Falkner and Boettcher, Appendix B, 2

Percentage Accurate: 100.0% → 100.0%
Time: 7.4s
Alternatives: 5
Speedup: 1.9×

Specification

?
\[\begin{array}{l} \\ \left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \end{array} \]
(FPCore (v)
 :precision binary64
 (* (* (/ (sqrt 2.0) 4.0) (sqrt (- 1.0 (* 3.0 (* v v))))) (- 1.0 (* v v))))
double code(double v) {
	return ((sqrt(2.0) / 4.0) * sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = ((sqrt(2.0d0) / 4.0d0) * sqrt((1.0d0 - (3.0d0 * (v * v))))) * (1.0d0 - (v * v))
end function
public static double code(double v) {
	return ((Math.sqrt(2.0) / 4.0) * Math.sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
}
def code(v):
	return ((math.sqrt(2.0) / 4.0) * math.sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v))
function code(v)
	return Float64(Float64(Float64(sqrt(2.0) / 4.0) * sqrt(Float64(1.0 - Float64(3.0 * Float64(v * v))))) * Float64(1.0 - Float64(v * v)))
end
function tmp = code(v)
	tmp = ((sqrt(2.0) / 4.0) * sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
end
code[v_] := N[(N[(N[(N[Sqrt[2.0], $MachinePrecision] / 4.0), $MachinePrecision] * N[Sqrt[N[(1.0 - N[(3.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

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

Sampling outcomes in binary64 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 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: 100.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \end{array} \]
(FPCore (v)
 :precision binary64
 (* (* (/ (sqrt 2.0) 4.0) (sqrt (- 1.0 (* 3.0 (* v v))))) (- 1.0 (* v v))))
double code(double v) {
	return ((sqrt(2.0) / 4.0) * sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = ((sqrt(2.0d0) / 4.0d0) * sqrt((1.0d0 - (3.0d0 * (v * v))))) * (1.0d0 - (v * v))
end function
public static double code(double v) {
	return ((Math.sqrt(2.0) / 4.0) * Math.sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
}
def code(v):
	return ((math.sqrt(2.0) / 4.0) * math.sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v))
function code(v)
	return Float64(Float64(Float64(sqrt(2.0) / 4.0) * sqrt(Float64(1.0 - Float64(3.0 * Float64(v * v))))) * Float64(1.0 - Float64(v * v)))
end
function tmp = code(v)
	tmp = ((sqrt(2.0) / 4.0) * sqrt((1.0 - (3.0 * (v * v))))) * (1.0 - (v * v));
end
code[v_] := N[(N[(N[(N[Sqrt[2.0], $MachinePrecision] / 4.0), $MachinePrecision] * N[Sqrt[N[(1.0 - N[(3.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

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

Alternative 1: 100.0% accurate, 1.7× speedup?

\[\begin{array}{l} \\ \frac{\left(1 - v \cdot \left(v \cdot \left(v \cdot v\right)\right)\right) \cdot \sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\left(1 + v \cdot v\right) \cdot 4} \end{array} \]
(FPCore (v)
 :precision binary64
 (/
  (* (- 1.0 (* v (* v (* v v)))) (sqrt (+ 2.0 (* (* v v) -6.0))))
  (* (+ 1.0 (* v v)) 4.0)))
double code(double v) {
	return ((1.0 - (v * (v * (v * v)))) * sqrt((2.0 + ((v * v) * -6.0)))) / ((1.0 + (v * v)) * 4.0);
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = ((1.0d0 - (v * (v * (v * v)))) * sqrt((2.0d0 + ((v * v) * (-6.0d0))))) / ((1.0d0 + (v * v)) * 4.0d0)
end function
public static double code(double v) {
	return ((1.0 - (v * (v * (v * v)))) * Math.sqrt((2.0 + ((v * v) * -6.0)))) / ((1.0 + (v * v)) * 4.0);
}
def code(v):
	return ((1.0 - (v * (v * (v * v)))) * math.sqrt((2.0 + ((v * v) * -6.0)))) / ((1.0 + (v * v)) * 4.0)
function code(v)
	return Float64(Float64(Float64(1.0 - Float64(v * Float64(v * Float64(v * v)))) * sqrt(Float64(2.0 + Float64(Float64(v * v) * -6.0)))) / Float64(Float64(1.0 + Float64(v * v)) * 4.0))
end
function tmp = code(v)
	tmp = ((1.0 - (v * (v * (v * v)))) * sqrt((2.0 + ((v * v) * -6.0)))) / ((1.0 + (v * v)) * 4.0);
end
code[v_] := N[(N[(N[(1.0 - N[(v * N[(v * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(2.0 + N[(N[(v * v), $MachinePrecision] * -6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(N[(1.0 + N[(v * v), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\left(1 - v \cdot \left(v \cdot \left(v \cdot v\right)\right)\right) \cdot \sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\left(1 + v \cdot v\right) \cdot 4}
\end{array}
Derivation
  1. Initial program 100.0%

    \[\left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. *-commutativeN/A

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

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}{\color{blue}{4}} \]
    3. clear-numN/A

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{1}{\color{blue}{\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}}} \]
    4. un-div-invN/A

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

      \[\leadsto \mathsf{/.f64}\left(\left(1 - v \cdot v\right), \color{blue}{\left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)}\right) \]
    6. --lowering--.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \left(v \cdot v\right)\right), \left(\frac{\color{blue}{4}}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    8. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \color{blue}{\left(\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right)}\right)\right) \]
    9. sqrt-unprodN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)\right)\right) \]
    10. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 + \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    13. +-lowering-+.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    14. *-commutativeN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(\left(v \cdot v\right) \cdot 3\right)\right)\right)\right)\right)\right)\right) \]
    15. distribute-rgt-neg-inN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\left(v \cdot v\right) \cdot \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    16. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(v \cdot v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    17. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    18. metadata-eval100.0%

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), -3\right)\right)\right)\right)\right)\right) \]
  4. Applied egg-rr100.0%

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

      \[\leadsto \left(1 - v \cdot v\right) \cdot \color{blue}{\frac{1}{\frac{4}{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}}} \]
    2. flip--N/A

      \[\leadsto \frac{1 \cdot 1 - \left(v \cdot v\right) \cdot \left(v \cdot v\right)}{1 + v \cdot v} \cdot \frac{\color{blue}{1}}{\frac{4}{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}} \]
    3. clear-numN/A

      \[\leadsto \frac{1 \cdot 1 - \left(v \cdot v\right) \cdot \left(v \cdot v\right)}{1 + v \cdot v} \cdot \frac{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}{\color{blue}{4}} \]
    4. frac-timesN/A

      \[\leadsto \frac{\left(1 \cdot 1 - \left(v \cdot v\right) \cdot \left(v \cdot v\right)\right) \cdot \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}{\color{blue}{\left(1 + v \cdot v\right) \cdot 4}} \]
    5. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\left(\left(1 \cdot 1 - \left(v \cdot v\right) \cdot \left(v \cdot v\right)\right) \cdot \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}\right), \color{blue}{\left(\left(1 + v \cdot v\right) \cdot 4\right)}\right) \]
  6. Applied egg-rr100.0%

    \[\leadsto \color{blue}{\frac{\left(1 - v \cdot \left(v \cdot \left(v \cdot v\right)\right)\right) \cdot \sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\left(1 + v \cdot v\right) \cdot 4}} \]
  7. Add Preprocessing

Alternative 2: 100.0% accurate, 1.9× speedup?

\[\begin{array}{l} \\ \frac{1 - v \cdot v}{\frac{4}{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ (- 1.0 (* v v)) (/ 4.0 (sqrt (+ 2.0 (* (* v v) -6.0))))))
double code(double v) {
	return (1.0 - (v * v)) / (4.0 / sqrt((2.0 + ((v * v) * -6.0))));
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = (1.0d0 - (v * v)) / (4.0d0 / sqrt((2.0d0 + ((v * v) * (-6.0d0)))))
end function
public static double code(double v) {
	return (1.0 - (v * v)) / (4.0 / Math.sqrt((2.0 + ((v * v) * -6.0))));
}
def code(v):
	return (1.0 - (v * v)) / (4.0 / math.sqrt((2.0 + ((v * v) * -6.0))))
function code(v)
	return Float64(Float64(1.0 - Float64(v * v)) / Float64(4.0 / sqrt(Float64(2.0 + Float64(Float64(v * v) * -6.0)))))
end
function tmp = code(v)
	tmp = (1.0 - (v * v)) / (4.0 / sqrt((2.0 + ((v * v) * -6.0))));
end
code[v_] := N[(N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision] / N[(4.0 / N[Sqrt[N[(2.0 + N[(N[(v * v), $MachinePrecision] * -6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{1 - v \cdot v}{\frac{4}{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}}
\end{array}
Derivation
  1. Initial program 100.0%

    \[\left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. *-commutativeN/A

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

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}{\color{blue}{4}} \]
    3. clear-numN/A

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{1}{\color{blue}{\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}}} \]
    4. un-div-invN/A

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

      \[\leadsto \mathsf{/.f64}\left(\left(1 - v \cdot v\right), \color{blue}{\left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)}\right) \]
    6. --lowering--.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \left(v \cdot v\right)\right), \left(\frac{\color{blue}{4}}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    8. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \color{blue}{\left(\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right)}\right)\right) \]
    9. sqrt-unprodN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)\right)\right) \]
    10. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 + \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    13. +-lowering-+.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    14. *-commutativeN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(\left(v \cdot v\right) \cdot 3\right)\right)\right)\right)\right)\right)\right) \]
    15. distribute-rgt-neg-inN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\left(v \cdot v\right) \cdot \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    16. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(v \cdot v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    17. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    18. metadata-eval100.0%

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), -3\right)\right)\right)\right)\right)\right) \]
  4. Applied egg-rr100.0%

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

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(\left(v \cdot v\right) \cdot -3 + 1\right)\right)\right)\right)\right) \]
    2. distribute-lft-inN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(\left(v \cdot v\right) \cdot -3\right) + 2 \cdot 1\right)\right)\right)\right) \]
    3. metadata-evalN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(\left(v \cdot v\right) \cdot -3\right) + 2\right)\right)\right)\right) \]
    4. +-lowering-+.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\left(2 \cdot \left(\left(v \cdot v\right) \cdot -3\right)\right), 2\right)\right)\right)\right) \]
    5. *-commutativeN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\left(\left(\left(v \cdot v\right) \cdot -3\right) \cdot 2\right), 2\right)\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\left(\left(v \cdot v\right) \cdot \left(-3 \cdot 2\right)\right), 2\right)\right)\right)\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\left(\left(v \cdot v\right) \cdot -6\right), 2\right)\right)\right)\right) \]
    8. metadata-evalN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\left(\left(v \cdot v\right) \cdot \left(2 \cdot -3\right)\right), 2\right)\right)\right)\right) \]
    9. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\left(v \cdot v\right), \left(2 \cdot -3\right)\right), 2\right)\right)\right)\right) \]
    10. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \left(2 \cdot -3\right)\right), 2\right)\right)\right)\right) \]
    11. metadata-eval100.0%

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), -6\right), 2\right)\right)\right)\right) \]
  6. Applied egg-rr100.0%

    \[\leadsto \frac{1 - v \cdot v}{\frac{4}{\sqrt{\color{blue}{\left(v \cdot v\right) \cdot -6 + 2}}}} \]
  7. Final simplification100.0%

    \[\leadsto \frac{1 - v \cdot v}{\frac{4}{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}} \]
  8. Add Preprocessing

Alternative 3: 100.0% accurate, 1.9× speedup?

\[\begin{array}{l} \\ \frac{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\frac{4}{1 - v \cdot v}} \end{array} \]
(FPCore (v)
 :precision binary64
 (/ (sqrt (+ 2.0 (* (* v v) -6.0))) (/ 4.0 (- 1.0 (* v v)))))
double code(double v) {
	return sqrt((2.0 + ((v * v) * -6.0))) / (4.0 / (1.0 - (v * v)));
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = sqrt((2.0d0 + ((v * v) * (-6.0d0)))) / (4.0d0 / (1.0d0 - (v * v)))
end function
public static double code(double v) {
	return Math.sqrt((2.0 + ((v * v) * -6.0))) / (4.0 / (1.0 - (v * v)));
}
def code(v):
	return math.sqrt((2.0 + ((v * v) * -6.0))) / (4.0 / (1.0 - (v * v)))
function code(v)
	return Float64(sqrt(Float64(2.0 + Float64(Float64(v * v) * -6.0))) / Float64(4.0 / Float64(1.0 - Float64(v * v))))
end
function tmp = code(v)
	tmp = sqrt((2.0 + ((v * v) * -6.0))) / (4.0 / (1.0 - (v * v)));
end
code[v_] := N[(N[Sqrt[N[(2.0 + N[(N[(v * v), $MachinePrecision] * -6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[(4.0 / N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\frac{4}{1 - v \cdot v}}
\end{array}
Derivation
  1. Initial program 100.0%

    \[\left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. *-commutativeN/A

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

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}{\color{blue}{4}} \]
    3. clear-numN/A

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{1}{\color{blue}{\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}}} \]
    4. un-div-invN/A

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

      \[\leadsto \mathsf{/.f64}\left(\left(1 - v \cdot v\right), \color{blue}{\left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)}\right) \]
    6. --lowering--.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \left(v \cdot v\right)\right), \left(\frac{\color{blue}{4}}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    8. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \color{blue}{\left(\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right)}\right)\right) \]
    9. sqrt-unprodN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)\right)\right) \]
    10. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 + \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    13. +-lowering-+.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    14. *-commutativeN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(\left(v \cdot v\right) \cdot 3\right)\right)\right)\right)\right)\right)\right) \]
    15. distribute-rgt-neg-inN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\left(v \cdot v\right) \cdot \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    16. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(v \cdot v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    17. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    18. metadata-eval100.0%

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), -3\right)\right)\right)\right)\right)\right) \]
  4. Applied egg-rr100.0%

    \[\leadsto \color{blue}{\frac{1 - v \cdot v}{\frac{4}{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}}} \]
  5. Step-by-step derivation
    1. associate-/r/N/A

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

      \[\leadsto \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)} \cdot \color{blue}{\frac{1 - v \cdot v}{4}} \]
    3. clear-numN/A

      \[\leadsto \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)} \cdot \frac{1}{\color{blue}{\frac{4}{1 - v \cdot v}}} \]
    4. metadata-evalN/A

      \[\leadsto \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)} \cdot \frac{1}{\frac{1 \cdot 4}{\color{blue}{1} - v \cdot v}} \]
    5. associate-*l/N/A

      \[\leadsto \sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)} \cdot \frac{1}{\frac{1}{1 - v \cdot v} \cdot \color{blue}{4}} \]
    6. div-invN/A

      \[\leadsto \frac{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}{\color{blue}{\frac{1}{1 - v \cdot v} \cdot 4}} \]
    7. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\left(\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}\right), \color{blue}{\left(\frac{1}{1 - v \cdot v} \cdot 4\right)}\right) \]
  6. Applied egg-rr100.0%

    \[\leadsto \color{blue}{\frac{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}{\frac{4}{1 - v \cdot v}}} \]
  7. Add Preprocessing

Alternative 4: 99.5% accurate, 2.0× speedup?

\[\begin{array}{l} \\ \sqrt{2} \cdot \left(0.25 + \left(v \cdot v\right) \cdot -0.625\right) \end{array} \]
(FPCore (v) :precision binary64 (* (sqrt 2.0) (+ 0.25 (* (* v v) -0.625))))
double code(double v) {
	return sqrt(2.0) * (0.25 + ((v * v) * -0.625));
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = sqrt(2.0d0) * (0.25d0 + ((v * v) * (-0.625d0)))
end function
public static double code(double v) {
	return Math.sqrt(2.0) * (0.25 + ((v * v) * -0.625));
}
def code(v):
	return math.sqrt(2.0) * (0.25 + ((v * v) * -0.625))
function code(v)
	return Float64(sqrt(2.0) * Float64(0.25 + Float64(Float64(v * v) * -0.625)))
end
function tmp = code(v)
	tmp = sqrt(2.0) * (0.25 + ((v * v) * -0.625));
end
code[v_] := N[(N[Sqrt[2.0], $MachinePrecision] * N[(0.25 + N[(N[(v * v), $MachinePrecision] * -0.625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt{2} \cdot \left(0.25 + \left(v \cdot v\right) \cdot -0.625\right)
\end{array}
Derivation
  1. Initial program 100.0%

    \[\left(\frac{\sqrt{2}}{4} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right) \cdot \left(1 - v \cdot v\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. *-commutativeN/A

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

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}{\color{blue}{4}} \]
    3. clear-numN/A

      \[\leadsto \left(1 - v \cdot v\right) \cdot \frac{1}{\color{blue}{\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}}} \]
    4. un-div-invN/A

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

      \[\leadsto \mathsf{/.f64}\left(\left(1 - v \cdot v\right), \color{blue}{\left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)}\right) \]
    6. --lowering--.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \left(v \cdot v\right)\right), \left(\frac{\color{blue}{4}}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \left(\frac{4}{\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}}\right)\right) \]
    8. /-lowering-/.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \color{blue}{\left(\sqrt{2} \cdot \sqrt{1 - 3 \cdot \left(v \cdot v\right)}\right)}\right)\right) \]
    9. sqrt-unprodN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)\right)\right) \]
    10. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\left(2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 - 3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(1 + \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    13. +-lowering-+.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(3 \cdot \left(v \cdot v\right)\right)\right)\right)\right)\right)\right)\right) \]
    14. *-commutativeN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\mathsf{neg}\left(\left(v \cdot v\right) \cdot 3\right)\right)\right)\right)\right)\right)\right) \]
    15. distribute-rgt-neg-inN/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \left(\left(v \cdot v\right) \cdot \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    16. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(v \cdot v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    17. *-lowering-*.f64N/A

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \left(\mathsf{neg}\left(3\right)\right)\right)\right)\right)\right)\right)\right) \]
    18. metadata-eval100.0%

      \[\leadsto \mathsf{/.f64}\left(\mathsf{\_.f64}\left(1, \mathsf{*.f64}\left(v, v\right)\right), \mathsf{/.f64}\left(4, \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), -3\right)\right)\right)\right)\right)\right) \]
  4. Applied egg-rr100.0%

    \[\leadsto \color{blue}{\frac{1 - v \cdot v}{\frac{4}{\sqrt{2 \cdot \left(1 + \left(v \cdot v\right) \cdot -3\right)}}}} \]
  5. Taylor expanded in v around 0

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

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

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\frac{1}{4} \cdot \left(\frac{-3}{2} \cdot \sqrt{2} + -1 \cdot \sqrt{2}\right)\right) \cdot \color{blue}{{v}^{2}} \]
    3. *-commutativeN/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\left(\frac{-3}{2} \cdot \sqrt{2} + -1 \cdot \sqrt{2}\right) \cdot \frac{1}{4}\right) \cdot {\color{blue}{v}}^{2} \]
    4. distribute-rgt-outN/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\left(\sqrt{2} \cdot \left(\frac{-3}{2} + -1\right)\right) \cdot \frac{1}{4}\right) \cdot {v}^{2} \]
    5. associate-*l*N/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\sqrt{2} \cdot \left(\left(\frac{-3}{2} + -1\right) \cdot \frac{1}{4}\right)\right) \cdot {\color{blue}{v}}^{2} \]
    6. metadata-evalN/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\sqrt{2} \cdot \left(\frac{-5}{2} \cdot \frac{1}{4}\right)\right) \cdot {v}^{2} \]
    7. metadata-evalN/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\sqrt{2} \cdot \frac{-5}{8}\right) \cdot {v}^{2} \]
    8. associate-*l*N/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \sqrt{2} \cdot \color{blue}{\left(\frac{-5}{8} \cdot {v}^{2}\right)} \]
    9. *-commutativeN/A

      \[\leadsto \frac{1}{4} \cdot \sqrt{2} + \left(\frac{-5}{8} \cdot {v}^{2}\right) \cdot \color{blue}{\sqrt{2}} \]
    10. distribute-rgt-outN/A

      \[\leadsto \sqrt{2} \cdot \color{blue}{\left(\frac{1}{4} + \frac{-5}{8} \cdot {v}^{2}\right)} \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{*.f64}\left(\left(\sqrt{2}\right), \color{blue}{\left(\frac{1}{4} + \frac{-5}{8} \cdot {v}^{2}\right)}\right) \]
    12. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \left(\color{blue}{\frac{1}{4}} + \frac{-5}{8} \cdot {v}^{2}\right)\right) \]
    13. +-lowering-+.f64N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \mathsf{+.f64}\left(\frac{1}{4}, \color{blue}{\left(\frac{-5}{8} \cdot {v}^{2}\right)}\right)\right) \]
    14. *-commutativeN/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \mathsf{+.f64}\left(\frac{1}{4}, \left({v}^{2} \cdot \color{blue}{\frac{-5}{8}}\right)\right)\right) \]
    15. *-lowering-*.f64N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \mathsf{+.f64}\left(\frac{1}{4}, \mathsf{*.f64}\left(\left({v}^{2}\right), \color{blue}{\frac{-5}{8}}\right)\right)\right) \]
    16. unpow2N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \mathsf{+.f64}\left(\frac{1}{4}, \mathsf{*.f64}\left(\left(v \cdot v\right), \frac{-5}{8}\right)\right)\right) \]
    17. *-lowering-*.f6499.6%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), \mathsf{+.f64}\left(\frac{1}{4}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(v, v\right), \frac{-5}{8}\right)\right)\right) \]
  7. Simplified99.6%

    \[\leadsto \color{blue}{\sqrt{2} \cdot \left(0.25 + \left(v \cdot v\right) \cdot -0.625\right)} \]
  8. Add Preprocessing

Alternative 5: 98.9% accurate, 2.1× speedup?

\[\begin{array}{l} \\ \sqrt{2} \cdot 0.25 \end{array} \]
(FPCore (v) :precision binary64 (* (sqrt 2.0) 0.25))
double code(double v) {
	return sqrt(2.0) * 0.25;
}
real(8) function code(v)
    real(8), intent (in) :: v
    code = sqrt(2.0d0) * 0.25d0
end function
public static double code(double v) {
	return Math.sqrt(2.0) * 0.25;
}
def code(v):
	return math.sqrt(2.0) * 0.25
function code(v)
	return Float64(sqrt(2.0) * 0.25)
end
function tmp = code(v)
	tmp = sqrt(2.0) * 0.25;
end
code[v_] := N[(N[Sqrt[2.0], $MachinePrecision] * 0.25), $MachinePrecision]
\begin{array}{l}

\\
\sqrt{2} \cdot 0.25
\end{array}
Derivation
  1. Initial program 100.0%

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

    \[\leadsto \color{blue}{\frac{1}{4} \cdot \sqrt{2}} \]
  4. Step-by-step derivation
    1. *-lowering-*.f64N/A

      \[\leadsto \mathsf{*.f64}\left(\frac{1}{4}, \color{blue}{\left(\sqrt{2}\right)}\right) \]
    2. sqrt-lowering-sqrt.f6498.6%

      \[\leadsto \mathsf{*.f64}\left(\frac{1}{4}, \mathsf{sqrt.f64}\left(2\right)\right) \]
  5. Simplified98.6%

    \[\leadsto \color{blue}{0.25 \cdot \sqrt{2}} \]
  6. Final simplification98.6%

    \[\leadsto \sqrt{2} \cdot 0.25 \]
  7. Add Preprocessing

Reproduce

?
herbie shell --seed 2024150 
(FPCore (v)
  :name "Falkner and Boettcher, Appendix B, 2"
  :precision binary64
  (* (* (/ (sqrt 2.0) 4.0) (sqrt (- 1.0 (* 3.0 (* v v))))) (- 1.0 (* v v))))