2-ancestry mixing, positive discriminant

Percentage Accurate: 43.9% → 96.0%
Time: 9.2s
Alternatives: 3
Speedup: 3.9×

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 3 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: 43.9% 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: 96.0% accurate, 2.3× 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(cbrt(g) / Float64(-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 43.9%

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
  4. Applied rewrites95.3%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
  5. Step-by-step derivation
    1. lift-*.f64N/A

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

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

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

      \[\leadsto \frac{\sqrt[3]{g} \cdot \sqrt[3]{\frac{-1}{2} \cdot 2}}{\sqrt[3]{a}} \]
    5. metadata-evalN/A

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

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

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

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\mathsf{neg}\left(1\right)\right)}{\sqrt[3]{a}} \]
    9. metadata-eval96.0%

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{neg}\left(\sqrt[3]{g}\right)}{\sqrt[3]{a}} \]
    21. lower-neg.f6496.0%

      \[\leadsto \frac{-\sqrt[3]{g}}{\sqrt[3]{\color{blue}{a}}} \]
  6. Applied rewrites96.0%

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

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

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

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{g}}{\sqrt[3]{a}}\right) \]
    4. distribute-neg-frac2N/A

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

      \[\leadsto \frac{\sqrt[3]{g}}{\color{blue}{\mathsf{neg}\left(\sqrt[3]{a}\right)}} \]
    6. lower-neg.f6496.0%

      \[\leadsto \frac{\sqrt[3]{g}}{-\sqrt[3]{a}} \]
  8. Applied rewrites96.0%

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

Alternative 2: 73.5% accurate, 3.6× 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 43.9%

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
  4. Applied rewrites95.3%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
  5. Step-by-step derivation
    1. lift-/.f64N/A

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt[3]{\frac{-1}{2} \cdot 2}}{\sqrt[3]{a}} \cdot \sqrt[3]{g} \]
    9. metadata-evalN/A

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

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

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

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

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

      \[\leadsto \sqrt[3]{\frac{-1}{a} \cdot g} \]
    15. frac-2neg-revN/A

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

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

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

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

      \[\leadsto \sqrt[3]{\frac{-1}{a} \cdot g} \]
    20. lower-/.f6473.5%

      \[\leadsto \sqrt[3]{\frac{-1}{a} \cdot g} \]
  6. Applied rewrites73.5%

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

Alternative 3: 73.5% accurate, 3.9× 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 43.9%

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}} \]
  4. Applied rewrites95.3%

    \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
  5. Step-by-step derivation
    1. lift-/.f64N/A

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

      \[\leadsto \frac{\mathsf{neg}\left(\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)\right)}{\color{blue}{\mathsf{neg}\left(\sqrt[3]{a}\right)}} \]
    3. distribute-frac-negN/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \mathsf{neg}\left(\frac{\sqrt[3]{-1 \cdot g}}{\mathsf{neg}\left(\sqrt[3]{a}\right)}\right) \]
    21. mul-1-negN/A

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

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

      \[\leadsto \mathsf{neg}\left(\frac{\mathsf{neg}\left(\sqrt[3]{g}\right)}{\mathsf{neg}\left(\sqrt[3]{a}\right)}\right) \]
  6. Applied rewrites73.5%

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

Reproduce

?
herbie shell --seed 2025193 
(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))))))))