normal distribution

Percentage Accurate: 99.4% → 99.6%
Time: 13.9s
Alternatives: 10
Speedup: 1.5×

Specification

?
\[\left(0 \leq u1 \land u1 \leq 1\right) \land \left(0 \leq u2 \land u2 \leq 1\right)\]
\[\begin{array}{l} \\ \left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \end{array} \]
(FPCore (u1 u2)
 :precision binary64
 (+
  (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2)))
  0.5))
double code(double u1, double u2) {
	return (((1.0 / 6.0) * pow((-2.0 * log(u1)), 0.5)) * cos(((2.0 * ((double) M_PI)) * u2))) + 0.5;
}
public static double code(double u1, double u2) {
	return (((1.0 / 6.0) * Math.pow((-2.0 * Math.log(u1)), 0.5)) * Math.cos(((2.0 * Math.PI) * u2))) + 0.5;
}
def code(u1, u2):
	return (((1.0 / 6.0) * math.pow((-2.0 * math.log(u1)), 0.5)) * math.cos(((2.0 * math.pi) * u2))) + 0.5
function code(u1, u2)
	return Float64(Float64(Float64(Float64(1.0 / 6.0) * (Float64(-2.0 * log(u1)) ^ 0.5)) * cos(Float64(Float64(2.0 * pi) * u2))) + 0.5)
end
function tmp = code(u1, u2)
	tmp = (((1.0 / 6.0) * ((-2.0 * log(u1)) ^ 0.5)) * cos(((2.0 * pi) * u2))) + 0.5;
end
code[u1_, u2_] := N[(N[(N[(N[(1.0 / 6.0), $MachinePrecision] * N[Power[N[(-2.0 * N[Log[u1], $MachinePrecision]), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(N[(2.0 * Pi), $MachinePrecision] * u2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}

\\
\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5
\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 10 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: 99.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \end{array} \]
(FPCore (u1 u2)
 :precision binary64
 (+
  (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2)))
  0.5))
double code(double u1, double u2) {
	return (((1.0 / 6.0) * pow((-2.0 * log(u1)), 0.5)) * cos(((2.0 * ((double) M_PI)) * u2))) + 0.5;
}
public static double code(double u1, double u2) {
	return (((1.0 / 6.0) * Math.pow((-2.0 * Math.log(u1)), 0.5)) * Math.cos(((2.0 * Math.PI) * u2))) + 0.5;
}
def code(u1, u2):
	return (((1.0 / 6.0) * math.pow((-2.0 * math.log(u1)), 0.5)) * math.cos(((2.0 * math.pi) * u2))) + 0.5
function code(u1, u2)
	return Float64(Float64(Float64(Float64(1.0 / 6.0) * (Float64(-2.0 * log(u1)) ^ 0.5)) * cos(Float64(Float64(2.0 * pi) * u2))) + 0.5)
end
function tmp = code(u1, u2)
	tmp = (((1.0 / 6.0) * ((-2.0 * log(u1)) ^ 0.5)) * cos(((2.0 * pi) * u2))) + 0.5;
end
code[u1_, u2_] := N[(N[(N[(N[(1.0 / 6.0), $MachinePrecision] * N[Power[N[(-2.0 * N[Log[u1], $MachinePrecision]), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(N[(2.0 * Pi), $MachinePrecision] * u2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}

\\
\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5
\end{array}

Alternative 1: 99.6% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \left(0.16666666666666666 \cdot \sqrt{2}\right), \sqrt{-\log u1}, 0.5\right) \end{array} \]
(FPCore (u1 u2)
 :precision binary64
 (fma
  (* (cos (* PI (+ u2 u2))) (* 0.16666666666666666 (sqrt 2.0)))
  (sqrt (- (log u1)))
  0.5))
double code(double u1, double u2) {
	return fma((cos((((double) M_PI) * (u2 + u2))) * (0.16666666666666666 * sqrt(2.0))), sqrt(-log(u1)), 0.5);
}
function code(u1, u2)
	return fma(Float64(cos(Float64(pi * Float64(u2 + u2))) * Float64(0.16666666666666666 * sqrt(2.0))), sqrt(Float64(-log(u1))), 0.5)
end
code[u1_, u2_] := N[(N[(N[Cos[N[(Pi * N[(u2 + u2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(0.16666666666666666 * N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision] + 0.5), $MachinePrecision]
\begin{array}{l}

\\
\mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \left(0.16666666666666666 \cdot \sqrt{2}\right), \sqrt{-\log u1}, 0.5\right)
\end{array}
Derivation
  1. Initial program 99.4%

    \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
  2. Add Preprocessing
  3. Taylor expanded in u1 around inf

    \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
  4. Step-by-step derivation
    1. lower-*.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    2. lower-sqrt.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    3. log-recN/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    4. lower-neg.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    5. lower-log.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    6. lower-sqrt.f6499.5

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
  5. Applied rewrites99.5%

    \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
  6. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \left(\color{blue}{\frac{1}{6}} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    2. lift-log.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    3. lift-neg.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    4. lift-sqrt.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    5. lift-sqrt.f64N/A

      \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    6. *-commutativeN/A

      \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{2} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    7. associate-*r*N/A

      \[\leadsto \color{blue}{\left(\left(\frac{1}{6} \cdot \sqrt{2}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)} \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    8. lift-sqrt.f64N/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    9. pow1/2N/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{2}^{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    10. metadata-evalN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot {2}^{\color{blue}{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    11. pow-prod-upN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({2}^{\frac{1}{4}} \cdot {2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    12. pow-prod-downN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{\left(2 \cdot 2\right)}^{\frac{1}{4}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    13. metadata-evalN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{4}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    14. metadata-evalN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{\left(-2 \cdot -2\right)}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    15. pow-prod-downN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({-2}^{\frac{1}{4}} \cdot {-2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    16. pow-prod-upN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{-2}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    17. metadata-evalN/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot {-2}^{\color{blue}{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    18. pow1/2N/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    19. lift-sqrt.f64N/A

      \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    20. *-commutativeN/A

      \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    21. lift-/.f64N/A

      \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    22. metadata-evalN/A

      \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    23. lift-*.f64N/A

      \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    24. lower-*.f640.0

      \[\leadsto \color{blue}{\left(\left(\sqrt{-2} \cdot 0.16666666666666666\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
  7. Applied rewrites99.5%

    \[\leadsto \color{blue}{\left(\left(0.16666666666666666 \cdot \sqrt{2}\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
  8. Step-by-step derivation
    1. Applied rewrites99.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \left(0.16666666666666666 \cdot \sqrt{2}\right), \sqrt{-\log u1}, 0.5\right)} \]
    2. Add Preprocessing

    Alternative 2: 99.5% accurate, 1.4× speedup?

    \[\begin{array}{l} \\ \mathsf{fma}\left(\sqrt{2}, 0.16666666666666666 \cdot \left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{-\log u1}\right), 0.5\right) \end{array} \]
    (FPCore (u1 u2)
     :precision binary64
     (fma
      (sqrt 2.0)
      (* 0.16666666666666666 (* (cos (* PI (+ u2 u2))) (sqrt (- (log u1)))))
      0.5))
    double code(double u1, double u2) {
    	return fma(sqrt(2.0), (0.16666666666666666 * (cos((((double) M_PI) * (u2 + u2))) * sqrt(-log(u1)))), 0.5);
    }
    
    function code(u1, u2)
    	return fma(sqrt(2.0), Float64(0.16666666666666666 * Float64(cos(Float64(pi * Float64(u2 + u2))) * sqrt(Float64(-log(u1))))), 0.5)
    end
    
    code[u1_, u2_] := N[(N[Sqrt[2.0], $MachinePrecision] * N[(0.16666666666666666 * N[(N[Cos[N[(Pi * N[(u2 + u2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 0.5), $MachinePrecision]
    
    \begin{array}{l}
    
    \\
    \mathsf{fma}\left(\sqrt{2}, 0.16666666666666666 \cdot \left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{-\log u1}\right), 0.5\right)
    \end{array}
    
    Derivation
    1. Initial program 99.4%

      \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    2. Add Preprocessing
    3. Taylor expanded in u1 around inf

      \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
    4. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      2. lower-sqrt.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      3. log-recN/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. lower-neg.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      5. lower-log.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      6. lower-sqrt.f6499.5

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    5. Applied rewrites99.5%

      \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    6. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left(\color{blue}{\frac{1}{6}} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      2. lift-log.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      3. lift-neg.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. lift-sqrt.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      5. lift-sqrt.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      6. *-commutativeN/A

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{2} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      7. associate-*r*N/A

        \[\leadsto \color{blue}{\left(\left(\frac{1}{6} \cdot \sqrt{2}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)} \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      8. lift-sqrt.f64N/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      9. pow1/2N/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{2}^{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      10. metadata-evalN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot {2}^{\color{blue}{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      11. pow-prod-upN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({2}^{\frac{1}{4}} \cdot {2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      12. pow-prod-downN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{\left(2 \cdot 2\right)}^{\frac{1}{4}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      13. metadata-evalN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{4}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      14. metadata-evalN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{\left(-2 \cdot -2\right)}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      15. pow-prod-downN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({-2}^{\frac{1}{4}} \cdot {-2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      16. pow-prod-upN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{-2}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      17. metadata-evalN/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot {-2}^{\color{blue}{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      18. pow1/2N/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      19. lift-sqrt.f64N/A

        \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      20. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      21. lift-/.f64N/A

        \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      22. metadata-evalN/A

        \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      23. lift-*.f64N/A

        \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      24. lower-*.f640.0

        \[\leadsto \color{blue}{\left(\left(\sqrt{-2} \cdot 0.16666666666666666\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    7. Applied rewrites99.5%

      \[\leadsto \color{blue}{\left(\left(0.16666666666666666 \cdot \sqrt{2}\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    8. Applied rewrites99.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{2}, 0.16666666666666666 \cdot \left(\sqrt{-\log u1} \cdot \cos \left(\pi \cdot \left(u2 + u2\right)\right)\right), 0.5\right)} \]
    9. Final simplification99.5%

      \[\leadsto \mathsf{fma}\left(\sqrt{2}, 0.16666666666666666 \cdot \left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{-\log u1}\right), 0.5\right) \]
    10. Add Preprocessing

    Alternative 3: 99.4% accurate, 1.5× speedup?

    \[\begin{array}{l} \\ \mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right) \end{array} \]
    (FPCore (u1 u2)
     :precision binary64
     (fma
      (* (cos (* PI (+ u2 u2))) (sqrt (* (log u1) -2.0)))
      0.16666666666666666
      0.5))
    double code(double u1, double u2) {
    	return fma((cos((((double) M_PI) * (u2 + u2))) * sqrt((log(u1) * -2.0))), 0.16666666666666666, 0.5);
    }
    
    function code(u1, u2)
    	return fma(Float64(cos(Float64(pi * Float64(u2 + u2))) * sqrt(Float64(log(u1) * -2.0))), 0.16666666666666666, 0.5)
    end
    
    code[u1_, u2_] := N[(N[(N[Cos[N[(Pi * N[(u2 + u2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 0.16666666666666666 + 0.5), $MachinePrecision]
    
    \begin{array}{l}
    
    \\
    \mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right)
    \end{array}
    
    Derivation
    1. Initial program 99.4%

      \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-log.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot {\left(-2 \cdot \color{blue}{\log u1}\right)}^{\frac{1}{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      2. lift-*.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot {\color{blue}{\left(-2 \cdot \log u1\right)}}^{\frac{1}{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      3. sqr-powN/A

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. pow2N/A

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      5. lower-pow.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      6. metadata-evalN/A

        \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{\frac{1}{4}}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      7. metadata-evalN/A

        \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{\left(\frac{1}{2} \cdot \frac{1}{2}\right)}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      8. lower-pow.f64N/A

        \[\leadsto \left(\frac{1}{6} \cdot {\color{blue}{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{1}{2} \cdot \frac{1}{2}\right)}\right)}}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      9. metadata-eval99.2

        \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{0.25}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    4. Applied rewrites99.2%

      \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{0.25}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
    5. Step-by-step derivation
      1. Applied rewrites99.3%

        \[\leadsto \color{blue}{\mathsf{fma}\left(0.16666666666666666 \cdot \cos \left(2 \cdot \left(\pi \cdot u2\right)\right), \sqrt{\log u1 \cdot -2}, 0.5\right)} \]
      2. Step-by-step derivation
        1. lift-PI.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\color{blue}{\mathsf{PI}\left(\right)} \cdot u2\right)\right)\right) \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        2. lift-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \left(2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot u2\right)}\right)\right) \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        3. lift-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \color{blue}{\left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)}\right) \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        4. lift-cos.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)}\right) \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        5. lift-*.f64N/A

          \[\leadsto \color{blue}{\left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)\right)} \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        6. lift-log.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)\right) \cdot \sqrt{\color{blue}{\log u1} \cdot -2} + \frac{1}{2} \]
        7. lift-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)\right) \cdot \sqrt{\color{blue}{\log u1 \cdot -2}} + \frac{1}{2} \]
        8. lift-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)\right) \cdot \color{blue}{\sqrt{\log u1 \cdot -2}} + \frac{1}{2} \]
        9. lift-*.f64N/A

          \[\leadsto \color{blue}{\left(\frac{1}{6} \cdot \cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right)\right)} \cdot \sqrt{\log u1 \cdot -2} + \frac{1}{2} \]
        10. associate-*l*N/A

          \[\leadsto \color{blue}{\frac{1}{6} \cdot \left(\cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}\right)} + \frac{1}{2} \]
        11. *-commutativeN/A

          \[\leadsto \color{blue}{\left(\cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}\right) \cdot \frac{1}{6}} + \frac{1}{2} \]
        12. lower-fma.f64N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(2 \cdot \left(\mathsf{PI}\left(\right) \cdot u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}, \frac{1}{6}, \frac{1}{2}\right)} \]
      3. Applied rewrites99.4%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\log u1 \cdot -2} \cdot \cos \left(\pi \cdot \left(u2 + u2\right)\right), 0.16666666666666666, 0.5\right)} \]
      4. Final simplification99.4%

        \[\leadsto \mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right) \]
      5. Add Preprocessing

      Alternative 4: 98.9% accurate, 2.0× speedup?

      \[\begin{array}{l} \\ 0.5 + \left(\frac{1}{6} \cdot \left(\sqrt{2} \cdot \sqrt{-\log u1}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \end{array} \]
      (FPCore (u1 u2)
       :precision binary64
       (+
        0.5
        (*
         (* (/ 1.0 6.0) (* (sqrt 2.0) (sqrt (- (log u1)))))
         (fma u2 (* u2 (* -2.0 (* PI PI))) 1.0))))
      double code(double u1, double u2) {
      	return 0.5 + (((1.0 / 6.0) * (sqrt(2.0) * sqrt(-log(u1)))) * fma(u2, (u2 * (-2.0 * (((double) M_PI) * ((double) M_PI)))), 1.0));
      }
      
      function code(u1, u2)
      	return Float64(0.5 + Float64(Float64(Float64(1.0 / 6.0) * Float64(sqrt(2.0) * sqrt(Float64(-log(u1))))) * fma(u2, Float64(u2 * Float64(-2.0 * Float64(pi * pi))), 1.0)))
      end
      
      code[u1_, u2_] := N[(0.5 + N[(N[(N[(1.0 / 6.0), $MachinePrecision] * N[(N[Sqrt[2.0], $MachinePrecision] * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(u2 * N[(u2 * N[(-2.0 * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      0.5 + \left(\frac{1}{6} \cdot \left(\sqrt{2} \cdot \sqrt{-\log u1}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.4%

        \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around inf

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. Step-by-step derivation
        1. lower-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        2. lower-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        3. log-recN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        4. lower-neg.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        5. lower-log.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        6. lower-sqrt.f6499.5

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      5. Applied rewrites99.5%

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(1 + -2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + \frac{1}{2} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(-2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right)} + \frac{1}{2} \]
        2. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        3. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{\left(\sqrt{-2}\right)}^{2}} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        4. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) \cdot {\left(\sqrt{-2}\right)}^{2}} + 1\right) + \frac{1}{2} \]
        5. associate-*r*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot {\left(\sqrt{-2}\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        6. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)}\right) + 1\right) + \frac{1}{2} \]
        7. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{-2}\right) + 1\right) + \frac{1}{2} \]
        8. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \color{blue}{\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        9. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        10. associate-*l*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{u2 \cdot \left(u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + 1\right) + \frac{1}{2} \]
        11. lower-fma.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right), 1\right)} + \frac{1}{2} \]
      8. Applied rewrites99.0%

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right)} + 0.5 \]
      9. Final simplification99.0%

        \[\leadsto 0.5 + \left(\frac{1}{6} \cdot \left(\sqrt{2} \cdot \sqrt{-\log u1}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \]
      10. Add Preprocessing

      Alternative 5: 98.8% accurate, 2.1× speedup?

      \[\begin{array}{l} \\ 0.5 + \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \left(\sqrt{2} \cdot \left(0.16666666666666666 \cdot \sqrt{-\log u1}\right)\right) \end{array} \]
      (FPCore (u1 u2)
       :precision binary64
       (+
        0.5
        (*
         (fma u2 (* u2 (* -2.0 (* PI PI))) 1.0)
         (* (sqrt 2.0) (* 0.16666666666666666 (sqrt (- (log u1))))))))
      double code(double u1, double u2) {
      	return 0.5 + (fma(u2, (u2 * (-2.0 * (((double) M_PI) * ((double) M_PI)))), 1.0) * (sqrt(2.0) * (0.16666666666666666 * sqrt(-log(u1)))));
      }
      
      function code(u1, u2)
      	return Float64(0.5 + Float64(fma(u2, Float64(u2 * Float64(-2.0 * Float64(pi * pi))), 1.0) * Float64(sqrt(2.0) * Float64(0.16666666666666666 * sqrt(Float64(-log(u1)))))))
      end
      
      code[u1_, u2_] := N[(0.5 + N[(N[(u2 * N[(u2 * N[(-2.0 * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] * N[(N[Sqrt[2.0], $MachinePrecision] * N[(0.16666666666666666 * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      0.5 + \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \left(\sqrt{2} \cdot \left(0.16666666666666666 \cdot \sqrt{-\log u1}\right)\right)
      \end{array}
      
      Derivation
      1. Initial program 99.4%

        \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around inf

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. Step-by-step derivation
        1. lower-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        2. lower-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        3. log-recN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        4. lower-neg.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        5. lower-log.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        6. lower-sqrt.f6499.5

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      5. Applied rewrites99.5%

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(1 + -2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + \frac{1}{2} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(-2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right)} + \frac{1}{2} \]
        2. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        3. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{\left(\sqrt{-2}\right)}^{2}} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        4. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) \cdot {\left(\sqrt{-2}\right)}^{2}} + 1\right) + \frac{1}{2} \]
        5. associate-*r*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot {\left(\sqrt{-2}\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        6. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)}\right) + 1\right) + \frac{1}{2} \]
        7. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{-2}\right) + 1\right) + \frac{1}{2} \]
        8. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \color{blue}{\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        9. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        10. associate-*l*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{u2 \cdot \left(u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + 1\right) + \frac{1}{2} \]
        11. lower-fma.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right), 1\right)} + \frac{1}{2} \]
      8. Applied rewrites99.0%

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right)} + 0.5 \]
      9. Step-by-step derivation
        1. metadata-evalN/A

          \[\leadsto \left(\color{blue}{\frac{1}{6}} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        2. lift-log.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        3. lift-neg.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        4. lift-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        5. lift-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        6. associate-*r*N/A

          \[\leadsto \color{blue}{\left(\left(\frac{1}{6} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \sqrt{2}\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        7. lower-*.f64N/A

          \[\leadsto \color{blue}{\left(\left(\frac{1}{6} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \sqrt{2}\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot -2\right), 1\right) + \frac{1}{2} \]
        8. lower-*.f6499.0

          \[\leadsto \left(\color{blue}{\left(0.16666666666666666 \cdot \sqrt{-\log u1}\right)} \cdot \sqrt{2}\right) \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right) + 0.5 \]
      10. Applied rewrites99.0%

        \[\leadsto \color{blue}{\left(\left(0.16666666666666666 \cdot \sqrt{-\log u1}\right) \cdot \sqrt{2}\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right) + 0.5 \]
      11. Final simplification99.0%

        \[\leadsto 0.5 + \mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \left(\sqrt{2} \cdot \left(0.16666666666666666 \cdot \sqrt{-\log u1}\right)\right) \]
      12. Add Preprocessing

      Alternative 6: 98.9% accurate, 2.1× speedup?

      \[\begin{array}{l} \\ \mathsf{fma}\left(\left(0.16666666666666666 \cdot \sqrt{-\log u1}\right) \cdot \mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right), \sqrt{2}, 0.5\right) \end{array} \]
      (FPCore (u1 u2)
       :precision binary64
       (fma
        (*
         (* 0.16666666666666666 (sqrt (- (log u1))))
         (fma u2 (* -2.0 (* u2 (* PI PI))) 1.0))
        (sqrt 2.0)
        0.5))
      double code(double u1, double u2) {
      	return fma(((0.16666666666666666 * sqrt(-log(u1))) * fma(u2, (-2.0 * (u2 * (((double) M_PI) * ((double) M_PI)))), 1.0)), sqrt(2.0), 0.5);
      }
      
      function code(u1, u2)
      	return fma(Float64(Float64(0.16666666666666666 * sqrt(Float64(-log(u1)))) * fma(u2, Float64(-2.0 * Float64(u2 * Float64(pi * pi))), 1.0)), sqrt(2.0), 0.5)
      end
      
      code[u1_, u2_] := N[(N[(N[(0.16666666666666666 * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision]), $MachinePrecision] * N[(u2 * N[(-2.0 * N[(u2 * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] * N[Sqrt[2.0], $MachinePrecision] + 0.5), $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      \mathsf{fma}\left(\left(0.16666666666666666 \cdot \sqrt{-\log u1}\right) \cdot \mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right), \sqrt{2}, 0.5\right)
      \end{array}
      
      Derivation
      1. Initial program 99.4%

        \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around inf

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
      4. Step-by-step derivation
        1. lower-*.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        2. lower-sqrt.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        3. log-recN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        4. lower-neg.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        5. lower-log.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        6. lower-sqrt.f6499.5

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      5. Applied rewrites99.5%

        \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(1 + -2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + \frac{1}{2} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(-2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right)} + \frac{1}{2} \]
        2. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        3. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{\left(\sqrt{-2}\right)}^{2}} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        4. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) \cdot {\left(\sqrt{-2}\right)}^{2}} + 1\right) + \frac{1}{2} \]
        5. associate-*r*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot {\left(\sqrt{-2}\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        6. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)}\right) + 1\right) + \frac{1}{2} \]
        7. rem-square-sqrtN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{-2}\right) + 1\right) + \frac{1}{2} \]
        8. *-commutativeN/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \color{blue}{\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
        9. unpow2N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
        10. associate-*l*N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{u2 \cdot \left(u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + 1\right) + \frac{1}{2} \]
        11. lower-fma.f64N/A

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right), 1\right)} + \frac{1}{2} \]
      8. Applied rewrites99.0%

        \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right)} + 0.5 \]
      9. Step-by-step derivation
        1. Applied rewrites99.0%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \left(0.16666666666666666 \cdot \sqrt{-\log u1}\right), \sqrt{2}, 0.5\right)} \]
        2. Final simplification99.0%

          \[\leadsto \mathsf{fma}\left(\left(0.16666666666666666 \cdot \sqrt{-\log u1}\right) \cdot \mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right), \sqrt{2}, 0.5\right) \]
        3. Add Preprocessing

        Alternative 7: 98.8% accurate, 2.3× speedup?

        \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \sqrt{\log u1 \cdot \left(-2\right)}, 0.16666666666666666, 0.5\right) \end{array} \]
        (FPCore (u1 u2)
         :precision binary64
         (fma
          (* (fma u2 (* -2.0 (* u2 (* PI PI))) 1.0) (sqrt (* (log u1) (- 2.0))))
          0.16666666666666666
          0.5))
        double code(double u1, double u2) {
        	return fma((fma(u2, (-2.0 * (u2 * (((double) M_PI) * ((double) M_PI)))), 1.0) * sqrt((log(u1) * -2.0))), 0.16666666666666666, 0.5);
        }
        
        function code(u1, u2)
        	return fma(Float64(fma(u2, Float64(-2.0 * Float64(u2 * Float64(pi * pi))), 1.0) * sqrt(Float64(log(u1) * Float64(-2.0)))), 0.16666666666666666, 0.5)
        end
        
        code[u1_, u2_] := N[(N[(N[(u2 * N[(-2.0 * N[(u2 * N[(Pi * Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * (-2.0)), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 0.16666666666666666 + 0.5), $MachinePrecision]
        
        \begin{array}{l}
        
        \\
        \mathsf{fma}\left(\mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \sqrt{\log u1 \cdot \left(-2\right)}, 0.16666666666666666, 0.5\right)
        \end{array}
        
        Derivation
        1. Initial program 99.4%

          \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        2. Add Preprocessing
        3. Taylor expanded in u1 around inf

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
        4. Step-by-step derivation
          1. lower-*.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          2. lower-sqrt.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          3. log-recN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          4. lower-neg.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          5. lower-log.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          6. lower-sqrt.f6499.5

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        5. Applied rewrites99.5%

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        6. Taylor expanded in u2 around 0

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(1 + -2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + \frac{1}{2} \]
        7. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\left(-2 \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right)} + \frac{1}{2} \]
          2. rem-square-sqrtN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
          3. unpow2N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{\left(\sqrt{-2}\right)}^{2}} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
          4. *-commutativeN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) \cdot {\left(\sqrt{-2}\right)}^{2}} + 1\right) + \frac{1}{2} \]
          5. associate-*r*N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{{u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot {\left(\sqrt{-2}\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
          6. unpow2N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{\left(\sqrt{-2} \cdot \sqrt{-2}\right)}\right) + 1\right) + \frac{1}{2} \]
          7. rem-square-sqrtN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{2} \cdot \color{blue}{-2}\right) + 1\right) + \frac{1}{2} \]
          8. *-commutativeN/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left({u2}^{2} \cdot \color{blue}{\left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)} + 1\right) + \frac{1}{2} \]
          9. unpow2N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right) + 1\right) + \frac{1}{2} \]
          10. associate-*l*N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \left(\color{blue}{u2 \cdot \left(u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} + 1\right) + \frac{1}{2} \]
          11. lower-fma.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(-2 \cdot {\mathsf{PI}\left(\right)}^{2}\right), 1\right)} + \frac{1}{2} \]
        8. Applied rewrites99.0%

          \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \sqrt{2}\right)\right) \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\left(\pi \cdot \pi\right) \cdot -2\right), 1\right)} + 0.5 \]
        9. Applied rewrites98.9%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{-\log u1 \cdot 2} \cdot \mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right), 0.16666666666666666, 0.5\right)} \]
        10. Final simplification98.9%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(u2, -2 \cdot \left(u2 \cdot \left(\pi \cdot \pi\right)\right), 1\right) \cdot \sqrt{\log u1 \cdot \left(-2\right)}, 0.16666666666666666, 0.5\right) \]
        11. Add Preprocessing

        Alternative 8: 98.8% accurate, 2.4× speedup?

        \[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, \pi \cdot \left(\pi \cdot \left(u2 \cdot u2\right)\right), 0.16666666666666666\right), \sqrt{\log u1 \cdot -2}, 0.5\right) \end{array} \]
        (FPCore (u1 u2)
         :precision binary64
         (fma
          (fma -0.3333333333333333 (* PI (* PI (* u2 u2))) 0.16666666666666666)
          (sqrt (* (log u1) -2.0))
          0.5))
        double code(double u1, double u2) {
        	return fma(fma(-0.3333333333333333, (((double) M_PI) * (((double) M_PI) * (u2 * u2))), 0.16666666666666666), sqrt((log(u1) * -2.0)), 0.5);
        }
        
        function code(u1, u2)
        	return fma(fma(-0.3333333333333333, Float64(pi * Float64(pi * Float64(u2 * u2))), 0.16666666666666666), sqrt(Float64(log(u1) * -2.0)), 0.5)
        end
        
        code[u1_, u2_] := N[(N[(-0.3333333333333333 * N[(Pi * N[(Pi * N[(u2 * u2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 0.16666666666666666), $MachinePrecision] * N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision]
        
        \begin{array}{l}
        
        \\
        \mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, \pi \cdot \left(\pi \cdot \left(u2 \cdot u2\right)\right), 0.16666666666666666\right), \sqrt{\log u1 \cdot -2}, 0.5\right)
        \end{array}
        
        Derivation
        1. Initial program 99.4%

          \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-log.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot {\left(-2 \cdot \color{blue}{\log u1}\right)}^{\frac{1}{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          2. lift-*.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot {\color{blue}{\left(-2 \cdot \log u1\right)}}^{\frac{1}{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          3. sqr-powN/A

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          4. pow2N/A

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          5. lower-pow.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          6. metadata-evalN/A

            \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{\frac{1}{4}}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          7. metadata-evalN/A

            \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{\left(\frac{1}{2} \cdot \frac{1}{2}\right)}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          8. lower-pow.f64N/A

            \[\leadsto \left(\frac{1}{6} \cdot {\color{blue}{\left({\left(-2 \cdot \log u1\right)}^{\left(\frac{1}{2} \cdot \frac{1}{2}\right)}\right)}}^{2}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          9. metadata-eval99.2

            \[\leadsto \left(\frac{1}{6} \cdot {\left({\left(-2 \cdot \log u1\right)}^{\color{blue}{0.25}}\right)}^{2}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        4. Applied rewrites99.2%

          \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{{\left({\left(-2 \cdot \log u1\right)}^{0.25}\right)}^{2}}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
        5. Step-by-step derivation
          1. Applied rewrites99.3%

            \[\leadsto \color{blue}{\mathsf{fma}\left(0.16666666666666666 \cdot \cos \left(2 \cdot \left(\pi \cdot u2\right)\right), \sqrt{\log u1 \cdot -2}, 0.5\right)} \]
          2. Taylor expanded in u2 around 0

            \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{1}{6} + \frac{-1}{3} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)}, \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
          3. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{-1}{3} \cdot \left({u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + \frac{1}{6}}, \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            2. lower-fma.f64N/A

              \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-1}{3}, {u2}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}, \frac{1}{6}\right)}, \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            3. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, {u2}^{2} \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}, \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            4. associate-*r*N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \color{blue}{\left({u2}^{2} \cdot \mathsf{PI}\left(\right)\right) \cdot \mathsf{PI}\left(\right)}, \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            5. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \color{blue}{\left({u2}^{2} \cdot \mathsf{PI}\left(\right)\right) \cdot \mathsf{PI}\left(\right)}, \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            6. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \color{blue}{\left({u2}^{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot \mathsf{PI}\left(\right), \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            7. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \mathsf{PI}\left(\right), \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            8. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \mathsf{PI}\left(\right), \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            9. lower-PI.f64N/A

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{-1}{3}, \left(\left(u2 \cdot u2\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot \mathsf{PI}\left(\right), \frac{1}{6}\right), \sqrt{\log u1 \cdot -2}, \frac{1}{2}\right) \]
            10. lower-PI.f6498.9

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, \left(\left(u2 \cdot u2\right) \cdot \pi\right) \cdot \color{blue}{\pi}, 0.16666666666666666\right), \sqrt{\log u1 \cdot -2}, 0.5\right) \]
          4. Applied rewrites98.9%

            \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(-0.3333333333333333, \left(\left(u2 \cdot u2\right) \cdot \pi\right) \cdot \pi, 0.16666666666666666\right)}, \sqrt{\log u1 \cdot -2}, 0.5\right) \]
          5. Final simplification98.9%

            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(-0.3333333333333333, \pi \cdot \left(\pi \cdot \left(u2 \cdot u2\right)\right), 0.16666666666666666\right), \sqrt{\log u1 \cdot -2}, 0.5\right) \]
          6. Add Preprocessing

          Alternative 9: 98.4% accurate, 2.5× speedup?

          \[\begin{array}{l} \\ \mathsf{fma}\left(0.16666666666666666 \cdot \sqrt{2}, \sqrt{-\log u1}, 0.5\right) \end{array} \]
          (FPCore (u1 u2)
           :precision binary64
           (fma (* 0.16666666666666666 (sqrt 2.0)) (sqrt (- (log u1))) 0.5))
          double code(double u1, double u2) {
          	return fma((0.16666666666666666 * sqrt(2.0)), sqrt(-log(u1)), 0.5);
          }
          
          function code(u1, u2)
          	return fma(Float64(0.16666666666666666 * sqrt(2.0)), sqrt(Float64(-log(u1))), 0.5)
          end
          
          code[u1_, u2_] := N[(N[(0.16666666666666666 * N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * N[Sqrt[(-N[Log[u1], $MachinePrecision])], $MachinePrecision] + 0.5), $MachinePrecision]
          
          \begin{array}{l}
          
          \\
          \mathsf{fma}\left(0.16666666666666666 \cdot \sqrt{2}, \sqrt{-\log u1}, 0.5\right)
          \end{array}
          
          Derivation
          1. Initial program 99.4%

            \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
          2. Add Preprocessing
          3. Taylor expanded in u1 around inf

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
          4. Step-by-step derivation
            1. lower-*.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{\log \left(\frac{1}{u1}\right)} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            2. lower-sqrt.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\log \left(\frac{1}{u1}\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            3. log-recN/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            4. lower-neg.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            5. lower-log.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            6. lower-sqrt.f6499.5

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{-\log u1} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
          5. Applied rewrites99.5%

            \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{-\log u1} \cdot \sqrt{2}\right)}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
          6. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto \left(\color{blue}{\frac{1}{6}} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            2. lift-log.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\color{blue}{\log u1}\right)} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            3. lift-neg.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\color{blue}{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            4. lift-sqrt.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\color{blue}{\sqrt{\mathsf{neg}\left(\log u1\right)}} \cdot \sqrt{2}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            5. lift-sqrt.f64N/A

              \[\leadsto \left(\frac{1}{6} \cdot \left(\sqrt{\mathsf{neg}\left(\log u1\right)} \cdot \color{blue}{\sqrt{2}}\right)\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            6. *-commutativeN/A

              \[\leadsto \left(\frac{1}{6} \cdot \color{blue}{\left(\sqrt{2} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            7. associate-*r*N/A

              \[\leadsto \color{blue}{\left(\left(\frac{1}{6} \cdot \sqrt{2}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right)} \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            8. lift-sqrt.f64N/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            9. pow1/2N/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{2}^{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            10. metadata-evalN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot {2}^{\color{blue}{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            11. pow-prod-upN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({2}^{\frac{1}{4}} \cdot {2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            12. pow-prod-downN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{\left(2 \cdot 2\right)}^{\frac{1}{4}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            13. metadata-evalN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{4}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            14. metadata-evalN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot {\color{blue}{\left(-2 \cdot -2\right)}}^{\frac{1}{4}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            15. pow-prod-downN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\left({-2}^{\frac{1}{4}} \cdot {-2}^{\frac{1}{4}}\right)}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            16. pow-prod-upN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{{-2}^{\left(\frac{1}{4} + \frac{1}{4}\right)}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            17. metadata-evalN/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot {-2}^{\color{blue}{\frac{1}{2}}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            18. pow1/2N/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            19. lift-sqrt.f64N/A

              \[\leadsto \left(\left(\frac{1}{6} \cdot \color{blue}{\sqrt{-2}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            20. *-commutativeN/A

              \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            21. lift-/.f64N/A

              \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            22. metadata-evalN/A

              \[\leadsto \left(\left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            23. lift-*.f64N/A

              \[\leadsto \left(\color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\mathsf{neg}\left(\log u1\right)}\right) \cdot \cos \left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot u2\right) + \frac{1}{2} \]
            24. lower-*.f640.0

              \[\leadsto \color{blue}{\left(\left(\sqrt{-2} \cdot 0.16666666666666666\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
          7. Applied rewrites99.5%

            \[\leadsto \color{blue}{\left(\left(0.16666666666666666 \cdot \sqrt{2}\right) \cdot \sqrt{-\log u1}\right)} \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
          8. Step-by-step derivation
            1. Applied rewrites99.5%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(\pi \cdot \left(u2 + u2\right)\right) \cdot \left(0.16666666666666666 \cdot \sqrt{2}\right), \sqrt{-\log u1}, 0.5\right)} \]
            2. Taylor expanded in u2 around 0

              \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{1}{6} \cdot \sqrt{2}}, \sqrt{\mathsf{neg}\left(\log u1\right)}, \frac{1}{2}\right) \]
            3. Step-by-step derivation
              1. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{1}{6} \cdot \sqrt{2}}, \sqrt{\mathsf{neg}\left(\log u1\right)}, \frac{1}{2}\right) \]
              2. lower-sqrt.f6498.6

                \[\leadsto \mathsf{fma}\left(0.16666666666666666 \cdot \color{blue}{\sqrt{2}}, \sqrt{-\log u1}, 0.5\right) \]
            4. Applied rewrites98.6%

              \[\leadsto \mathsf{fma}\left(\color{blue}{0.16666666666666666 \cdot \sqrt{2}}, \sqrt{-\log u1}, 0.5\right) \]
            5. Add Preprocessing

            Alternative 10: 98.2% accurate, 2.8× speedup?

            \[\begin{array}{l} \\ \mathsf{fma}\left(\sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right) \end{array} \]
            (FPCore (u1 u2)
             :precision binary64
             (fma (sqrt (* (log u1) -2.0)) 0.16666666666666666 0.5))
            double code(double u1, double u2) {
            	return fma(sqrt((log(u1) * -2.0)), 0.16666666666666666, 0.5);
            }
            
            function code(u1, u2)
            	return fma(sqrt(Float64(log(u1) * -2.0)), 0.16666666666666666, 0.5)
            end
            
            code[u1_, u2_] := N[(N[Sqrt[N[(N[Log[u1], $MachinePrecision] * -2.0), $MachinePrecision]], $MachinePrecision] * 0.16666666666666666 + 0.5), $MachinePrecision]
            
            \begin{array}{l}
            
            \\
            \mathsf{fma}\left(\sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right)
            \end{array}
            
            Derivation
            1. Initial program 99.4%

              \[\left(\frac{1}{6} \cdot {\left(-2 \cdot \log u1\right)}^{0.5}\right) \cdot \cos \left(\left(2 \cdot \pi\right) \cdot u2\right) + 0.5 \]
            2. Add Preprocessing
            3. Taylor expanded in u2 around 0

              \[\leadsto \color{blue}{\frac{1}{2} + \frac{1}{6} \cdot \left(\sqrt{\log u1} \cdot \sqrt{-2}\right)} \]
            4. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \color{blue}{\frac{1}{6} \cdot \left(\sqrt{\log u1} \cdot \sqrt{-2}\right) + \frac{1}{2}} \]
              2. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\sqrt{\log u1} \cdot \sqrt{-2}\right) \cdot \frac{1}{6}} + \frac{1}{2} \]
              3. associate-*l*N/A

                \[\leadsto \color{blue}{\sqrt{\log u1} \cdot \left(\sqrt{-2} \cdot \frac{1}{6}\right)} + \frac{1}{2} \]
              4. *-commutativeN/A

                \[\leadsto \sqrt{\log u1} \cdot \color{blue}{\left(\frac{1}{6} \cdot \sqrt{-2}\right)} + \frac{1}{2} \]
              5. lower-fma.f64N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\log u1}, \frac{1}{6} \cdot \sqrt{-2}, \frac{1}{2}\right)} \]
              6. lower-sqrt.f64N/A

                \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\log u1}}, \frac{1}{6} \cdot \sqrt{-2}, \frac{1}{2}\right) \]
              7. lower-log.f64N/A

                \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\log u1}}, \frac{1}{6} \cdot \sqrt{-2}, \frac{1}{2}\right) \]
              8. *-commutativeN/A

                \[\leadsto \mathsf{fma}\left(\sqrt{\log u1}, \color{blue}{\sqrt{-2} \cdot \frac{1}{6}}, \frac{1}{2}\right) \]
              9. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\sqrt{\log u1}, \color{blue}{\sqrt{-2} \cdot \frac{1}{6}}, \frac{1}{2}\right) \]
              10. lower-sqrt.f640.0

                \[\leadsto \mathsf{fma}\left(\sqrt{\log u1}, \color{blue}{\sqrt{-2}} \cdot 0.16666666666666666, 0.5\right) \]
            5. Applied rewrites0.0%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\log u1}, \sqrt{-2} \cdot 0.16666666666666666, 0.5\right)} \]
            6. Step-by-step derivation
              1. lift-log.f64N/A

                \[\leadsto \sqrt{\color{blue}{\log u1}} \cdot \left(\sqrt{-2} \cdot \frac{1}{6}\right) + \frac{1}{2} \]
              2. lift-sqrt.f64N/A

                \[\leadsto \color{blue}{\sqrt{\log u1}} \cdot \left(\sqrt{-2} \cdot \frac{1}{6}\right) + \frac{1}{2} \]
              3. lift-sqrt.f64N/A

                \[\leadsto \sqrt{\log u1} \cdot \left(\color{blue}{\sqrt{-2}} \cdot \frac{1}{6}\right) + \frac{1}{2} \]
              4. lift-*.f64N/A

                \[\leadsto \sqrt{\log u1} \cdot \color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} + \frac{1}{2} \]
              5. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right) \cdot \sqrt{\log u1}} + \frac{1}{2} \]
              6. lift-*.f64N/A

                \[\leadsto \color{blue}{\left(\sqrt{-2} \cdot \frac{1}{6}\right)} \cdot \sqrt{\log u1} + \frac{1}{2} \]
              7. metadata-evalN/A

                \[\leadsto \left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\log u1} + \frac{1}{2} \]
              8. lift-/.f64N/A

                \[\leadsto \left(\sqrt{-2} \cdot \color{blue}{\frac{1}{6}}\right) \cdot \sqrt{\log u1} + \frac{1}{2} \]
              9. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\frac{1}{6} \cdot \sqrt{-2}\right)} \cdot \sqrt{\log u1} + \frac{1}{2} \]
              10. associate-*r*N/A

                \[\leadsto \color{blue}{\frac{1}{6} \cdot \left(\sqrt{-2} \cdot \sqrt{\log u1}\right)} + \frac{1}{2} \]
              11. lift-sqrt.f64N/A

                \[\leadsto \frac{1}{6} \cdot \left(\color{blue}{\sqrt{-2}} \cdot \sqrt{\log u1}\right) + \frac{1}{2} \]
              12. lift-sqrt.f64N/A

                \[\leadsto \frac{1}{6} \cdot \left(\sqrt{-2} \cdot \color{blue}{\sqrt{\log u1}}\right) + \frac{1}{2} \]
              13. sqrt-prodN/A

                \[\leadsto \frac{1}{6} \cdot \color{blue}{\sqrt{-2 \cdot \log u1}} + \frac{1}{2} \]
              14. lift-*.f64N/A

                \[\leadsto \frac{1}{6} \cdot \sqrt{\color{blue}{-2 \cdot \log u1}} + \frac{1}{2} \]
              15. lift-sqrt.f64N/A

                \[\leadsto \frac{1}{6} \cdot \color{blue}{\sqrt{-2 \cdot \log u1}} + \frac{1}{2} \]
              16. *-commutativeN/A

                \[\leadsto \color{blue}{\sqrt{-2 \cdot \log u1} \cdot \frac{1}{6}} + \frac{1}{2} \]
              17. lower-fma.f6498.4

                \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{-2 \cdot \log u1}, \frac{1}{6}, 0.5\right)} \]
            7. Applied rewrites98.4%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\log u1 \cdot -2}, 0.16666666666666666, 0.5\right)} \]
            8. Add Preprocessing

            Reproduce

            ?
            herbie shell --seed 2024214 
            (FPCore (u1 u2)
              :name "normal distribution"
              :precision binary64
              :pre (and (and (<= 0.0 u1) (<= u1 1.0)) (and (<= 0.0 u2) (<= u2 1.0)))
              (+ (* (* (/ 1.0 6.0) (pow (* -2.0 (log u1)) 0.5)) (cos (* (* 2.0 PI) u2))) 0.5))