2 regimes
  2. if k < 9.00000000000000006e264

    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. Add Preprocessing
    3. Taylor expanded in k around 0 54.2%

      \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
    4. Step-by-step derivation
      1. associate-*l/54.2%

        \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
      2. *-un-lft-identity54.2%

        \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
      3. sqrt-unprod54.3%

        \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
      4. *-commutative54.3%

        \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
      5. *-commutative54.3%

        \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    5. Applied egg-rr54.3%

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

    if 9.00000000000000006e264 < k

    1. Initial program 100.0%

      \[\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)} \]
    2. Add Preprocessing
    3. Taylor expanded in k around 0 3.4%

      \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
    4. Step-by-step derivation
      1. associate-*l/3.4%

        \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
      2. *-un-lft-identity3.4%

        \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
      3. sqrt-unprod3.4%

        \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
      4. *-commutative3.4%

        \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
      5. *-commutative3.4%

        \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
      6. sqrt-undiv3.3%

        \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    5. Applied egg-rr3.3%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    6. Step-by-step derivation
      1. div-inv3.3%

        \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \left(\pi \cdot n\right)\right) \cdot \frac{1}{k}}} \]
      2. associate-*r*3.3%

        \[\leadsto \sqrt{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)} \cdot \frac{1}{k}} \]
      3. *-commutative3.3%

        \[\leadsto \sqrt{\color{blue}{\left(n \cdot \left(2 \cdot \pi\right)\right)} \cdot \frac{1}{k}} \]
      4. associate-*l*3.3%

        \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(2 \cdot \pi\right) \cdot \frac{1}{k}\right)}} \]
      5. *-commutative3.3%

        \[\leadsto \sqrt{n \cdot \left(\color{blue}{\left(\pi \cdot 2\right)} \cdot \frac{1}{k}\right)} \]
    7. Applied egg-rr3.3%

      \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}} \]
    8. Step-by-step derivation
      1. add-cbrt-cube37.0%

        \[\leadsto \color{blue}{\sqrt[3]{\left(\sqrt{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)} \cdot \sqrt{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}\right) \cdot \sqrt{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}}} \]
      2. add-sqr-sqrt37.0%

        \[\leadsto \sqrt[3]{\color{blue}{\left(n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)\right)} \cdot \sqrt{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}} \]
      3. pow137.0%

        \[\leadsto \sqrt[3]{\color{blue}{{\left(n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)\right)}^{1}} \cdot \sqrt{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}} \]
      4. pow1/237.0%

        \[\leadsto \sqrt[3]{{\left(n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)\right)}^{1} \cdot \color{blue}{{\left(n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)\right)}^{0.5}}} \]
      5. pow-prod-up37.0%

        \[\leadsto \sqrt[3]{\color{blue}{{\left(n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)\right)}^{\left(1 + 0.5\right)}}} \]
      6. *-commutative37.0%

        \[\leadsto \sqrt[3]{{\left(n \cdot \color{blue}{\left(\frac{1}{k} \cdot \left(\pi \cdot 2\right)\right)}\right)}^{\left(1 + 0.5\right)}} \]
      7. associate-*r*37.0%

        \[\leadsto \sqrt[3]{{\color{blue}{\left(\left(n \cdot \frac{1}{k}\right) \cdot \left(\pi \cdot 2\right)\right)}}^{\left(1 + 0.5\right)}} \]
      8. div-inv37.0%

        \[\leadsto \sqrt[3]{{\left(\color{blue}{\frac{n}{k}} \cdot \left(\pi \cdot 2\right)\right)}^{\left(1 + 0.5\right)}} \]
      9. *-commutative37.0%

        \[\leadsto \sqrt[3]{{\left(\frac{n}{k} \cdot \color{blue}{\left(2 \cdot \pi\right)}\right)}^{\left(1 + 0.5\right)}} \]
      10. metadata-eval37.0%

        \[\leadsto \sqrt[3]{{\left(\frac{n}{k} \cdot \left(2 \cdot \pi\right)\right)}^{\color{blue}{1.5}}} \]
    9. Applied egg-rr37.0%

      \[\leadsto \color{blue}{\sqrt[3]{{\left(\frac{n}{k} \cdot \left(2 \cdot \pi\right)\right)}^{1.5}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification53.1%

    \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq 9 \cdot 10^{+264}:\\ \;\;\;\;\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt[3]{{\left(\frac{n}{k} \cdot \left(\pi \cdot 2\right)\right)}^{1.5}}\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 99.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \end{array} \]
(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}
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%

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

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

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

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

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

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

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

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

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

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

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

Alternative 4: 50.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{2 \cdot \frac{\pi}{k}} \cdot \sqrt{n} \end{array} \]
(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}
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. Add Preprocessing
  3. Taylor expanded in k around 0 50.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  4. Step-by-step derivation
    1. associate-*l/50.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity50.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod50.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
    5. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv40.3%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  5. Applied egg-rr40.3%

    \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  6. Step-by-step derivation
    1. div-inv40.3%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \left(\pi \cdot n\right)\right) \cdot \frac{1}{k}}} \]
    2. associate-*r*40.3%

      \[\leadsto \sqrt{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)} \cdot \frac{1}{k}} \]
    3. *-commutative40.3%

      \[\leadsto \sqrt{\color{blue}{\left(n \cdot \left(2 \cdot \pi\right)\right)} \cdot \frac{1}{k}} \]
    4. associate-*l*40.3%

      \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(2 \cdot \pi\right) \cdot \frac{1}{k}\right)}} \]
    5. *-commutative40.3%

      \[\leadsto \sqrt{n \cdot \left(\color{blue}{\left(\pi \cdot 2\right)} \cdot \frac{1}{k}\right)} \]
  7. Applied egg-rr40.3%

    \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}} \]
  8. Step-by-step derivation
    1. *-commutative40.3%

      \[\leadsto \sqrt{\color{blue}{\left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right) \cdot n}} \]
    2. sqrt-prod50.9%

      \[\leadsto \color{blue}{\sqrt{\left(\pi \cdot 2\right) \cdot \frac{1}{k}} \cdot \sqrt{n}} \]
    3. un-div-inv50.9%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot 2}{k}}} \cdot \sqrt{n} \]
    4. *-commutative50.9%

      \[\leadsto \sqrt{\frac{\color{blue}{2 \cdot \pi}}{k}} \cdot \sqrt{n} \]
    5. *-un-lft-identity50.9%

      \[\leadsto \sqrt{\frac{2 \cdot \pi}{\color{blue}{1 \cdot k}}} \cdot \sqrt{n} \]
    6. times-frac50.9%

      \[\leadsto \sqrt{\color{blue}{\frac{2}{1} \cdot \frac{\pi}{k}}} \cdot \sqrt{n} \]
    7. metadata-eval50.9%

      \[\leadsto \sqrt{\color{blue}{2} \cdot \frac{\pi}{k}} \cdot \sqrt{n} \]
  9. Applied egg-rr50.9%

    \[\leadsto \color{blue}{\sqrt{2 \cdot \frac{\pi}{k}} \cdot \sqrt{n}} \]
  10. Final simplification50.9%

    \[\leadsto \sqrt{2 \cdot \frac{\pi}{k}} \cdot \sqrt{n} \]
  11. Add Preprocessing

Alternative 5: 50.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}} \end{array} \]
(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}
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. Add Preprocessing
  3. Taylor expanded in k around 0 50.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  4. Step-by-step derivation
    1. associate-*l/50.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity50.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod50.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
    5. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
  5. Applied egg-rr50.9%

    \[\leadsto \color{blue}{\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}} \]
  6. Final simplification50.9%

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

Alternative 6: 39.3% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \frac{1}{\sqrt{\frac{0.5}{\pi} \cdot \frac{k}{n}}} \end{array} \]
(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}
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. Add Preprocessing
  3. Applied egg-rr99.3%

    \[\leadsto \color{blue}{{\left(\frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(\frac{1 - k}{4}\right)}}{{k}^{0.25}}\right)}^{2}} \]
  4. Taylor expanded in k around 0 40.2%

    \[\leadsto {\color{blue}{\left({\left(2 \cdot \frac{n \cdot \pi}{k}\right)}^{0.25}\right)}}^{2} \]
  5. Step-by-step derivation
    1. associate-*r/40.2%

      \[\leadsto {\left({\color{blue}{\left(\frac{2 \cdot \left(n \cdot \pi\right)}{k}\right)}}^{0.25}\right)}^{2} \]
    2. *-commutative40.2%

      \[\leadsto {\left({\left(\frac{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}{k}\right)}^{0.25}\right)}^{2} \]
    3. associate-*r*40.2%

      \[\leadsto {\left({\left(\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}\right)}^{0.25}\right)}^{2} \]
    4. *-commutative40.2%

      \[\leadsto {\left({\left(\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}\right)}^{0.25}\right)}^{2} \]
    5. associate-*l*40.2%

      \[\leadsto {\left({\left(\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}\right)}^{0.25}\right)}^{2} \]
    6. associate-/l*40.2%

      \[\leadsto {\left({\color{blue}{\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}}^{0.25}\right)}^{2} \]
  6. Simplified40.2%

    \[\leadsto {\color{blue}{\left({\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{0.25}\right)}}^{2} \]
  7. Step-by-step derivation
    1. pow-pow40.3%

      \[\leadsto \color{blue}{{\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{\left(0.25 \cdot 2\right)}} \]
    2. metadata-eval40.3%

      \[\leadsto {\left(\frac{\pi}{\frac{k}{2 \cdot n}}\right)}^{\color{blue}{0.5}} \]
    3. pow1/240.3%

      \[\leadsto \color{blue}{\sqrt{\frac{\pi}{\frac{k}{2 \cdot n}}}} \]
    4. clear-num40.3%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{\frac{k}{2 \cdot n}}{\pi}}}} \]
    5. sqrt-div41.4%

      \[\leadsto \color{blue}{\frac{\sqrt{1}}{\sqrt{\frac{\frac{k}{2 \cdot n}}{\pi}}}} \]
    6. metadata-eval41.4%

      \[\leadsto \frac{\color{blue}{1}}{\sqrt{\frac{\frac{k}{2 \cdot n}}{\pi}}} \]
    7. *-un-lft-identity41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{\frac{\color{blue}{1 \cdot k}}{2 \cdot n}}{\pi}}} \]
    8. times-frac41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{\color{blue}{\frac{1}{2} \cdot \frac{k}{n}}}{\pi}}} \]
    9. metadata-eval41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{\color{blue}{0.5} \cdot \frac{k}{n}}{\pi}}} \]
  8. Applied egg-rr41.4%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{0.5 \cdot \frac{k}{n}}{\pi}}}} \]
  9. Step-by-step derivation
    1. associate-/l*40.3%

      \[\leadsto \frac{1}{\sqrt{\color{blue}{\frac{0.5}{\frac{\pi}{\frac{k}{n}}}}}} \]
    2. associate-/r/41.3%

      \[\leadsto \frac{1}{\sqrt{\color{blue}{\frac{0.5}{\pi} \cdot \frac{k}{n}}}} \]
  10. Simplified41.3%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{0.5}{\pi} \cdot \frac{k}{n}}}} \]
  11. Final simplification41.3%

    \[\leadsto \frac{1}{\sqrt{\frac{0.5}{\pi} \cdot \frac{k}{n}}} \]
  12. Add Preprocessing

Alternative 7: 39.3% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \frac{1}{\sqrt{\frac{k}{n \cdot \frac{\pi}{0.5}}}} \end{array} \]
(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}
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. Add Preprocessing
  3. Taylor expanded in k around 0 50.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  4. Step-by-step derivation
    1. associate-*l/50.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity50.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod50.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
    5. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv40.3%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  5. Applied egg-rr40.3%

    \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  6. Step-by-step derivation
    1. div-inv40.3%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \left(\pi \cdot n\right)\right) \cdot \frac{1}{k}}} \]
    2. associate-*r*40.3%

      \[\leadsto \sqrt{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot n\right)} \cdot \frac{1}{k}} \]
    3. *-commutative40.3%

      \[\leadsto \sqrt{\color{blue}{\left(n \cdot \left(2 \cdot \pi\right)\right)} \cdot \frac{1}{k}} \]
    4. associate-*l*40.3%

      \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(2 \cdot \pi\right) \cdot \frac{1}{k}\right)}} \]
    5. *-commutative40.3%

      \[\leadsto \sqrt{n \cdot \left(\color{blue}{\left(\pi \cdot 2\right)} \cdot \frac{1}{k}\right)} \]
  7. Applied egg-rr40.3%

    \[\leadsto \sqrt{\color{blue}{n \cdot \left(\left(\pi \cdot 2\right) \cdot \frac{1}{k}\right)}} \]
  8. Step-by-step derivation
    1. associate-*r*40.3%

      \[\leadsto \sqrt{\color{blue}{\left(n \cdot \left(\pi \cdot 2\right)\right) \cdot \frac{1}{k}}} \]
    2. sqrt-prod50.8%

      \[\leadsto \color{blue}{\sqrt{n \cdot \left(\pi \cdot 2\right)} \cdot \sqrt{\frac{1}{k}}} \]
    3. associate-*r*50.8%

      \[\leadsto \sqrt{\color{blue}{\left(n \cdot \pi\right) \cdot 2}} \cdot \sqrt{\frac{1}{k}} \]
    4. *-commutative50.8%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2} \cdot \sqrt{\frac{1}{k}} \]
    5. *-commutative50.8%

      \[\leadsto \sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}} \cdot \sqrt{\frac{1}{k}} \]
    6. sqrt-div50.8%

      \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot \color{blue}{\frac{\sqrt{1}}{\sqrt{k}}} \]
    7. metadata-eval50.8%

      \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot \frac{\color{blue}{1}}{\sqrt{k}} \]
    8. div-inv50.9%

      \[\leadsto \color{blue}{\frac{\sqrt{2 \cdot \left(\pi \cdot n\right)}}{\sqrt{k}}} \]
    9. clear-num50.8%

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{k}}{\sqrt{2 \cdot \left(\pi \cdot n\right)}}}} \]
    10. sqrt-undiv41.4%

      \[\leadsto \frac{1}{\color{blue}{\sqrt{\frac{k}{2 \cdot \left(\pi \cdot n\right)}}}} \]
    11. *-commutative41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\left(\pi \cdot n\right) \cdot 2}}}} \]
    12. *-commutative41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\left(n \cdot \pi\right)} \cdot 2}}} \]
    13. associate-*r*41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{n \cdot \left(\pi \cdot 2\right)}}}} \]
    14. *-commutative41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{n \cdot \color{blue}{\left(2 \cdot \pi\right)}}}} \]
  9. Applied egg-rr41.4%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k}{n \cdot \left(2 \cdot \pi\right)}}}} \]
  10. Step-by-step derivation
    1. *-commutative41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}}} \]
    2. *-commutative41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}}} \]
    3. associate-*r*41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}}} \]
    4. /-rgt-identity41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\frac{\pi}{1}} \cdot \left(2 \cdot n\right)}}} \]
    5. associate-/r/41.3%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\frac{\pi}{\frac{1}{2 \cdot n}}}}}} \]
    6. associate-/r*41.3%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\frac{\pi}{\color{blue}{\frac{\frac{1}{2}}{n}}}}}} \]
    7. metadata-eval41.3%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\frac{\pi}{\frac{\color{blue}{0.5}}{n}}}}} \]
    8. associate-/r/41.4%

      \[\leadsto \frac{1}{\sqrt{\frac{k}{\color{blue}{\frac{\pi}{0.5} \cdot n}}}} \]
  11. Simplified41.4%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k}{\frac{\pi}{0.5} \cdot n}}}} \]
  12. Final simplification41.4%

    \[\leadsto \frac{1}{\sqrt{\frac{k}{n \cdot \frac{\pi}{0.5}}}} \]
  13. Add Preprocessing

Alternative 8: 38.6% accurate, 2.0× 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. Add Preprocessing
  3. Taylor expanded in k around 0 50.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  4. Step-by-step derivation
    1. associate-*l/50.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity50.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod50.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
    5. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv40.3%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  5. Applied egg-rr40.3%

    \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  6. Taylor expanded in n around 0 40.3%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  7. Step-by-step derivation
    1. associate-/l*40.3%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{n}{\frac{k}{\pi}}}} \]
  8. Simplified40.3%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n}{\frac{k}{\pi}}}} \]
  9. Step-by-step derivation
    1. associate-/r/40.3%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
  10. Applied egg-rr40.3%

    \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
  11. Final simplification40.3%

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

Alternative 9: 38.7% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}} \end{array} \]
(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(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}
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. Add Preprocessing
  3. Taylor expanded in k around 0 50.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  4. Step-by-step derivation
    1. associate-*l/50.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity50.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod50.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot n\right)} \cdot 2}}{\sqrt{k}} \]
    5. *-commutative50.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv40.3%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  5. Applied egg-rr40.3%

    \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
  6. Final simplification40.3%

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

Reproduce

?
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))))