Beckmann Sample, near normal, slope_y

Percentage Accurate: 57.5% → 98.3%
Time: 3.8s
Alternatives: 10
Speedup: 4.5×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\begin{array}{l} \\ \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf(-logf((1.0f - u1))) * sinf(((2.0f * ((float) M_PI)) * u2));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt(-log((single(1.0) - u1))) * sin(((single(2.0) * single(pi)) * u2));
end
\begin{array}{l}

\\
\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)
\end{array}

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 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: 57.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf(-logf((1.0f - u1))) * sinf(((2.0f * ((float) M_PI)) * u2));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt(-log((single(1.0) - u1))) * sin(((single(2.0) * single(pi)) * u2));
end
\begin{array}{l}

\\
\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)
\end{array}

Alternative 1: 98.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (- (log1p (- u1)))) (sin (* (+ PI PI) u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf(-log1pf(-u1)) * sinf(((((float) M_PI) + ((float) M_PI)) * u2));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(-log1p(Float32(-u1)))) * sin(Float32(Float32(Float32(pi) + Float32(pi)) * u2)))
end
\begin{array}{l}

\\
\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)
\end{array}
Derivation
  1. Initial program 57.5%

    \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  2. Step-by-step derivation
    1. lift-log.f32N/A

      \[\leadsto \sqrt{-\color{blue}{\log \left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    2. lift--.f32N/A

      \[\leadsto \sqrt{-\log \color{blue}{\left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    3. sub-flipN/A

      \[\leadsto \sqrt{-\log \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. lower-log1p.f32N/A

      \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(\mathsf{neg}\left(u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    5. lower-neg.f3298.3

      \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  3. Applied rewrites98.3%

    \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  4. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{\left(2 \cdot \pi\right)} \cdot u2\right) \]
    2. count-2-revN/A

      \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
    3. lift-+.f3298.3

      \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
  5. Applied rewrites98.3%

    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
  6. Add Preprocessing

Alternative 2: 96.9% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ \mathbf{if}\;t\_0 \leq -0.0024999999441206455:\\ \;\;\;\;\sqrt{-t\_0} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (log (- 1.0 u1))))
   (if (<= t_0 -0.0024999999441206455)
     (* (sqrt (- t_0)) (sin (* (+ PI PI) u2)))
     (* (sqrt (* (fma 0.5 u1 1.0) u1)) (sin (* u2 (+ PI PI)))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = logf((1.0f - u1));
	float tmp;
	if (t_0 <= -0.0024999999441206455f) {
		tmp = sqrtf(-t_0) * sinf(((((float) M_PI) + ((float) M_PI)) * u2));
	} else {
		tmp = sqrtf((fmaf(0.5f, u1, 1.0f) * u1)) * sinf((u2 * (((float) M_PI) + ((float) M_PI))));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = log(Float32(Float32(1.0) - u1))
	tmp = Float32(0.0)
	if (t_0 <= Float32(-0.0024999999441206455))
		tmp = Float32(sqrt(Float32(-t_0)) * sin(Float32(Float32(Float32(pi) + Float32(pi)) * u2)));
	else
		tmp = Float32(sqrt(Float32(fma(Float32(0.5), u1, Float32(1.0)) * u1)) * sin(Float32(u2 * Float32(Float32(pi) + Float32(pi)))));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log \left(1 - u1\right)\\
\mathbf{if}\;t\_0 \leq -0.0024999999441206455:\\
\;\;\;\;\sqrt{-t\_0} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.00249999994

    1. Initial program 57.5%

      \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    2. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\color{blue}{\left(2 \cdot \pi\right)} \cdot u2\right) \]
      2. count-2-revN/A

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
      3. lower-+.f3257.5

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
    3. Applied rewrites57.5%

      \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \sin \color{blue}{\left(\left(\pi + \pi\right) \cdot u2\right)} \]

    if -0.00249999994 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

    1. Initial program 57.5%

      \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    2. Taylor expanded in u1 around 0

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      2. lower-+.f32N/A

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. lower-*.f32N/A

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \color{blue}{\left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. lower-+.f32N/A

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \color{blue}{u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      5. lower-*.f32N/A

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \color{blue}{\left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      6. lower-+.f32N/A

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \color{blue}{\frac{1}{4} \cdot u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      7. lower-*.f3293.4

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot \color{blue}{u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites93.4%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    5. Step-by-step derivation
      1. Applied rewrites93.4%

        \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.25, u1, 0.3333333333333333\right), u1, 0.5\right), u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)} \]
      2. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\mathsf{fma}\left(\frac{1}{2}, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
      3. Step-by-step derivation
        1. Applied rewrites88.0%

          \[\leadsto \sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
      4. Recombined 2 regimes into one program.
      5. Add Preprocessing

      Alternative 3: 95.0% accurate, 0.8× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ t_1 := \sqrt{-t\_0}\\ \mathbf{if}\;t\_0 \leq -0.006099999882280827:\\ \;\;\;\;u2 \cdot \mathsf{fma}\left(\pi + \pi, t\_1, \left(\left(\left(u2 \cdot u2\right) \cdot \left(\left(\pi \cdot \pi\right) \cdot \pi\right)\right) \cdot t\_1\right) \cdot -1.3333333333333333\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (let* ((t_0 (log (- 1.0 u1))) (t_1 (sqrt (- t_0))))
         (if (<= t_0 -0.006099999882280827)
           (*
            u2
            (fma
             (+ PI PI)
             t_1
             (* (* (* (* u2 u2) (* (* PI PI) PI)) t_1) -1.3333333333333333)))
           (* (sqrt (* (fma 0.5 u1 1.0) u1)) (sin (* u2 (+ PI PI)))))))
      float code(float cosTheta_i, float u1, float u2) {
      	float t_0 = logf((1.0f - u1));
      	float t_1 = sqrtf(-t_0);
      	float tmp;
      	if (t_0 <= -0.006099999882280827f) {
      		tmp = u2 * fmaf((((float) M_PI) + ((float) M_PI)), t_1, ((((u2 * u2) * ((((float) M_PI) * ((float) M_PI)) * ((float) M_PI))) * t_1) * -1.3333333333333333f));
      	} else {
      		tmp = sqrtf((fmaf(0.5f, u1, 1.0f) * u1)) * sinf((u2 * (((float) M_PI) + ((float) M_PI))));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	t_0 = log(Float32(Float32(1.0) - u1))
      	t_1 = sqrt(Float32(-t_0))
      	tmp = Float32(0.0)
      	if (t_0 <= Float32(-0.006099999882280827))
      		tmp = Float32(u2 * fma(Float32(Float32(pi) + Float32(pi)), t_1, Float32(Float32(Float32(Float32(u2 * u2) * Float32(Float32(Float32(pi) * Float32(pi)) * Float32(pi))) * t_1) * Float32(-1.3333333333333333))));
      	else
      		tmp = Float32(sqrt(Float32(fma(Float32(0.5), u1, Float32(1.0)) * u1)) * sin(Float32(u2 * Float32(Float32(pi) + Float32(pi)))));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \log \left(1 - u1\right)\\
      t_1 := \sqrt{-t\_0}\\
      \mathbf{if}\;t\_0 \leq -0.006099999882280827:\\
      \;\;\;\;u2 \cdot \mathsf{fma}\left(\pi + \pi, t\_1, \left(\left(\left(u2 \cdot u2\right) \cdot \left(\left(\pi \cdot \pi\right) \cdot \pi\right)\right) \cdot t\_1\right) \cdot -1.3333333333333333\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.00609999988

        1. Initial program 57.5%

          \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        2. Taylor expanded in u2 around 0

          \[\leadsto \color{blue}{u2 \cdot \left(\frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{3} \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) + 2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
        3. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto u2 \cdot \color{blue}{\left(\frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{3} \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) + 2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
          2. lower-fma.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{-4}{3}, \color{blue}{{u2}^{2} \cdot \left({\mathsf{PI}\left(\right)}^{3} \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}, 2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
        4. Applied rewrites53.6%

          \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(-1.3333333333333333, {u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right), 2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)} \]
        5. Step-by-step derivation
          1. lift-fma.f32N/A

            \[\leadsto u2 \cdot \left(\frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) + \color{blue}{2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)}\right) \]
          2. +-commutativeN/A

            \[\leadsto u2 \cdot \left(2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right) + \color{blue}{\frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)}\right) \]
          3. lift-*.f32N/A

            \[\leadsto u2 \cdot \left(2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right) + \color{blue}{\frac{-4}{3}} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          4. lift-*.f32N/A

            \[\leadsto u2 \cdot \left(2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right) + \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          5. associate-*r*N/A

            \[\leadsto u2 \cdot \left(\left(2 \cdot \pi\right) \cdot \sqrt{-\log \left(1 - u1\right)} + \color{blue}{\frac{-4}{3}} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          6. lift-*.f32N/A

            \[\leadsto u2 \cdot \left(\left(2 \cdot \pi\right) \cdot \sqrt{-\log \left(1 - u1\right)} + \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          7. lower-fma.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(2 \cdot \pi, \color{blue}{\sqrt{-\log \left(1 - u1\right)}}, \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          8. lift-*.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(2 \cdot \pi, \sqrt{\color{blue}{-\log \left(1 - u1\right)}}, \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          9. count-2-revN/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\pi + \pi, \sqrt{\color{blue}{-\log \left(1 - u1\right)}}, \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          10. lift-+.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\pi + \pi, \sqrt{\color{blue}{-\log \left(1 - u1\right)}}, \frac{-4}{3} \cdot \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\right) \]
          11. *-commutativeN/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\pi + \pi, \sqrt{-\log \left(1 - u1\right)}, \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \cdot \frac{-4}{3}\right) \]
          12. lower-*.f3253.6

            \[\leadsto u2 \cdot \mathsf{fma}\left(\pi + \pi, \sqrt{-\log \left(1 - u1\right)}, \left({u2}^{2} \cdot \left({\pi}^{3} \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \cdot -1.3333333333333333\right) \]
        6. Applied rewrites53.6%

          \[\leadsto u2 \cdot \mathsf{fma}\left(\pi + \pi, \color{blue}{\sqrt{-\log \left(1 - u1\right)}}, \left(\left(\left(u2 \cdot u2\right) \cdot \left(\left(\pi \cdot \pi\right) \cdot \pi\right)\right) \cdot \sqrt{-\log \left(1 - u1\right)}\right) \cdot -1.3333333333333333\right) \]

        if -0.00609999988 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

        1. Initial program 57.5%

          \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        2. Taylor expanded in u1 around 0

          \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        3. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          2. lower-+.f32N/A

            \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          3. lower-*.f32N/A

            \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \color{blue}{\left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          4. lower-+.f32N/A

            \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \color{blue}{u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          5. lower-*.f32N/A

            \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \color{blue}{\left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          6. lower-+.f32N/A

            \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \color{blue}{\frac{1}{4} \cdot u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          7. lower-*.f3293.4

            \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot \color{blue}{u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        4. Applied rewrites93.4%

          \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        5. Step-by-step derivation
          1. Applied rewrites93.4%

            \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.25, u1, 0.3333333333333333\right), u1, 0.5\right), u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)} \]
          2. Taylor expanded in u1 around 0

            \[\leadsto \sqrt{\mathsf{fma}\left(\frac{1}{2}, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
          3. Step-by-step derivation
            1. Applied rewrites88.0%

              \[\leadsto \sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
          4. Recombined 2 regimes into one program.
          5. Add Preprocessing

          Alternative 4: 94.2% accurate, 1.0× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.00018200000340584666:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\ \end{array} \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (if (<= u2 0.00018200000340584666)
             (* (sqrt (- (log1p (- u1)))) (* 2.0 (* u2 PI)))
             (* (sqrt (* (fma 0.5 u1 1.0) u1)) (sin (* u2 (+ PI PI))))))
          float code(float cosTheta_i, float u1, float u2) {
          	float tmp;
          	if (u2 <= 0.00018200000340584666f) {
          		tmp = sqrtf(-log1pf(-u1)) * (2.0f * (u2 * ((float) M_PI)));
          	} else {
          		tmp = sqrtf((fmaf(0.5f, u1, 1.0f) * u1)) * sinf((u2 * (((float) M_PI) + ((float) M_PI))));
          	}
          	return tmp;
          }
          
          function code(cosTheta_i, u1, u2)
          	tmp = Float32(0.0)
          	if (u2 <= Float32(0.00018200000340584666))
          		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))));
          	else
          		tmp = Float32(sqrt(Float32(fma(Float32(0.5), u1, Float32(1.0)) * u1)) * sin(Float32(u2 * Float32(Float32(pi) + Float32(pi)))));
          	end
          	return tmp
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;u2 \leq 0.00018200000340584666:\\
          \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if u2 < 1.82000003e-4

            1. Initial program 57.5%

              \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            2. Step-by-step derivation
              1. lift-log.f32N/A

                \[\leadsto \sqrt{-\color{blue}{\log \left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              2. lift--.f32N/A

                \[\leadsto \sqrt{-\log \color{blue}{\left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              3. sub-flipN/A

                \[\leadsto \sqrt{-\log \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              4. lower-log1p.f32N/A

                \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(\mathsf{neg}\left(u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              5. lower-neg.f3298.3

                \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            3. Applied rewrites98.3%

              \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            4. Taylor expanded in u2 around 0

              \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \mathsf{PI}\left(\right)\right)\right)} \]
            5. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \color{blue}{\left(u2 \cdot \mathsf{PI}\left(\right)\right)}\right) \]
              2. lower-*.f32N/A

                \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
              3. lower-PI.f3281.1

                \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
            6. Applied rewrites81.1%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \pi\right)\right)} \]

            if 1.82000003e-4 < u2

            1. Initial program 57.5%

              \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            2. Taylor expanded in u1 around 0

              \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            3. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              2. lower-+.f32N/A

                \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              3. lower-*.f32N/A

                \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \color{blue}{\left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              4. lower-+.f32N/A

                \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \color{blue}{u1 \cdot \left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              5. lower-*.f32N/A

                \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \color{blue}{\left(\frac{1}{3} + \frac{1}{4} \cdot u1\right)}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              6. lower-+.f32N/A

                \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + u1 \cdot \left(\frac{1}{3} + \color{blue}{\frac{1}{4} \cdot u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
              7. lower-*.f3293.4

                \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot \color{blue}{u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            4. Applied rewrites93.4%

              \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            5. Step-by-step derivation
              1. Applied rewrites93.4%

                \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.25, u1, 0.3333333333333333\right), u1, 0.5\right), u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right)} \]
              2. Taylor expanded in u1 around 0

                \[\leadsto \sqrt{\mathsf{fma}\left(\frac{1}{2}, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
              3. Step-by-step derivation
                1. Applied rewrites88.0%

                  \[\leadsto \sqrt{\mathsf{fma}\left(0.5, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot \left(\pi + \pi\right)\right) \]
              4. Recombined 2 regimes into one program.
              5. Add Preprocessing

              Alternative 5: 90.7% accurate, 1.1× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.0019000000320374966:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)\\ \end{array} \end{array} \]
              (FPCore (cosTheta_i u1 u2)
               :precision binary32
               (if (<= u2 0.0019000000320374966)
                 (* (sqrt (- (log1p (- u1)))) (* 2.0 (* u2 PI)))
                 (* (sqrt u1) (sin (* (+ PI PI) u2)))))
              float code(float cosTheta_i, float u1, float u2) {
              	float tmp;
              	if (u2 <= 0.0019000000320374966f) {
              		tmp = sqrtf(-log1pf(-u1)) * (2.0f * (u2 * ((float) M_PI)));
              	} else {
              		tmp = sqrtf(u1) * sinf(((((float) M_PI) + ((float) M_PI)) * u2));
              	}
              	return tmp;
              }
              
              function code(cosTheta_i, u1, u2)
              	tmp = Float32(0.0)
              	if (u2 <= Float32(0.0019000000320374966))
              		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))));
              	else
              		tmp = Float32(sqrt(u1) * sin(Float32(Float32(Float32(pi) + Float32(pi)) * u2)));
              	end
              	return tmp
              end
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              \mathbf{if}\;u2 \leq 0.0019000000320374966:\\
              \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\
              
              \mathbf{else}:\\
              \;\;\;\;\sqrt{u1} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if u2 < 0.00190000003

                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Step-by-step derivation
                  1. lift-log.f32N/A

                    \[\leadsto \sqrt{-\color{blue}{\log \left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  2. lift--.f32N/A

                    \[\leadsto \sqrt{-\log \color{blue}{\left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  3. sub-flipN/A

                    \[\leadsto \sqrt{-\log \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  4. lower-log1p.f32N/A

                    \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(\mathsf{neg}\left(u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  5. lower-neg.f3298.3

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                3. Applied rewrites98.3%

                  \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                4. Taylor expanded in u2 around 0

                  \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \mathsf{PI}\left(\right)\right)\right)} \]
                5. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \color{blue}{\left(u2 \cdot \mathsf{PI}\left(\right)\right)}\right) \]
                  2. lower-*.f32N/A

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
                  3. lower-PI.f3281.1

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
                6. Applied rewrites81.1%

                  \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \pi\right)\right)} \]

                if 0.00190000003 < u2

                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Taylor expanded in u1 around 0

                  \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                3. Step-by-step derivation
                  1. Applied rewrites76.6%

                    \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  2. Step-by-step derivation
                    1. lift-*.f32N/A

                      \[\leadsto \sqrt{u1} \cdot \sin \left(\color{blue}{\left(2 \cdot \pi\right)} \cdot u2\right) \]
                    2. count-2-revN/A

                      \[\leadsto \sqrt{u1} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
                    3. lift-+.f3276.6

                      \[\leadsto \sqrt{u1} \cdot \sin \left(\color{blue}{\left(\pi + \pi\right)} \cdot u2\right) \]
                  3. Applied rewrites76.6%

                    \[\leadsto \color{blue}{\sqrt{u1} \cdot \sin \left(\left(\pi + \pi\right) \cdot u2\right)} \]
                4. Recombined 2 regimes into one program.
                5. Add Preprocessing

                Alternative 6: 81.1% accurate, 2.3× speedup?

                \[\begin{array}{l} \\ \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (* (sqrt (- (log1p (- u1)))) (* 2.0 (* u2 PI))))
                float code(float cosTheta_i, float u1, float u2) {
                	return sqrtf(-log1pf(-u1)) * (2.0f * (u2 * ((float) M_PI)));
                }
                
                function code(cosTheta_i, u1, u2)
                	return Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))))
                end
                
                \begin{array}{l}
                
                \\
                \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)
                \end{array}
                
                Derivation
                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Step-by-step derivation
                  1. lift-log.f32N/A

                    \[\leadsto \sqrt{-\color{blue}{\log \left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  2. lift--.f32N/A

                    \[\leadsto \sqrt{-\log \color{blue}{\left(1 - u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  3. sub-flipN/A

                    \[\leadsto \sqrt{-\log \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  4. lower-log1p.f32N/A

                    \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(\mathsf{neg}\left(u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  5. lower-neg.f3298.3

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                3. Applied rewrites98.3%

                  \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                4. Taylor expanded in u2 around 0

                  \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \mathsf{PI}\left(\right)\right)\right)} \]
                5. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \color{blue}{\left(u2 \cdot \mathsf{PI}\left(\right)\right)}\right) \]
                  2. lower-*.f32N/A

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
                  3. lower-PI.f3281.1

                    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
                6. Applied rewrites81.1%

                  \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(2 \cdot \left(u2 \cdot \pi\right)\right)} \]
                7. Add Preprocessing

                Alternative 7: 76.7% accurate, 2.1× speedup?

                \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u1 \leq 0.00018000000272877514:\\ \;\;\;\;2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\\ \end{array} \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (if (<= u1 0.00018000000272877514)
                   (* 2.0 (* u2 (* u1 (* PI (/ (sqrt u1) u1)))))
                   (* 2.0 (* u2 (* PI (sqrt (- (log (- 1.0 u1)))))))))
                float code(float cosTheta_i, float u1, float u2) {
                	float tmp;
                	if (u1 <= 0.00018000000272877514f) {
                		tmp = 2.0f * (u2 * (u1 * (((float) M_PI) * (sqrtf(u1) / u1))));
                	} else {
                		tmp = 2.0f * (u2 * (((float) M_PI) * sqrtf(-logf((1.0f - u1)))));
                	}
                	return tmp;
                }
                
                function code(cosTheta_i, u1, u2)
                	tmp = Float32(0.0)
                	if (u1 <= Float32(0.00018000000272877514))
                		tmp = Float32(Float32(2.0) * Float32(u2 * Float32(u1 * Float32(Float32(pi) * Float32(sqrt(u1) / u1)))));
                	else
                		tmp = Float32(Float32(2.0) * Float32(u2 * Float32(Float32(pi) * sqrt(Float32(-log(Float32(Float32(1.0) - u1)))))));
                	end
                	return tmp
                end
                
                function tmp_2 = code(cosTheta_i, u1, u2)
                	tmp = single(0.0);
                	if (u1 <= single(0.00018000000272877514))
                		tmp = single(2.0) * (u2 * (u1 * (single(pi) * (sqrt(u1) / u1))));
                	else
                		tmp = single(2.0) * (u2 * (single(pi) * sqrt(-log((single(1.0) - u1)))));
                	end
                	tmp_2 = tmp;
                end
                
                \begin{array}{l}
                
                \\
                \begin{array}{l}
                \mathbf{if}\;u1 \leq 0.00018000000272877514:\\
                \;\;\;\;2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right)\\
                
                \mathbf{else}:\\
                \;\;\;\;2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if u1 < 1.80000003e-4

                  1. Initial program 57.5%

                    \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  2. Taylor expanded in u2 around 0

                    \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                  3. Step-by-step derivation
                    1. lower-*.f32N/A

                      \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                    2. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}\right) \]
                    3. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                    4. lower-PI.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\color{blue}{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                    5. lower-sqrt.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
                    6. lower-neg.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                    7. lower-log.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                    8. lower--.f3250.5

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  4. Applied rewrites50.5%

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

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                  6. Step-by-step derivation
                    1. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{u1}\right)\right) \]
                    2. lower-PI.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                    3. lower-sqrt.f3266.0

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                  7. Applied rewrites66.0%

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                  8. Taylor expanded in u1 around inf

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                  9. Step-by-step derivation
                    1. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                    2. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                    3. lower-PI.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                    4. lower-sqrt.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                    5. lower-/.f3266.0

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  10. Applied rewrites66.0%

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                  11. Taylor expanded in u1 around 0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                  12. Step-by-step derivation
                    1. lower-/.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                    2. lower-sqrt.f3265.9

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                  13. Applied rewrites65.9%

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]

                  if 1.80000003e-4 < u1

                  1. Initial program 57.5%

                    \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                  2. Taylor expanded in u2 around 0

                    \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                  3. Step-by-step derivation
                    1. lower-*.f32N/A

                      \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                    2. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}\right) \]
                    3. lower-*.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                    4. lower-PI.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\color{blue}{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                    5. lower-sqrt.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
                    6. lower-neg.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                    7. lower-log.f32N/A

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                    8. lower--.f3250.5

                      \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  4. Applied rewrites50.5%

                    \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right)} \]
                3. Recombined 2 regimes into one program.
                4. Add Preprocessing

                Alternative 8: 66.0% accurate, 2.9× speedup?

                \[\begin{array}{l} \\ 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (* 2.0 (* u2 (* u1 (* PI (/ (sqrt u1) u1))))))
                float code(float cosTheta_i, float u1, float u2) {
                	return 2.0f * (u2 * (u1 * (((float) M_PI) * (sqrtf(u1) / u1))));
                }
                
                function code(cosTheta_i, u1, u2)
                	return Float32(Float32(2.0) * Float32(u2 * Float32(u1 * Float32(Float32(pi) * Float32(sqrt(u1) / u1)))))
                end
                
                function tmp = code(cosTheta_i, u1, u2)
                	tmp = single(2.0) * (u2 * (u1 * (single(pi) * (sqrt(u1) / u1))));
                end
                
                \begin{array}{l}
                
                \\
                2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right)
                \end{array}
                
                Derivation
                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Taylor expanded in u2 around 0

                  \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                3. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                  2. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}\right) \]
                  3. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  4. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\color{blue}{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  5. lower-sqrt.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
                  6. lower-neg.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  7. lower-log.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  8. lower--.f3250.5

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                4. Applied rewrites50.5%

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

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                6. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{u1}\right)\right) \]
                  2. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                  3. lower-sqrt.f3266.0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                7. Applied rewrites66.0%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                8. Taylor expanded in u1 around inf

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                9. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  2. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  3. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  4. lower-sqrt.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  5. lower-/.f3266.0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                10. Applied rewrites66.0%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                11. Taylor expanded in u1 around 0

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                12. Step-by-step derivation
                  1. lower-/.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                  2. lower-sqrt.f3265.9

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                13. Applied rewrites65.9%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \frac{\sqrt{u1}}{u1}\right)\right)\right) \]
                14. Add Preprocessing

                Alternative 9: 66.0% accurate, 2.9× speedup?

                \[\begin{array}{l} \\ \left(\left(\left(\sqrt{\frac{1}{u1}} \cdot \pi\right) \cdot u1\right) \cdot u2\right) \cdot 2 \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (* (* (* (* (sqrt (/ 1.0 u1)) PI) u1) u2) 2.0))
                float code(float cosTheta_i, float u1, float u2) {
                	return (((sqrtf((1.0f / u1)) * ((float) M_PI)) * u1) * u2) * 2.0f;
                }
                
                function code(cosTheta_i, u1, u2)
                	return Float32(Float32(Float32(Float32(sqrt(Float32(Float32(1.0) / u1)) * Float32(pi)) * u1) * u2) * Float32(2.0))
                end
                
                function tmp = code(cosTheta_i, u1, u2)
                	tmp = (((sqrt((single(1.0) / u1)) * single(pi)) * u1) * u2) * single(2.0);
                end
                
                \begin{array}{l}
                
                \\
                \left(\left(\left(\sqrt{\frac{1}{u1}} \cdot \pi\right) \cdot u1\right) \cdot u2\right) \cdot 2
                \end{array}
                
                Derivation
                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Taylor expanded in u2 around 0

                  \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                3. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                  2. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}\right) \]
                  3. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  4. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\color{blue}{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  5. lower-sqrt.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
                  6. lower-neg.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  7. lower-log.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  8. lower--.f3250.5

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                4. Applied rewrites50.5%

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

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                6. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{u1}\right)\right) \]
                  2. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                  3. lower-sqrt.f3266.0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                7. Applied rewrites66.0%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                8. Taylor expanded in u1 around inf

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                9. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  2. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  3. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  4. lower-sqrt.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                  5. lower-/.f3266.0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \]
                10. Applied rewrites66.0%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \color{blue}{\sqrt{\frac{1}{u1}}}\right)\right)\right) \]
                11. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right)} \]
                  2. *-commutativeN/A

                    \[\leadsto \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \cdot \color{blue}{2} \]
                  3. lower-*.f3266.0

                    \[\leadsto \left(u2 \cdot \left(u1 \cdot \left(\pi \cdot \sqrt{\frac{1}{u1}}\right)\right)\right) \cdot \color{blue}{2} \]
                12. Applied rewrites66.0%

                  \[\leadsto \left(\left(\left(\sqrt{\frac{1}{u1}} \cdot \pi\right) \cdot u1\right) \cdot u2\right) \cdot \color{blue}{2} \]
                13. Add Preprocessing

                Alternative 10: 65.9% accurate, 4.5× speedup?

                \[\begin{array}{l} \\ 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \end{array} \]
                (FPCore (cosTheta_i u1 u2) :precision binary32 (* 2.0 (* u2 (* PI (sqrt u1)))))
                float code(float cosTheta_i, float u1, float u2) {
                	return 2.0f * (u2 * (((float) M_PI) * sqrtf(u1)));
                }
                
                function code(cosTheta_i, u1, u2)
                	return Float32(Float32(2.0) * Float32(u2 * Float32(Float32(pi) * sqrt(u1))))
                end
                
                function tmp = code(cosTheta_i, u1, u2)
                	tmp = single(2.0) * (u2 * (single(pi) * sqrt(u1)));
                end
                
                \begin{array}{l}
                
                \\
                2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right)
                \end{array}
                
                Derivation
                1. Initial program 57.5%

                  \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
                2. Taylor expanded in u2 around 0

                  \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                3. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \color{blue}{\left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
                  2. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)}\right) \]
                  3. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  4. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\color{blue}{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right)\right) \]
                  5. lower-sqrt.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right) \]
                  6. lower-neg.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  7. lower-log.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                  8. lower--.f3250.5

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{-\log \left(1 - u1\right)}\right)\right) \]
                4. Applied rewrites50.5%

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

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                6. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{u1}\right)\right) \]
                  2. lower-PI.f32N/A

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                  3. lower-sqrt.f3266.0

                    \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
                7. Applied rewrites66.0%

                  \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
                8. Add Preprocessing

                Reproduce

                ?
                herbie shell --seed 2025142 
                (FPCore (cosTheta_i u1 u2)
                  :name "Beckmann Sample, near normal, slope_y"
                  :precision binary32
                  :pre (and (and (and (> cosTheta_i 0.9999) (<= cosTheta_i 1.0)) (and (<= 2.328306437e-10 u1) (<= u1 1.0))) (and (<= 2.328306437e-10 u2) (<= u2 1.0)))
                  (* (sqrt (- (log (- 1.0 u1)))) (sin (* (* 2.0 PI) u2))))