2-ancestry mixing, positive discriminant

Percentage Accurate: 43.7% → 97.9%
Time: 10.2s
Alternatives: 5
Speedup: 3.8×

Specification

?
\[\begin{array}{l} t_0 := \frac{1}{2 \cdot a}\\ t_1 := \sqrt{g \cdot g - h \cdot h}\\ \sqrt[3]{t\_0 \cdot \left(\left(-g\right) + t\_1\right)} + \sqrt[3]{t\_0 \cdot \left(\left(-g\right) - t\_1\right)} \end{array} \]
(FPCore (g h a)
 :precision binary64
 (let* ((t_0 (/ 1.0 (* 2.0 a))) (t_1 (sqrt (- (* g g) (* h h)))))
   (+ (cbrt (* t_0 (+ (- g) t_1))) (cbrt (* t_0 (- (- g) t_1))))))
double code(double g, double h, double a) {
	double t_0 = 1.0 / (2.0 * a);
	double t_1 = sqrt(((g * g) - (h * h)));
	return cbrt((t_0 * (-g + t_1))) + cbrt((t_0 * (-g - t_1)));
}
public static double code(double g, double h, double a) {
	double t_0 = 1.0 / (2.0 * a);
	double t_1 = Math.sqrt(((g * g) - (h * h)));
	return Math.cbrt((t_0 * (-g + t_1))) + Math.cbrt((t_0 * (-g - t_1)));
}
function code(g, h, a)
	t_0 = Float64(1.0 / Float64(2.0 * a))
	t_1 = sqrt(Float64(Float64(g * g) - Float64(h * h)))
	return Float64(cbrt(Float64(t_0 * Float64(Float64(-g) + t_1))) + cbrt(Float64(t_0 * Float64(Float64(-g) - t_1))))
end
code[g_, h_, a_] := Block[{t$95$0 = N[(1.0 / N[(2.0 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(g * g), $MachinePrecision] - N[(h * h), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[Power[N[(t$95$0 * N[((-g) + t$95$1), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[N[(t$95$0 * N[((-g) - t$95$1), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
t_0 := \frac{1}{2 \cdot a}\\
t_1 := \sqrt{g \cdot g - h \cdot h}\\
\sqrt[3]{t\_0 \cdot \left(\left(-g\right) + t\_1\right)} + \sqrt[3]{t\_0 \cdot \left(\left(-g\right) - t\_1\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 5 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: 43.7% accurate, 1.0× speedup?

\[\begin{array}{l} t_0 := \frac{1}{2 \cdot a}\\ t_1 := \sqrt{g \cdot g - h \cdot h}\\ \sqrt[3]{t\_0 \cdot \left(\left(-g\right) + t\_1\right)} + \sqrt[3]{t\_0 \cdot \left(\left(-g\right) - t\_1\right)} \end{array} \]
(FPCore (g h a)
 :precision binary64
 (let* ((t_0 (/ 1.0 (* 2.0 a))) (t_1 (sqrt (- (* g g) (* h h)))))
   (+ (cbrt (* t_0 (+ (- g) t_1))) (cbrt (* t_0 (- (- g) t_1))))))
double code(double g, double h, double a) {
	double t_0 = 1.0 / (2.0 * a);
	double t_1 = sqrt(((g * g) - (h * h)));
	return cbrt((t_0 * (-g + t_1))) + cbrt((t_0 * (-g - t_1)));
}
public static double code(double g, double h, double a) {
	double t_0 = 1.0 / (2.0 * a);
	double t_1 = Math.sqrt(((g * g) - (h * h)));
	return Math.cbrt((t_0 * (-g + t_1))) + Math.cbrt((t_0 * (-g - t_1)));
}
function code(g, h, a)
	t_0 = Float64(1.0 / Float64(2.0 * a))
	t_1 = sqrt(Float64(Float64(g * g) - Float64(h * h)))
	return Float64(cbrt(Float64(t_0 * Float64(Float64(-g) + t_1))) + cbrt(Float64(t_0 * Float64(Float64(-g) - t_1))))
end
code[g_, h_, a_] := Block[{t$95$0 = N[(1.0 / N[(2.0 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(g * g), $MachinePrecision] - N[(h * h), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[Power[N[(t$95$0 * N[((-g) + t$95$1), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[N[(t$95$0 * N[((-g) - t$95$1), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
t_0 := \frac{1}{2 \cdot a}\\
t_1 := \sqrt{g \cdot g - h \cdot h}\\
\sqrt[3]{t\_0 \cdot \left(\left(-g\right) + t\_1\right)} + \sqrt[3]{t\_0 \cdot \left(\left(-g\right) - t\_1\right)}
\end{array}

Alternative 1: 97.9% accurate, 0.7× speedup?

\[-\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{\left(\left|h\right|\right)}^{0.6666666666666666} \cdot \sqrt[3]{0.25}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
(FPCore (g h a)
 :precision binary64
 (-
  (+
   (/ (cbrt g) (cbrt a))
   (/
    (* (pow (fabs h) 0.6666666666666666) (cbrt 0.25))
    (* (cbrt a) (cbrt g))))))
double code(double g, double h, double a) {
	return -((cbrt(g) / cbrt(a)) + ((pow(fabs(h), 0.6666666666666666) * cbrt(0.25)) / (cbrt(a) * cbrt(g))));
}
public static double code(double g, double h, double a) {
	return -((Math.cbrt(g) / Math.cbrt(a)) + ((Math.pow(Math.abs(h), 0.6666666666666666) * Math.cbrt(0.25)) / (Math.cbrt(a) * Math.cbrt(g))));
}
function code(g, h, a)
	return Float64(-Float64(Float64(cbrt(g) / cbrt(a)) + Float64(Float64((abs(h) ^ 0.6666666666666666) * cbrt(0.25)) / Float64(cbrt(a) * cbrt(g)))))
end
code[g_, h_, a_] := (-N[(N[(N[Power[g, 1/3], $MachinePrecision] / N[Power[a, 1/3], $MachinePrecision]), $MachinePrecision] + N[(N[(N[Power[N[Abs[h], $MachinePrecision], 0.6666666666666666], $MachinePrecision] * N[Power[0.25, 1/3], $MachinePrecision]), $MachinePrecision] / N[(N[Power[a, 1/3], $MachinePrecision] * N[Power[g, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision])
-\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{\left(\left|h\right|\right)}^{0.6666666666666666} \cdot \sqrt[3]{0.25}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right)
Derivation
  1. Initial program 43.7%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites43.3%

    \[\leadsto \sqrt[3]{\color{blue}{\left(1 + \frac{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)}}{a + a}}{\frac{g}{-2 \cdot a}}\right) \cdot \frac{g}{-2 \cdot a}}} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  3. Taylor expanded in g around -inf

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} + -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}} \]
  4. Step-by-step derivation
    1. lower-fma.f64N/A

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

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\color{blue}{\sqrt[3]{a}}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    3. lower-*.f64N/A

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

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    5. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    6. lower-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    7. lower-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    8. lower-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    9. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{\frac{2}{3}} \cdot {\left(\sqrt[3]{\frac{1}{2}}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
  5. Applied rewrites48.4%

    \[\leadsto \color{blue}{\mathsf{fma}\left(-1, \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}, -1 \cdot \frac{{h}^{0.6666666666666666} \cdot {\left(\sqrt[3]{0.5}\right)}^{2}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right)} \]
  6. Applied rewrites35.9%

    \[\leadsto \color{blue}{-\mathsf{fma}\left(\sqrt[3]{\frac{0.25}{a \cdot g}}, {h}^{0.6666666666666666}, \sqrt[3]{\frac{g}{a}}\right)} \]
  7. Taylor expanded in g around 0

    \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
  8. Step-by-step derivation
    1. lower-+.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    2. lower-/.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    3. lower-cbrt.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    4. lower-cbrt.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    5. lower-/.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    6. lower-*.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    7. lower-pow.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    8. lower-cbrt.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    9. lower-*.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    10. lower-cbrt.f64N/A

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{\frac{2}{3}} \cdot \sqrt[3]{\frac{1}{4}}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
    11. lower-cbrt.f6448.8%

      \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{0.6666666666666666} \cdot \sqrt[3]{0.25}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
  9. Applied rewrites48.8%

    \[\leadsto -\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}} + \frac{{h}^{0.6666666666666666} \cdot \sqrt[3]{0.25}}{\sqrt[3]{a} \cdot \sqrt[3]{g}}\right) \]
  10. Add Preprocessing

Alternative 2: 95.8% accurate, 2.0× speedup?

\[\sqrt[3]{-0.5 \cdot g} \cdot \sqrt[3]{\frac{2}{a}} \]
(FPCore (g h a) :precision binary64 (* (cbrt (* -0.5 g)) (cbrt (/ 2.0 a))))
double code(double g, double h, double a) {
	return cbrt((-0.5 * g)) * cbrt((2.0 / a));
}
public static double code(double g, double h, double a) {
	return Math.cbrt((-0.5 * g)) * Math.cbrt((2.0 / a));
}
function code(g, h, a)
	return Float64(cbrt(Float64(-0.5 * g)) * cbrt(Float64(2.0 / a)))
end
code[g_, h_, a_] := N[(N[Power[N[(-0.5 * g), $MachinePrecision], 1/3], $MachinePrecision] * N[Power[N[(2.0 / a), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]
\sqrt[3]{-0.5 \cdot g} \cdot \sqrt[3]{\frac{2}{a}}
Derivation
  1. Initial program 43.7%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites49.6%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g} - \sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} + g}}{\sqrt[3]{a + a}}} \]
  3. Taylor expanded in g around inf

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lower-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
    4. lower-cbrt.f6495.8%

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}} \]
  5. Applied rewrites95.8%

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  6. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lift-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. associate-*r/N/A

      \[\leadsto \frac{-1 \cdot \sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot -1}{\sqrt[3]{\color{blue}{a}}} \]
    5. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\mathsf{neg}\left(1\right)\right)}{\sqrt[3]{a}} \]
    6. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\mathsf{neg}\left(\sqrt[3]{1}\right)\right)}{\sqrt[3]{a}} \]
    7. cbrt-neg-revN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{\mathsf{neg}\left(1\right)}}{\sqrt[3]{a}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{-1}}{\sqrt[3]{a}} \]
    9. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2} \cdot 2}}{\sqrt[3]{a}} \]
    10. cbrt-unprodN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    11. lift-cbrt.f64N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    12. lift-cbrt.f64N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    13. associate-*r*N/A

      \[\leadsto \frac{\left(\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2}}\right) \cdot \sqrt[3]{2}}{\sqrt[3]{\color{blue}{a}}} \]
    14. associate-/l*N/A

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

      \[\leadsto \left(\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2}}\right) \cdot \color{blue}{\frac{\sqrt[3]{2}}{\sqrt[3]{a}}} \]
    16. *-commutativeN/A

      \[\leadsto \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{g}\right) \cdot \frac{\color{blue}{\sqrt[3]{2}}}{\sqrt[3]{a}} \]
    17. lift-cbrt.f64N/A

      \[\leadsto \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{g}\right) \cdot \frac{\sqrt[3]{\color{blue}{2}}}{\sqrt[3]{a}} \]
    18. lift-cbrt.f64N/A

      \[\leadsto \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{g}\right) \cdot \frac{\sqrt[3]{2}}{\sqrt[3]{a}} \]
    19. cbrt-unprodN/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \frac{\color{blue}{\sqrt[3]{2}}}{\sqrt[3]{a}} \]
    20. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \frac{\color{blue}{\sqrt[3]{2}}}{\sqrt[3]{a}} \]
    21. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \frac{\sqrt[3]{\color{blue}{2}}}{\sqrt[3]{a}} \]
    22. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \frac{\sqrt[3]{2}}{\sqrt[3]{\color{blue}{a}}} \]
    23. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \frac{\sqrt[3]{2}}{\sqrt[3]{a}} \]
    24. cbrt-undivN/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \sqrt[3]{\frac{2}{a}} \]
    25. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{-1}{2} \cdot g} \cdot \sqrt[3]{\frac{2}{a}} \]
    26. lower-/.f6495.8%

      \[\leadsto \sqrt[3]{-0.5 \cdot g} \cdot \sqrt[3]{\frac{2}{a}} \]
  7. Applied rewrites95.8%

    \[\leadsto \sqrt[3]{-0.5 \cdot g} \cdot \color{blue}{\sqrt[3]{\frac{2}{a}}} \]
  8. Add Preprocessing

Alternative 3: 95.8% accurate, 2.2× speedup?

\[\frac{-\sqrt[3]{g}}{\sqrt[3]{a}} \]
(FPCore (g h a) :precision binary64 (/ (- (cbrt g)) (cbrt a)))
double code(double g, double h, double a) {
	return -cbrt(g) / cbrt(a);
}
public static double code(double g, double h, double a) {
	return -Math.cbrt(g) / Math.cbrt(a);
}
function code(g, h, a)
	return Float64(Float64(-cbrt(g)) / cbrt(a))
end
code[g_, h_, a_] := N[((-N[Power[g, 1/3], $MachinePrecision]) / N[Power[a, 1/3], $MachinePrecision]), $MachinePrecision]
\frac{-\sqrt[3]{g}}{\sqrt[3]{a}}
Derivation
  1. Initial program 43.7%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites49.6%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g} - \sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} + g}}{\sqrt[3]{a + a}}} \]
  3. Taylor expanded in g around inf

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lower-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
    4. lower-cbrt.f6495.8%

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}} \]
  5. Applied rewrites95.8%

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  6. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. mul-1-negN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    3. lift-/.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    4. mult-flipN/A

      \[\leadsto \mathsf{neg}\left(\sqrt[3]{g} \cdot \frac{1}{\sqrt[3]{a}}\right) \]
    5. associate-/l*N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot 1}{\sqrt[3]{a}}\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \sqrt[3]{1}}{\sqrt[3]{a}}\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \sqrt[3]{\frac{1}{2} \cdot 2}}{\sqrt[3]{a}}\right) \]
    8. cbrt-unprodN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    9. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    10. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    11. lift-*.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    12. lift-*.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    13. lift-/.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    14. lower-neg.f6495.1%

      \[\leadsto -\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    15. lift-/.f64N/A

      \[\leadsto -\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
  7. Applied rewrites73.6%

    \[\leadsto -\sqrt[3]{\frac{g}{a}} \]
  8. Step-by-step derivation
    1. lift-neg.f64N/A

      \[\leadsto \mathsf{neg}\left(\sqrt[3]{\frac{g}{a}}\right) \]
    2. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\sqrt[3]{\frac{g}{a}}\right) \]
    3. lift-/.f64N/A

      \[\leadsto \mathsf{neg}\left(\sqrt[3]{\frac{g}{a}}\right) \]
    4. cbrt-divN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    5. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    6. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    7. distribute-neg-fracN/A

      \[\leadsto \frac{\mathsf{neg}\left(\sqrt[3]{g}\right)}{\color{blue}{\sqrt[3]{a}}} \]
    8. lower-/.f64N/A

      \[\leadsto \frac{\mathsf{neg}\left(\sqrt[3]{g}\right)}{\color{blue}{\sqrt[3]{a}}} \]
    9. lower-neg.f6495.8%

      \[\leadsto \frac{-\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
  9. Applied rewrites95.8%

    \[\leadsto \frac{-\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
  10. Add Preprocessing

Alternative 4: 73.6% accurate, 3.5× speedup?

\[\sqrt[3]{\frac{-1}{a} \cdot g} \]
(FPCore (g h a) :precision binary64 (cbrt (* (/ -1.0 a) g)))
double code(double g, double h, double a) {
	return cbrt(((-1.0 / a) * g));
}
public static double code(double g, double h, double a) {
	return Math.cbrt(((-1.0 / a) * g));
}
function code(g, h, a)
	return cbrt(Float64(Float64(-1.0 / a) * g))
end
code[g_, h_, a_] := N[Power[N[(N[(-1.0 / a), $MachinePrecision] * g), $MachinePrecision], 1/3], $MachinePrecision]
\sqrt[3]{\frac{-1}{a} \cdot g}
Derivation
  1. Initial program 43.7%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites49.6%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g} - \sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} + g}}{\sqrt[3]{a + a}}} \]
  3. Taylor expanded in g around inf

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lower-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
    4. lower-cbrt.f6495.8%

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}} \]
  5. Applied rewrites95.8%

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  6. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lift-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. associate-*r/N/A

      \[\leadsto \frac{-1 \cdot \sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot -1}{\sqrt[3]{\color{blue}{a}}} \]
    5. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\mathsf{neg}\left(1\right)\right)}{\sqrt[3]{a}} \]
    6. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\mathsf{neg}\left(\sqrt[3]{1}\right)\right)}{\sqrt[3]{a}} \]
    7. cbrt-neg-revN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{\mathsf{neg}\left(1\right)}}{\sqrt[3]{a}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{-1}}{\sqrt[3]{a}} \]
    9. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2} \cdot 2}}{\sqrt[3]{a}} \]
    10. cbrt-unprodN/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    11. lift-cbrt.f64N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    12. lift-cbrt.f64N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    13. associate-*r*N/A

      \[\leadsto \frac{\left(\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2}}\right) \cdot \sqrt[3]{2}}{\sqrt[3]{\color{blue}{a}}} \]
    14. associate-*r*N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{\color{blue}{a}}} \]
    15. lift-*.f64N/A

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    16. associate-/l*N/A

      \[\leadsto \sqrt[3]{g} \cdot \color{blue}{\frac{\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}}{\sqrt[3]{a}}} \]
    17. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}}{\sqrt[3]{a}} \cdot \color{blue}{\sqrt[3]{g}} \]
  7. Applied rewrites73.6%

    \[\leadsto \sqrt[3]{\frac{-1}{a} \cdot g} \]
  8. Add Preprocessing

Alternative 5: 73.6% accurate, 3.8× speedup?

\[-\sqrt[3]{\frac{g}{a}} \]
(FPCore (g h a) :precision binary64 (- (cbrt (/ g a))))
double code(double g, double h, double a) {
	return -cbrt((g / a));
}
public static double code(double g, double h, double a) {
	return -Math.cbrt((g / a));
}
function code(g, h, a)
	return Float64(-cbrt(Float64(g / a)))
end
code[g_, h_, a_] := (-N[Power[N[(g / a), $MachinePrecision], 1/3], $MachinePrecision])
-\sqrt[3]{\frac{g}{a}}
Derivation
  1. Initial program 43.7%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites49.6%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g} - \sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} + g}}{\sqrt[3]{a + a}}} \]
  3. Taylor expanded in g around inf

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. lower-/.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
    4. lower-cbrt.f6495.8%

      \[\leadsto -1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}} \]
  5. Applied rewrites95.8%

    \[\leadsto \color{blue}{-1 \cdot \frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
  6. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto -1 \cdot \color{blue}{\frac{\sqrt[3]{g}}{\sqrt[3]{a}}} \]
    2. mul-1-negN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    3. lift-/.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    4. mult-flipN/A

      \[\leadsto \mathsf{neg}\left(\sqrt[3]{g} \cdot \frac{1}{\sqrt[3]{a}}\right) \]
    5. associate-/l*N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot 1}{\sqrt[3]{a}}\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \sqrt[3]{1}}{\sqrt[3]{a}}\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \sqrt[3]{\frac{1}{2} \cdot 2}}{\sqrt[3]{a}}\right) \]
    8. cbrt-unprodN/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    9. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    10. lift-cbrt.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    11. lift-*.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    12. lift-*.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    13. lift-/.f64N/A

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}\right) \]
    14. lower-neg.f6495.1%

      \[\leadsto -\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
    15. lift-/.f64N/A

      \[\leadsto -\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{1}{2}} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
  7. Applied rewrites73.6%

    \[\leadsto -\sqrt[3]{\frac{g}{a}} \]
  8. Add Preprocessing

Reproduce

?
herbie shell --seed 2025209 
(FPCore (g h a)
  :name "2-ancestry mixing, positive discriminant"
  :precision binary64
  (+ (cbrt (* (/ 1.0 (* 2.0 a)) (+ (- g) (sqrt (- (* g g) (* h h)))))) (cbrt (* (/ 1.0 (* 2.0 a)) (- (- g) (sqrt (- (* g g) (* h h))))))))