Falkner and Boettcher, Equation (22+)

Percentage Accurate: 98.5% → 100.0%
Time: 1.6s
Alternatives: 6
Speedup: 3.1×

Specification

?
\[\begin{array}{l} \\ \frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ 4.0 (* (* (* 3.0 PI) (- 1.0 (* v v))) (sqrt (- 2.0 (* 6.0 (* v v)))))))
double code(double v) {
	return 4.0 / (((3.0 * ((double) M_PI)) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v)))));
}
public static double code(double v) {
	return 4.0 / (((3.0 * Math.PI) * (1.0 - (v * v))) * Math.sqrt((2.0 - (6.0 * (v * v)))));
}
def code(v):
	return 4.0 / (((3.0 * math.pi) * (1.0 - (v * v))) * math.sqrt((2.0 - (6.0 * (v * v)))))
function code(v)
	return Float64(4.0 / Float64(Float64(Float64(3.0 * pi) * Float64(1.0 - Float64(v * v))) * sqrt(Float64(2.0 - Float64(6.0 * Float64(v * v))))))
end
function tmp = code(v)
	tmp = 4.0 / (((3.0 * pi) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v)))));
end
code[v_] := N[(4.0 / N[(N[(N[(3.0 * Pi), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(2.0 - N[(6.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}
\end{array}

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 6 alternatives:

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

Initial Program: 98.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ 4.0 (* (* (* 3.0 PI) (- 1.0 (* v v))) (sqrt (- 2.0 (* 6.0 (* v v)))))))
double code(double v) {
	return 4.0 / (((3.0 * ((double) M_PI)) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v)))));
}
public static double code(double v) {
	return 4.0 / (((3.0 * Math.PI) * (1.0 - (v * v))) * Math.sqrt((2.0 - (6.0 * (v * v)))));
}
def code(v):
	return 4.0 / (((3.0 * math.pi) * (1.0 - (v * v))) * math.sqrt((2.0 - (6.0 * (v * v)))))
function code(v)
	return Float64(4.0 / Float64(Float64(Float64(3.0 * pi) * Float64(1.0 - Float64(v * v))) * sqrt(Float64(2.0 - Float64(6.0 * Float64(v * v))))))
end
function tmp = code(v)
	tmp = 4.0 / (((3.0 * pi) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v)))));
end
code[v_] := N[(4.0 / N[(N[(N[(3.0 * Pi), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(2.0 - N[(6.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}
\end{array}

Alternative 1: 100.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ (/ 4.0 (* (- 1.0 (* v v)) (* PI 3.0))) (sqrt (fma -6.0 (* v v) 2.0))))
double code(double v) {
	return (4.0 / ((1.0 - (v * v)) * (((double) M_PI) * 3.0))) / sqrt(fma(-6.0, (v * v), 2.0));
}
function code(v)
	return Float64(Float64(4.0 / Float64(Float64(1.0 - Float64(v * v)) * Float64(pi * 3.0))) / sqrt(fma(-6.0, Float64(v * v), 2.0)))
end
code[v_] := N[(N[(4.0 / N[(N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision] * N[(Pi * 3.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(-6.0 * N[(v * v), $MachinePrecision] + 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}
\end{array}
Derivation
  1. Initial program 98.5%

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    3. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    4. lift-PI.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    5. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\color{blue}{\left(3 \cdot \mathsf{PI}\left(\right)\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    6. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{\left(1 - v \cdot v\right)}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    7. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - \color{blue}{v \cdot v}\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    8. lift-sqrt.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \color{blue}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    9. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\color{blue}{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    10. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - \color{blue}{6 \cdot \left(v \cdot v\right)}}} \]
    11. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    12. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    13. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
  3. Applied rewrites100.0%

    \[\leadsto \color{blue}{\frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
  4. Add Preprocessing

Alternative 2: 99.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, 1.3333333333333333, \frac{1.3333333333333333}{\pi}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/
  (fma (/ (* v v) PI) 1.3333333333333333 (/ 1.3333333333333333 PI))
  (sqrt (fma -6.0 (* v v) 2.0))))
double code(double v) {
	return fma(((v * v) / ((double) M_PI)), 1.3333333333333333, (1.3333333333333333 / ((double) M_PI))) / sqrt(fma(-6.0, (v * v), 2.0));
}
function code(v)
	return Float64(fma(Float64(Float64(v * v) / pi), 1.3333333333333333, Float64(1.3333333333333333 / pi)) / sqrt(fma(-6.0, Float64(v * v), 2.0)))
end
code[v_] := N[(N[(N[(N[(v * v), $MachinePrecision] / Pi), $MachinePrecision] * 1.3333333333333333 + N[(1.3333333333333333 / Pi), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(-6.0 * N[(v * v), $MachinePrecision] + 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, 1.3333333333333333, \frac{1.3333333333333333}{\pi}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}
\end{array}
Derivation
  1. Initial program 98.5%

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    3. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    4. lift-PI.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    5. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\color{blue}{\left(3 \cdot \mathsf{PI}\left(\right)\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    6. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{\left(1 - v \cdot v\right)}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    7. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - \color{blue}{v \cdot v}\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    8. lift-sqrt.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \color{blue}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    9. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\color{blue}{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    10. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - \color{blue}{6 \cdot \left(v \cdot v\right)}}} \]
    11. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    12. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    13. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
  3. Applied rewrites100.0%

    \[\leadsto \color{blue}{\frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
  4. Taylor expanded in v around 0

    \[\leadsto \frac{\color{blue}{\frac{4}{3} \cdot \frac{{v}^{2}}{\mathsf{PI}\left(\right)} + \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  5. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \frac{\frac{{v}^{2}}{\mathsf{PI}\left(\right)} \cdot \frac{4}{3} + \color{blue}{\frac{4}{3}} \cdot \frac{1}{\mathsf{PI}\left(\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    2. lower-fma.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{{v}^{2}}{\mathsf{PI}\left(\right)}, \color{blue}{\frac{4}{3}}, \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    3. lower-/.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{{v}^{2}}{\mathsf{PI}\left(\right)}, \frac{4}{3}, \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    4. pow2N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\mathsf{PI}\left(\right)}, \frac{4}{3}, \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    5. lift-*.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\mathsf{PI}\left(\right)}, \frac{4}{3}, \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    6. lift-PI.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, \frac{4}{3}, \frac{4}{3} \cdot \frac{1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    7. associate-*r/N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, \frac{4}{3}, \frac{\frac{4}{3} \cdot 1}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, \frac{4}{3}, \frac{\frac{4}{3}}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    9. lower-/.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, \frac{4}{3}, \frac{\frac{4}{3}}{\mathsf{PI}\left(\right)}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    10. lift-PI.f6499.5

      \[\leadsto \frac{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, 1.3333333333333333, \frac{1.3333333333333333}{\pi}\right)}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  6. Applied rewrites99.5%

    \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(\frac{v \cdot v}{\pi}, 1.3333333333333333, \frac{1.3333333333333333}{\pi}\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  7. Add Preprocessing

Alternative 3: 99.0% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \frac{\frac{4}{\pi \cdot 3}}{\sqrt{\mathsf{fma}\left(-6 \cdot v, v, 2\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ (/ 4.0 (* PI 3.0)) (sqrt (fma (* -6.0 v) v 2.0))))
double code(double v) {
	return (4.0 / (((double) M_PI) * 3.0)) / sqrt(fma((-6.0 * v), v, 2.0));
}
function code(v)
	return Float64(Float64(4.0 / Float64(pi * 3.0)) / sqrt(fma(Float64(-6.0 * v), v, 2.0)))
end
code[v_] := N[(N[(4.0 / N[(Pi * 3.0), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[(-6.0 * v), $MachinePrecision] * v + 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\frac{4}{\pi \cdot 3}}{\sqrt{\mathsf{fma}\left(-6 \cdot v, v, 2\right)}}
\end{array}
Derivation
  1. Initial program 98.5%

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Taylor expanded in v around 0

    \[\leadsto \frac{4}{\color{blue}{\left(3 \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \frac{4}{\left(\mathsf{PI}\left(\right) \cdot \color{blue}{3}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    2. lower-*.f64N/A

      \[\leadsto \frac{4}{\left(\mathsf{PI}\left(\right) \cdot \color{blue}{3}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    3. lift-PI.f6497.5

      \[\leadsto \frac{4}{\left(\pi \cdot 3\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  4. Applied rewrites97.5%

    \[\leadsto \frac{4}{\color{blue}{\left(\pi \cdot 3\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  5. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{4}{\left(\pi \cdot 3\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\pi \cdot 3\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    3. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    4. lift-sqrt.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\color{blue}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    5. lift--.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{\color{blue}{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    6. lift-*.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 - \color{blue}{6 \cdot \left(v \cdot v\right)}}} \]
    7. lift-*.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 - 6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    8. pow2N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 - 6 \cdot \color{blue}{{v}^{2}}}} \]
    9. fp-cancel-sub-sign-invN/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{\color{blue}{2 + \left(\mathsf{neg}\left(6\right)\right) \cdot {v}^{2}}}} \]
    10. metadata-evalN/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 + \color{blue}{-6} \cdot {v}^{2}}} \]
    11. pow2N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 + -6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    12. lift-*.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{2 + -6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    13. +-commutativeN/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{\color{blue}{-6 \cdot \left(v \cdot v\right) + 2}}} \]
    14. lift-*.f64N/A

      \[\leadsto \frac{\frac{4}{\pi \cdot 3}}{\sqrt{-6 \cdot \color{blue}{\left(v \cdot v\right)} + 2}} \]
  6. Applied rewrites99.0%

    \[\leadsto \color{blue}{\frac{\frac{4}{\pi \cdot 3}}{\sqrt{\mathsf{fma}\left(-6 \cdot v, v, 2\right)}}} \]
  7. Add Preprocessing

Alternative 4: 99.0% accurate, 1.7× speedup?

\[\begin{array}{l} \\ \frac{\frac{1.3333333333333333}{\pi}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ (/ 1.3333333333333333 PI) (sqrt (fma -6.0 (* v v) 2.0))))
double code(double v) {
	return (1.3333333333333333 / ((double) M_PI)) / sqrt(fma(-6.0, (v * v), 2.0));
}
function code(v)
	return Float64(Float64(1.3333333333333333 / pi) / sqrt(fma(-6.0, Float64(v * v), 2.0)))
end
code[v_] := N[(N[(1.3333333333333333 / Pi), $MachinePrecision] / N[Sqrt[N[(-6.0 * N[(v * v), $MachinePrecision] + 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\frac{1.3333333333333333}{\pi}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}
\end{array}
Derivation
  1. Initial program 98.5%

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    3. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    4. lift-PI.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    5. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\color{blue}{\left(3 \cdot \mathsf{PI}\left(\right)\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    6. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{\left(1 - v \cdot v\right)}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    7. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - \color{blue}{v \cdot v}\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    8. lift-sqrt.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \color{blue}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    9. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\color{blue}{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    10. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - \color{blue}{6 \cdot \left(v \cdot v\right)}}} \]
    11. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    12. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    13. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
  3. Applied rewrites100.0%

    \[\leadsto \color{blue}{\frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
  4. Taylor expanded in v around 0

    \[\leadsto \frac{\color{blue}{\frac{\frac{4}{3}}{\mathsf{PI}\left(\right)}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  5. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\frac{\frac{4}{3}}{\color{blue}{\mathsf{PI}\left(\right)}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    2. lift-PI.f6499.0

      \[\leadsto \frac{\frac{1.3333333333333333}{\pi}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  6. Applied rewrites99.0%

    \[\leadsto \frac{\color{blue}{\frac{1.3333333333333333}{\pi}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  7. Add Preprocessing

Alternative 5: 99.0% accurate, 3.1× speedup?

\[\begin{array}{l} \\ \frac{\frac{1.3333333333333333}{\pi}}{\sqrt{2}} \end{array} \]
(FPCore (v) :precision binary64 (/ (/ 1.3333333333333333 PI) (sqrt 2.0)))
double code(double v) {
	return (1.3333333333333333 / ((double) M_PI)) / sqrt(2.0);
}
public static double code(double v) {
	return (1.3333333333333333 / Math.PI) / Math.sqrt(2.0);
}
def code(v):
	return (1.3333333333333333 / math.pi) / math.sqrt(2.0)
function code(v)
	return Float64(Float64(1.3333333333333333 / pi) / sqrt(2.0))
end
function tmp = code(v)
	tmp = (1.3333333333333333 / pi) / sqrt(2.0);
end
code[v_] := N[(N[(1.3333333333333333 / Pi), $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\frac{1.3333333333333333}{\pi}}{\sqrt{2}}
\end{array}
Derivation
  1. Initial program 98.5%

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    3. lift-*.f64N/A

      \[\leadsto \frac{4}{\color{blue}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right)} \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    4. lift-PI.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    5. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\color{blue}{\left(3 \cdot \mathsf{PI}\left(\right)\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    6. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{\left(1 - v \cdot v\right)}\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    7. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - \color{blue}{v \cdot v}\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    8. lift-sqrt.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \color{blue}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    9. lift--.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\color{blue}{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    10. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - \color{blue}{6 \cdot \left(v \cdot v\right)}}} \]
    11. lift-*.f64N/A

      \[\leadsto \frac{4}{\left(\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \color{blue}{\left(v \cdot v\right)}}} \]
    12. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
    13. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{\frac{4}{\left(3 \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)}}{\sqrt{2 - 6 \cdot \left(v \cdot v\right)}}} \]
  3. Applied rewrites100.0%

    \[\leadsto \color{blue}{\frac{\frac{4}{\left(1 - v \cdot v\right) \cdot \left(\pi \cdot 3\right)}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
  4. Taylor expanded in v around 0

    \[\leadsto \frac{\color{blue}{\frac{\frac{4}{3}}{\mathsf{PI}\left(\right)}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  5. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\frac{\frac{4}{3}}{\color{blue}{\mathsf{PI}\left(\right)}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
    2. lift-PI.f6499.0

      \[\leadsto \frac{\frac{1.3333333333333333}{\pi}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  6. Applied rewrites99.0%

    \[\leadsto \frac{\color{blue}{\frac{1.3333333333333333}{\pi}}}{\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
  7. Taylor expanded in v around 0

    \[\leadsto \frac{\frac{\frac{4}{3}}{\pi}}{\sqrt{\color{blue}{2}}} \]
  8. Step-by-step derivation
    1. Applied rewrites99.0%

      \[\leadsto \frac{\frac{1.3333333333333333}{\pi}}{\sqrt{\color{blue}{2}}} \]
    2. Add Preprocessing

    Alternative 6: 97.5% accurate, 3.2× speedup?

    \[\begin{array}{l} \\ \frac{\sqrt{0.5}}{\pi} \cdot 1.3333333333333333 \end{array} \]
    (FPCore (v) :precision binary64 (* (/ (sqrt 0.5) PI) 1.3333333333333333))
    double code(double v) {
    	return (sqrt(0.5) / ((double) M_PI)) * 1.3333333333333333;
    }
    
    public static double code(double v) {
    	return (Math.sqrt(0.5) / Math.PI) * 1.3333333333333333;
    }
    
    def code(v):
    	return (math.sqrt(0.5) / math.pi) * 1.3333333333333333
    
    function code(v)
    	return Float64(Float64(sqrt(0.5) / pi) * 1.3333333333333333)
    end
    
    function tmp = code(v)
    	tmp = (sqrt(0.5) / pi) * 1.3333333333333333;
    end
    
    code[v_] := N[(N[(N[Sqrt[0.5], $MachinePrecision] / Pi), $MachinePrecision] * 1.3333333333333333), $MachinePrecision]
    
    \begin{array}{l}
    
    \\
    \frac{\sqrt{0.5}}{\pi} \cdot 1.3333333333333333
    \end{array}
    
    Derivation
    1. Initial program 98.5%

      \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
    2. Taylor expanded in v around 0

      \[\leadsto \color{blue}{\frac{4}{3} \cdot \frac{\sqrt{\frac{1}{2}}}{\mathsf{PI}\left(\right)}} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\sqrt{\frac{1}{2}}}{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{4}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\sqrt{\frac{1}{2}}}{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{4}{3}} \]
      3. lower-/.f64N/A

        \[\leadsto \frac{\sqrt{\frac{1}{2}}}{\mathsf{PI}\left(\right)} \cdot \frac{4}{3} \]
      4. lower-sqrt.f64N/A

        \[\leadsto \frac{\sqrt{\frac{1}{2}}}{\mathsf{PI}\left(\right)} \cdot \frac{4}{3} \]
      5. lift-PI.f6497.5

        \[\leadsto \frac{\sqrt{0.5}}{\pi} \cdot 1.3333333333333333 \]
    4. Applied rewrites97.5%

      \[\leadsto \color{blue}{\frac{\sqrt{0.5}}{\pi} \cdot 1.3333333333333333} \]
    5. Add Preprocessing

    Reproduce

    ?
    herbie shell --seed 2025131 
    (FPCore (v)
      :name "Falkner and Boettcher, Equation (22+)"
      :precision binary64
      (/ 4.0 (* (* (* 3.0 PI) (- 1.0 (* v v))) (sqrt (- 2.0 (* 6.0 (* v v)))))))