Migdal et al, Equation (51)

Percentage Accurate: 99.4% → 99.5%
Time: 16.0s
Alternatives: 10
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 10 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?

\[\begin{array}{l} \\ \frac{{\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}} \end{array} \]
(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(2.0 * Float64(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[(2.0 * N[(Pi * n), $MachinePrecision]), $MachinePrecision], N[(0.5 - N[(k / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{{\left(2 \cdot \left(\pi \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. associate-*l*99.6%

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

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

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

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

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

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

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

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

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

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

Alternative 2: 99.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq 2.1 \cdot 10^{-26}:\\ \;\;\;\;\sqrt{\frac{\pi}{\frac{0.5}{n}}} \cdot {k}^{-0.5}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\\ \end{array} \end{array} \]
(FPCore (k n)
 :precision binary64
 (if (<= k 2.1e-26)
   (* (sqrt (/ PI (/ 0.5 n))) (pow k -0.5))
   (sqrt (/ (pow (* PI (* 2.0 n)) (- 1.0 k)) k))))
double code(double k, double n) {
	double tmp;
	if (k <= 2.1e-26) {
		tmp = sqrt((((double) M_PI) / (0.5 / n))) * pow(k, -0.5);
	} else {
		tmp = sqrt((pow((((double) M_PI) * (2.0 * n)), (1.0 - k)) / k));
	}
	return tmp;
}
public static double code(double k, double n) {
	double tmp;
	if (k <= 2.1e-26) {
		tmp = Math.sqrt((Math.PI / (0.5 / n))) * Math.pow(k, -0.5);
	} else {
		tmp = Math.sqrt((Math.pow((Math.PI * (2.0 * n)), (1.0 - k)) / k));
	}
	return tmp;
}
def code(k, n):
	tmp = 0
	if k <= 2.1e-26:
		tmp = math.sqrt((math.pi / (0.5 / n))) * math.pow(k, -0.5)
	else:
		tmp = math.sqrt((math.pow((math.pi * (2.0 * n)), (1.0 - k)) / k))
	return tmp
function code(k, n)
	tmp = 0.0
	if (k <= 2.1e-26)
		tmp = Float64(sqrt(Float64(pi / Float64(0.5 / n))) * (k ^ -0.5));
	else
		tmp = sqrt(Float64((Float64(pi * Float64(2.0 * n)) ^ Float64(1.0 - k)) / k));
	end
	return tmp
end
function tmp_2 = code(k, n)
	tmp = 0.0;
	if (k <= 2.1e-26)
		tmp = sqrt((pi / (0.5 / n))) * (k ^ -0.5);
	else
		tmp = sqrt((((pi * (2.0 * n)) ^ (1.0 - k)) / k));
	end
	tmp_2 = tmp;
end
code[k_, n_] := If[LessEqual[k, 2.1e-26], N[(N[Sqrt[N[(Pi / N[(0.5 / n), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Power[k, -0.5], $MachinePrecision]), $MachinePrecision], N[Sqrt[N[(N[Power[N[(Pi * N[(2.0 * n), $MachinePrecision]), $MachinePrecision], N[(1.0 - k), $MachinePrecision]], $MachinePrecision] / k), $MachinePrecision]], $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;k \leq 2.1 \cdot 10^{-26}:\\
\;\;\;\;\sqrt{\frac{\pi}{\frac{0.5}{n}}} \cdot {k}^{-0.5}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if k < 2.10000000000000008e-26

    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. Taylor expanded in k around 0 99.2%

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

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

        \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
      3. sqrt-unprod99.3%

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

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

        \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
      6. sqrt-undiv76.5%

        \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
      7. associate-*r*76.5%

        \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
      8. *-commutative76.5%

        \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
      9. associate-*r*76.5%

        \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
    4. Applied egg-rr76.5%

      \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
    5. Step-by-step derivation
      1. sqrt-div99.3%

        \[\leadsto \color{blue}{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}} \]
      2. div-inv99.3%

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

        \[\leadsto \sqrt{\pi \cdot \left(2 \cdot n\right)} \cdot \frac{\color{blue}{\sqrt{1}}}{\sqrt{k}} \]
      4. sqrt-div99.3%

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

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

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

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

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

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

        \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot {k}^{\color{blue}{-0.5}} \]
    6. Applied egg-rr99.3%

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

        \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot 2}} \cdot {k}^{-0.5} \]
      2. associate-*l*99.3%

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

      \[\leadsto \color{blue}{\sqrt{\pi \cdot \left(n \cdot 2\right)} \cdot {k}^{-0.5}} \]
    9. Step-by-step derivation
      1. associate-*r*99.3%

        \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot 2}} \cdot {k}^{-0.5} \]
      2. metadata-eval99.3%

        \[\leadsto \sqrt{\left(\pi \cdot n\right) \cdot \color{blue}{\frac{1}{0.5}}} \cdot {k}^{-0.5} \]
      3. div-inv99.3%

        \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5}}} \cdot {k}^{-0.5} \]
      4. associate-/l*99.4%

        \[\leadsto \sqrt{\color{blue}{\frac{\pi}{\frac{0.5}{n}}}} \cdot {k}^{-0.5} \]
    10. Applied egg-rr99.4%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi}{\frac{0.5}{n}}}} \cdot {k}^{-0.5} \]

    if 2.10000000000000008e-26 < 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. add-sqr-sqrt99.7%

        \[\leadsto \color{blue}{\sqrt{\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}} \cdot \sqrt{\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}} \]
      2. sqrt-unprod99.1%

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

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

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

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

        \[\leadsto \sqrt{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}} \cdot \color{blue}{\frac{{\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}}{\sqrt{k}}}} \]
      7. frac-times99.1%

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

      \[\leadsto \color{blue}{\sqrt{\frac{{\left({\left(2 \cdot \left(\pi \cdot n\right)\right)}^{\left(0.5 - k \cdot 0.5\right)}\right)}^{2}}{k}}} \]
    4. Simplified99.1%

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

    \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq 2.1 \cdot 10^{-26}:\\ \;\;\;\;\sqrt{\frac{\pi}{\frac{0.5}{n}}} \cdot {k}^{-0.5}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{{\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(1 - k\right)}}{k}}\\ \end{array} \]

Alternative 3: 50.1% accurate, 1.0× speedup?

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

\\
\sqrt{\frac{\pi}{\frac{0.5}{n}}} \cdot {k}^{-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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Step-by-step derivation
    1. sqrt-div47.9%

      \[\leadsto \color{blue}{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}} \]
    2. div-inv47.9%

      \[\leadsto \color{blue}{\sqrt{\pi \cdot \left(2 \cdot n\right)} \cdot \frac{1}{\sqrt{k}}} \]
    3. metadata-eval47.9%

      \[\leadsto \sqrt{\pi \cdot \left(2 \cdot n\right)} \cdot \frac{\color{blue}{\sqrt{1}}}{\sqrt{k}} \]
    4. sqrt-div47.9%

      \[\leadsto \sqrt{\pi \cdot \left(2 \cdot n\right)} \cdot \color{blue}{\sqrt{\frac{1}{k}}} \]
    5. associate-*r*47.9%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot 2\right) \cdot n}} \cdot \sqrt{\frac{1}{k}} \]
    6. *-commutative47.9%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \pi\right)} \cdot n} \cdot \sqrt{\frac{1}{k}} \]
    7. associate-*l*47.9%

      \[\leadsto \sqrt{\color{blue}{2 \cdot \left(\pi \cdot n\right)}} \cdot \sqrt{\frac{1}{k}} \]
    8. inv-pow47.9%

      \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot \sqrt{\color{blue}{{k}^{-1}}} \]
    9. sqrt-pow147.9%

      \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot \color{blue}{{k}^{\left(\frac{-1}{2}\right)}} \]
    10. metadata-eval47.9%

      \[\leadsto \sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot {k}^{\color{blue}{-0.5}} \]
  6. Applied egg-rr47.9%

    \[\leadsto \color{blue}{\sqrt{2 \cdot \left(\pi \cdot n\right)} \cdot {k}^{-0.5}} \]
  7. Step-by-step derivation
    1. *-commutative47.9%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot 2}} \cdot {k}^{-0.5} \]
    2. associate-*l*47.9%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot 2\right)}} \cdot {k}^{-0.5} \]
  8. Simplified47.9%

    \[\leadsto \color{blue}{\sqrt{\pi \cdot \left(n \cdot 2\right)} \cdot {k}^{-0.5}} \]
  9. Step-by-step derivation
    1. associate-*r*47.9%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot 2}} \cdot {k}^{-0.5} \]
    2. metadata-eval47.9%

      \[\leadsto \sqrt{\left(\pi \cdot n\right) \cdot \color{blue}{\frac{1}{0.5}}} \cdot {k}^{-0.5} \]
    3. div-inv47.9%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5}}} \cdot {k}^{-0.5} \]
    4. associate-/l*47.9%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi}{\frac{0.5}{n}}}} \cdot {k}^{-0.5} \]
  10. Applied egg-rr47.9%

    \[\leadsto \sqrt{\color{blue}{\frac{\pi}{\frac{0.5}{n}}}} \cdot {k}^{-0.5} \]
  11. Final simplification47.9%

    \[\leadsto \sqrt{\frac{\pi}{\frac{0.5}{n}}} \cdot {k}^{-0.5} \]

Alternative 4: 50.0% accurate, 1.0× speedup?

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

\\
\sqrt{\frac{2}{k}} \cdot \sqrt{\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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Step-by-step derivation
    1. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot \frac{2}{k}}} \]
    2. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\left(\pi \cdot n\right) \cdot 2}{k}}} \]
    3. metadata-eval37.8%

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

      \[\leadsto \sqrt{\frac{\color{blue}{\frac{\pi \cdot n}{0.5}}}{k}} \]
    5. associate-/r*37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5 \cdot k}}} \]
    6. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\pi \cdot n}{\color{blue}{k \cdot 0.5}}} \]
    7. clear-num37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    8. metadata-eval37.7%

      \[\leadsto \sqrt{\frac{\color{blue}{1 \cdot 1}}{\frac{k \cdot 0.5}{\pi \cdot n}}} \]
    9. add-sqr-sqrt37.7%

      \[\leadsto \sqrt{\frac{1 \cdot 1}{\color{blue}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}} \cdot \sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    10. frac-times37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}} \cdot \frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    11. sqrt-unprod38.2%

      \[\leadsto \color{blue}{\sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \cdot \sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    12. add-sqr-sqrt38.5%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    13. sqrt-div47.9%

      \[\leadsto \frac{1}{\color{blue}{\frac{\sqrt{k \cdot 0.5}}{\sqrt{\pi \cdot n}}}} \]
    14. associate-/r/47.9%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{k \cdot 0.5}} \cdot \sqrt{\pi \cdot n}} \]
  9. Applied egg-rr47.9%

    \[\leadsto \color{blue}{\sqrt{\frac{2}{k}} \cdot \sqrt{\pi \cdot n}} \]
  10. Final simplification47.9%

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

Alternative 5: 50.1% 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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. associate-*l/47.8%

      \[\leadsto \color{blue}{\frac{1 \cdot \left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)}{\sqrt{k}}} \]
    2. *-un-lft-identity47.8%

      \[\leadsto \frac{\color{blue}{\sqrt{n \cdot \pi} \cdot \sqrt{2}}}{\sqrt{k}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. associate-*r*47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}}{\sqrt{k}} \]
    7. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}}{\sqrt{k}} \]
    8. associate-*r*47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}}{\sqrt{k}} \]
  4. Applied egg-rr47.9%

    \[\leadsto \color{blue}{\frac{\sqrt{\pi \cdot \left(2 \cdot n\right)}}{\sqrt{k}}} \]
  5. Final simplification47.9%

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

Alternative 6: 38.7% accurate, 1.5× speedup?

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

\\
{\left(\frac{k}{n} \cdot \frac{0.5}{\pi}\right)}^{-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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Step-by-step derivation
    1. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot \frac{2}{k}}} \]
    2. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\left(\pi \cdot n\right) \cdot 2}{k}}} \]
    3. metadata-eval37.8%

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

      \[\leadsto \sqrt{\frac{\color{blue}{\frac{\pi \cdot n}{0.5}}}{k}} \]
    5. associate-/r*37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5 \cdot k}}} \]
    6. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\pi \cdot n}{\color{blue}{k \cdot 0.5}}} \]
    7. clear-num37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    8. metadata-eval37.7%

      \[\leadsto \sqrt{\frac{\color{blue}{1 \cdot 1}}{\frac{k \cdot 0.5}{\pi \cdot n}}} \]
    9. add-sqr-sqrt37.7%

      \[\leadsto \sqrt{\frac{1 \cdot 1}{\color{blue}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}} \cdot \sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    10. frac-times37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}} \cdot \frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    11. sqrt-unprod38.2%

      \[\leadsto \color{blue}{\sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \cdot \sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    12. add-sqr-sqrt38.5%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    13. inv-pow38.5%

      \[\leadsto \color{blue}{{\left(\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}\right)}^{-1}} \]
    14. sqrt-pow238.5%

      \[\leadsto \color{blue}{{\left(\frac{k \cdot 0.5}{\pi \cdot n}\right)}^{\left(\frac{-1}{2}\right)}} \]
  9. Applied egg-rr38.5%

    \[\leadsto \color{blue}{{\left(0.5 \cdot \frac{k}{\pi \cdot n}\right)}^{-0.5}} \]
  10. Step-by-step derivation
    1. associate-*r/38.5%

      \[\leadsto {\color{blue}{\left(\frac{0.5 \cdot k}{\pi \cdot n}\right)}}^{-0.5} \]
    2. *-commutative38.5%

      \[\leadsto {\left(\frac{\color{blue}{k \cdot 0.5}}{\pi \cdot n}\right)}^{-0.5} \]
    3. *-commutative38.5%

      \[\leadsto {\left(\frac{k \cdot 0.5}{\color{blue}{n \cdot \pi}}\right)}^{-0.5} \]
    4. times-frac38.5%

      \[\leadsto {\color{blue}{\left(\frac{k}{n} \cdot \frac{0.5}{\pi}\right)}}^{-0.5} \]
  11. Simplified38.5%

    \[\leadsto \color{blue}{{\left(\frac{k}{n} \cdot \frac{0.5}{\pi}\right)}^{-0.5}} \]
  12. Final simplification38.5%

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

Alternative 7: 38.7% accurate, 1.5× speedup?

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

\\
{\left(\frac{0.5 \cdot k}{\pi \cdot n}\right)}^{-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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Step-by-step derivation
    1. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot \frac{2}{k}}} \]
    2. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\left(\pi \cdot n\right) \cdot 2}{k}}} \]
    3. metadata-eval37.8%

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

      \[\leadsto \sqrt{\frac{\color{blue}{\frac{\pi \cdot n}{0.5}}}{k}} \]
    5. associate-/r*37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5 \cdot k}}} \]
    6. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\pi \cdot n}{\color{blue}{k \cdot 0.5}}} \]
    7. clear-num37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    8. metadata-eval37.7%

      \[\leadsto \sqrt{\frac{\color{blue}{1 \cdot 1}}{\frac{k \cdot 0.5}{\pi \cdot n}}} \]
    9. add-sqr-sqrt37.7%

      \[\leadsto \sqrt{\frac{1 \cdot 1}{\color{blue}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}} \cdot \sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    10. frac-times37.7%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}} \cdot \frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    11. sqrt-unprod38.2%

      \[\leadsto \color{blue}{\sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \cdot \sqrt{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}}} \]
    12. add-sqr-sqrt38.5%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}}} \]
    13. inv-pow38.5%

      \[\leadsto \color{blue}{{\left(\sqrt{\frac{k \cdot 0.5}{\pi \cdot n}}\right)}^{-1}} \]
    14. sqrt-pow238.5%

      \[\leadsto \color{blue}{{\left(\frac{k \cdot 0.5}{\pi \cdot n}\right)}^{\left(\frac{-1}{2}\right)}} \]
  9. Applied egg-rr38.5%

    \[\leadsto \color{blue}{{\left(0.5 \cdot \frac{k}{\pi \cdot n}\right)}^{-0.5}} \]
  10. Step-by-step derivation
    1. associate-*r/38.5%

      \[\leadsto {\color{blue}{\left(\frac{0.5 \cdot k}{\pi \cdot n}\right)}}^{-0.5} \]
    2. *-commutative38.5%

      \[\leadsto {\left(\frac{\color{blue}{k \cdot 0.5}}{\pi \cdot n}\right)}^{-0.5} \]
    3. *-commutative38.5%

      \[\leadsto {\left(\frac{k \cdot 0.5}{\color{blue}{n \cdot \pi}}\right)}^{-0.5} \]
  11. Simplified38.5%

    \[\leadsto \color{blue}{{\left(\frac{k \cdot 0.5}{n \cdot \pi}\right)}^{-0.5}} \]
  12. Final simplification38.5%

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

Alternative 8: 37.9% 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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  9. Step-by-step derivation
    1. *-commutative37.8%

      \[\leadsto \sqrt{2 \cdot \frac{\color{blue}{\pi \cdot n}}{k}} \]
    2. associate-/l*37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\frac{\pi}{\frac{k}{n}}}} \]
  10. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{\pi}{\frac{k}{n}}}} \]
  11. Final simplification37.8%

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

Alternative 9: 37.8% accurate, 1.5× speedup?

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

\\
\sqrt{\pi \cdot \left(n \cdot \frac{2}{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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Final simplification37.8%

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

Alternative 10: 37.9% accurate, 1.5× speedup?

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

\\
\sqrt{\frac{n}{0.5 \cdot \frac{k}{\pi}}}
\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. Taylor expanded in k around 0 47.8%

    \[\leadsto \frac{1}{\sqrt{k}} \cdot \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right)} \]
  3. Step-by-step derivation
    1. *-commutative47.8%

      \[\leadsto \color{blue}{\left(\sqrt{n \cdot \pi} \cdot \sqrt{2}\right) \cdot \frac{1}{\sqrt{k}}} \]
    2. div-inv47.8%

      \[\leadsto \color{blue}{\frac{\sqrt{n \cdot \pi} \cdot \sqrt{2}}{\sqrt{k}}} \]
    3. sqrt-unprod47.9%

      \[\leadsto \frac{\color{blue}{\sqrt{\left(n \cdot \pi\right) \cdot 2}}}{\sqrt{k}} \]
    4. *-commutative47.9%

      \[\leadsto \frac{\sqrt{\color{blue}{2 \cdot \left(n \cdot \pi\right)}}}{\sqrt{k}} \]
    5. *-commutative47.9%

      \[\leadsto \frac{\sqrt{2 \cdot \color{blue}{\left(\pi \cdot n\right)}}}{\sqrt{k}} \]
    6. sqrt-undiv37.8%

      \[\leadsto \color{blue}{\sqrt{\frac{2 \cdot \left(\pi \cdot n\right)}{k}}} \]
    7. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(2 \cdot \pi\right) \cdot n}}{k}} \]
    8. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\left(\pi \cdot 2\right)} \cdot n}{k}} \]
    9. associate-*r*37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{\pi \cdot \left(2 \cdot n\right)}}{k}} \]
  4. Applied egg-rr37.8%

    \[\leadsto \color{blue}{\sqrt{\frac{\pi \cdot \left(2 \cdot n\right)}{k}}} \]
  5. Taylor expanded in n around 0 37.8%

    \[\leadsto \sqrt{\color{blue}{2 \cdot \frac{n \cdot \pi}{k}}} \]
  6. Step-by-step derivation
    1. associate-*l/37.8%

      \[\leadsto \sqrt{2 \cdot \color{blue}{\left(\frac{n}{k} \cdot \pi\right)}} \]
    2. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(2 \cdot \frac{n}{k}\right) \cdot \pi}} \]
    3. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{2 \cdot n}{k}} \cdot \pi} \]
    4. *-commutative37.8%

      \[\leadsto \sqrt{\color{blue}{\pi \cdot \frac{2 \cdot n}{k}}} \]
    5. *-commutative37.8%

      \[\leadsto \sqrt{\pi \cdot \frac{\color{blue}{n \cdot 2}}{k}} \]
    6. associate-*r/37.8%

      \[\leadsto \sqrt{\pi \cdot \color{blue}{\left(n \cdot \frac{2}{k}\right)}} \]
  7. Simplified37.8%

    \[\leadsto \sqrt{\color{blue}{\pi \cdot \left(n \cdot \frac{2}{k}\right)}} \]
  8. Step-by-step derivation
    1. associate-*r*37.8%

      \[\leadsto \sqrt{\color{blue}{\left(\pi \cdot n\right) \cdot \frac{2}{k}}} \]
    2. associate-*r/37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\left(\pi \cdot n\right) \cdot 2}{k}}} \]
    3. metadata-eval37.8%

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

      \[\leadsto \sqrt{\frac{\color{blue}{\frac{\pi \cdot n}{0.5}}}{k}} \]
    5. associate-/r*37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{\pi \cdot n}{0.5 \cdot k}}} \]
    6. *-commutative37.8%

      \[\leadsto \sqrt{\frac{\color{blue}{n \cdot \pi}}{0.5 \cdot k}} \]
    7. *-commutative37.8%

      \[\leadsto \sqrt{\frac{n \cdot \pi}{\color{blue}{k \cdot 0.5}}} \]
    8. associate-/l*37.8%

      \[\leadsto \sqrt{\color{blue}{\frac{n}{\frac{k \cdot 0.5}{\pi}}}} \]
    9. *-commutative37.8%

      \[\leadsto \sqrt{\frac{n}{\frac{\color{blue}{0.5 \cdot k}}{\pi}}} \]
    10. *-un-lft-identity37.8%

      \[\leadsto \sqrt{\frac{n}{\frac{0.5 \cdot k}{\color{blue}{1 \cdot \pi}}}} \]
    11. times-frac37.8%

      \[\leadsto \sqrt{\frac{n}{\color{blue}{\frac{0.5}{1} \cdot \frac{k}{\pi}}}} \]
    12. metadata-eval37.8%

      \[\leadsto \sqrt{\frac{n}{\color{blue}{0.5} \cdot \frac{k}{\pi}}} \]
  9. Applied egg-rr37.8%

    \[\leadsto \sqrt{\color{blue}{\frac{n}{0.5 \cdot \frac{k}{\pi}}}} \]
  10. Final simplification37.8%

    \[\leadsto \sqrt{\frac{n}{0.5 \cdot \frac{k}{\pi}}} \]

Reproduce

?
herbie shell --seed 2023307 
(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))))