2-ancestry mixing, positive discriminant

Percentage Accurate: 44.3% → 96.0%
Time: 8.1s
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: 44.3% 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, 1.2× speedup?

\[\mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{g - g}{a + a}}\right) \]
(FPCore (g h a)
 :precision binary64
 (fma (cbrt (/ -0.5 a)) (cbrt (+ g g)) (cbrt (/ (- g g) (+ a a)))))
double code(double g, double h, double a) {
	return fma(cbrt((-0.5 / a)), cbrt((g + g)), cbrt(((g - g) / (a + a))));
}
function code(g, h, a)
	return fma(cbrt(Float64(-0.5 / a)), cbrt(Float64(g + g)), cbrt(Float64(Float64(g - g) / Float64(a + a))))
end
code[g_, h_, a_] := N[(N[Power[N[(-0.5 / a), $MachinePrecision], 1/3], $MachinePrecision] * N[Power[N[(g + g), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[N[(N[(g - g), $MachinePrecision] / N[(a + a), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]
\mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{g - g}{a + a}}\right)
Derivation
  1. Initial program 44.3%

    \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
  2. Applied rewrites47.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} + g}, \sqrt[3]{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g}{a + a}}\right)} \]
  3. Taylor expanded in g around inf

    \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{\color{blue}{g \cdot \left(1 + \frac{1}{2} \cdot \frac{h + -1 \cdot h}{g}\right)} + g}, \sqrt[3]{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g}{a + a}}\right) \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

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

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

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

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

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{\frac{-1}{2}}{a}}, \sqrt[3]{g \cdot \left(1 + \frac{1}{2} \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g}{a + a}}\right) \]
    6. lower-*.f6432.4%

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g}{a + a}}\right) \]
  5. Applied rewrites32.4%

    \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{\color{blue}{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right)} + g}, \sqrt[3]{\frac{\sqrt{\left(g - h\right) \cdot \left(h + g\right)} - g}{a + a}}\right) \]
  6. Taylor expanded in g around inf

    \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{\color{blue}{g \cdot \left(1 + \frac{1}{2} \cdot \frac{h + -1 \cdot h}{g}\right)} - g}{a + a}}\right) \]
  7. Step-by-step derivation
    1. lower-*.f64N/A

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

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

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

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

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{\frac{-1}{2}}{a}}, \sqrt[3]{g \cdot \left(1 + \frac{1}{2} \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{g \cdot \left(1 + \frac{1}{2} \cdot \frac{h + -1 \cdot h}{g}\right) - g}{a + a}}\right) \]
    6. lower-*.f6495.9%

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right) - g}{a + a}}\right) \]
  8. Applied rewrites95.9%

    \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right) + g}, \sqrt[3]{\frac{\color{blue}{g \cdot \left(1 + 0.5 \cdot \frac{h + -1 \cdot h}{g}\right)} - g}{a + a}}\right) \]
  9. Step-by-step derivation
    1. Applied rewrites95.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{\left(g + 0\right) + g}, \sqrt[3]{\frac{\left(g + 0\right) - g}{a + a}}\right)} \]
    2. Taylor expanded in g around 0

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{\left(g + 0\right) - g}{a + a}}\right) \]
    3. Step-by-step derivation
      1. Applied rewrites95.9%

        \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{\left(g + 0\right) - g}{a + a}}\right) \]
      2. Taylor expanded in g around 0

        \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{g - g}{a + a}}\right) \]
      3. Step-by-step derivation
        1. Applied rewrites95.9%

          \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{-0.5}{a}}, \sqrt[3]{g + g}, \sqrt[3]{\frac{g - g}{a + a}}\right) \]
        2. Add Preprocessing

        Alternative 2: 96.0% accurate, 2.0× speedup?

        \[\frac{1}{\frac{\sqrt[3]{a}}{-\sqrt[3]{g}}} \]
        (FPCore (g h a) :precision binary64 (/ 1.0 (/ (cbrt a) (- (cbrt g)))))
        double code(double g, double h, double a) {
        	return 1.0 / (cbrt(a) / -cbrt(g));
        }
        
        public static double code(double g, double h, double a) {
        	return 1.0 / (Math.cbrt(a) / -Math.cbrt(g));
        }
        
        function code(g, h, a)
        	return Float64(1.0 / Float64(cbrt(a) / Float64(-cbrt(g))))
        end
        
        code[g_, h_, a_] := N[(1.0 / N[(N[Power[a, 1/3], $MachinePrecision] / (-N[Power[g, 1/3], $MachinePrecision])), $MachinePrecision]), $MachinePrecision]
        
        \frac{1}{\frac{\sqrt[3]{a}}{-\sqrt[3]{g}}}
        
        Derivation
        1. Initial program 44.3%

          \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
        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.f6495.4%

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

          \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
        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. div-flipN/A

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

            \[\leadsto \frac{1}{\color{blue}{\frac{\sqrt[3]{a}}{\sqrt[3]{g} \cdot \left(\sqrt[3]{\frac{-1}{2}} \cdot \sqrt[3]{2}\right)}}} \]
          4. lower-unsound-/.f6495.3%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \frac{1}{\frac{\sqrt[3]{a}}{\mathsf{neg}\left(\sqrt[3]{g}\right)}} \]
          25. lower-neg.f6496.0%

            \[\leadsto \frac{1}{\frac{\sqrt[3]{a}}{-\sqrt[3]{g}}} \]
        6. Applied rewrites96.0%

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

        Alternative 3: 95.9% 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 44.3%

          \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
        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.f6495.4%

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

          \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
        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%

          \[\leadsto \frac{-\sqrt[3]{g}}{\color{blue}{\sqrt[3]{a}}} \]
        7. 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 44.3%

          \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
        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.f6495.4%

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

          \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
        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-/.f6473.6%

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

          \[\leadsto \sqrt[3]{\frac{-1}{a} \cdot g} \]
        7. 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 44.3%

          \[\sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) + \sqrt{g \cdot g - h \cdot h}\right)} + \sqrt[3]{\frac{1}{2 \cdot a} \cdot \left(\left(-g\right) - \sqrt{g \cdot g - h \cdot h}\right)} \]
        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.f6495.4%

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

          \[\leadsto \color{blue}{\frac{\sqrt[3]{g} \cdot \left(\sqrt[3]{-0.5} \cdot \sqrt[3]{2}\right)}{\sqrt[3]{a}}} \]
        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 rewrites73.6%

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

        Reproduce

        ?
        herbie shell --seed 2025201 
        (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))))))))