Beckmann Sample, near normal, slope_y

Percentage Accurate: 56.8% → 98.4%
Time: 4.8s
Alternatives: 9
Speedup: 4.7×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
(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
\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)

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 9 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: 56.8% accurate, 1.0× speedup?

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

Alternative 1: 98.4% accurate, 1.0× speedup?

\[\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (- (log1p (- u1)))) (sin (* 6.2831854820251465 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf(-log1pf(-u1)) * sinf((6.2831854820251465f * u2));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(-log1p(Float32(-u1)))) * sin(Float32(Float32(6.2831854820251465) * u2)))
end
\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right)
Derivation
  1. Initial program 56.8%

    \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  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.f3298.4%

      \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  3. Applied rewrites98.4%

    \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
  4. Evaluated real constant98.4%

    \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
  5. Add Preprocessing

Alternative 2: 97.0% accurate, 0.9× speedup?

\[\begin{array}{l} t_0 := \log \left(1 - u1\right)\\ t_1 := \sin \left(6.2831854820251465 \cdot u2\right)\\ \mathbf{if}\;t\_0 \leq -0.003000000026077032:\\ \;\;\;\;\sqrt{-t\_0} \cdot t\_1\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot t\_1\\ \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (log (- 1.0 u1))) (t_1 (sin (* 6.2831854820251465 u2))))
   (if (<= t_0 -0.003000000026077032)
     (* (sqrt (- t_0)) t_1)
     (* (sqrt (fma 0.5 (* u1 u1) u1)) t_1))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = logf((1.0f - u1));
	float t_1 = sinf((6.2831854820251465f * u2));
	float tmp;
	if (t_0 <= -0.003000000026077032f) {
		tmp = sqrtf(-t_0) * t_1;
	} else {
		tmp = sqrtf(fmaf(0.5f, (u1 * u1), u1)) * t_1;
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = log(Float32(Float32(1.0) - u1))
	t_1 = sin(Float32(Float32(6.2831854820251465) * u2))
	tmp = Float32(0.0)
	if (t_0 <= Float32(-0.003000000026077032))
		tmp = Float32(sqrt(Float32(-t_0)) * t_1);
	else
		tmp = Float32(sqrt(fma(Float32(0.5), Float32(u1 * u1), u1)) * t_1);
	end
	return tmp
end
\begin{array}{l}
t_0 := \log \left(1 - u1\right)\\
t_1 := \sin \left(6.2831854820251465 \cdot u2\right)\\
\mathbf{if}\;t\_0 \leq -0.003000000026077032:\\
\;\;\;\;\sqrt{-t\_0} \cdot t\_1\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot t\_1\\


\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.00300000003

    1. Initial program 56.8%

      \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    2. Evaluated real constant56.8%

      \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]

    if -0.00300000003 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

    1. Initial program 56.8%

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

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

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

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \color{blue}{\frac{1}{3} \cdot u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      5. lower-*.f3291.9%

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot \color{blue}{u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites91.9%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    5. Step-by-step derivation
      1. lift-*.f32N/A

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

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

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

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

        \[\leadsto \sqrt{\left(u1 \cdot \left(\frac{1}{2} + \frac{1}{3} \cdot u1\right)\right) \cdot u1 + 1 \cdot u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      6. *-commutativeN/A

        \[\leadsto \sqrt{\left(\left(\frac{1}{2} + \frac{1}{3} \cdot u1\right) \cdot u1\right) \cdot u1 + 1 \cdot u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      7. associate-*l*N/A

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(\frac{1}{3} \cdot u1 + \frac{1}{2}, u1 \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      13. lower-fma.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3}, u1, \frac{1}{2}\right), \color{blue}{u1} \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      14. lower-*.f3291.9%

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, u1, 0.5\right), u1 \cdot \color{blue}{u1}, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    6. Applied rewrites91.9%

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(0.5, \color{blue}{u1} \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      2. Evaluated real constant88.3%

        \[\leadsto \sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
    9. Recombined 2 regimes into one program.
    10. Add Preprocessing

    Alternative 3: 96.4% accurate, 1.0× speedup?

    \[\begin{array}{l} \mathbf{if}\;u2 \leq 0.020999999716877937:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\ \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.020999999716877937)
       (*
        (sqrt (- (log1p (- u1))))
        (* u2 (+ 6.2831854820251465 (* -41.341705691712875 (pow u2 2.0)))))
       (* (sqrt (* u1 (+ 1.0 (* 0.5 u1)))) (sin (* 6.2831854820251465 u2)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if (u2 <= 0.020999999716877937f) {
    		tmp = sqrtf(-log1pf(-u1)) * (u2 * (6.2831854820251465f + (-41.341705691712875f * powf(u2, 2.0f))));
    	} else {
    		tmp = sqrtf((u1 * (1.0f + (0.5f * u1)))) * sinf((6.2831854820251465f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.020999999716877937))
    		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(u2 * Float32(Float32(6.2831854820251465) + Float32(Float32(-41.341705691712875) * (u2 ^ Float32(2.0))))));
    	else
    		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(Float32(0.5) * u1)))) * sin(Float32(Float32(6.2831854820251465) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.020999999716877937:\\
    \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\
    
    
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.0209999997

      1. Initial program 56.8%

        \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      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.f3298.4%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. Applied rewrites98.4%

        \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. Evaluated real constant98.4%

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
      5. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)\right)} \]
      6. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \color{blue}{\left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)}\right) \]
        2. lower-+.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \color{blue}{\frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}}\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot \color{blue}{{u2}^{2}}\right)\right) \]
        4. lower-pow.f3289.3%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{\color{blue}{2}}\right)\right) \]
      7. Applied rewrites89.3%

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)} \]

      if 0.0209999997 < u2

      1. Initial program 56.8%

        \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      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.f3298.4%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. Applied rewrites98.4%

        \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. Evaluated real constant98.4%

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
      5. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + \frac{1}{2} \cdot u1\right)}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
      6. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + \frac{1}{2} \cdot u1\right)}} \cdot \sin \left(\frac{13176795}{2097152} \cdot u2\right) \]
        2. lower-+.f32N/A

          \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{\frac{1}{2} \cdot u1}\right)} \cdot \sin \left(\frac{13176795}{2097152} \cdot u2\right) \]
        3. lower-*.f3288.3%

          \[\leadsto \sqrt{u1 \cdot \left(1 + 0.5 \cdot \color{blue}{u1}\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
      7. Applied rewrites88.3%

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + 0.5 \cdot u1\right)}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 4: 96.4% accurate, 1.0× speedup?

    \[\begin{array}{l} \mathbf{if}\;u2 \leq 0.020999999716877937:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\ \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.020999999716877937)
       (*
        (sqrt (- (log1p (- u1))))
        (* u2 (+ 6.2831854820251465 (* -41.341705691712875 (pow u2 2.0)))))
       (* (sqrt (fma 0.5 (* u1 u1) u1)) (sin (* 6.2831854820251465 u2)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if (u2 <= 0.020999999716877937f) {
    		tmp = sqrtf(-log1pf(-u1)) * (u2 * (6.2831854820251465f + (-41.341705691712875f * powf(u2, 2.0f))));
    	} else {
    		tmp = sqrtf(fmaf(0.5f, (u1 * u1), u1)) * sinf((6.2831854820251465f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.020999999716877937))
    		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(u2 * Float32(Float32(6.2831854820251465) + Float32(Float32(-41.341705691712875) * (u2 ^ Float32(2.0))))));
    	else
    		tmp = Float32(sqrt(fma(Float32(0.5), Float32(u1 * u1), u1)) * sin(Float32(Float32(6.2831854820251465) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.020999999716877937:\\
    \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\
    
    
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.0209999997

      1. Initial program 56.8%

        \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      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.f3298.4%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. Applied rewrites98.4%

        \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. Evaluated real constant98.4%

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
      5. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)\right)} \]
      6. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \color{blue}{\left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)}\right) \]
        2. lower-+.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \color{blue}{\frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}}\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot \color{blue}{{u2}^{2}}\right)\right) \]
        4. lower-pow.f3289.3%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{\color{blue}{2}}\right)\right) \]
      7. Applied rewrites89.3%

        \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)} \]

      if 0.0209999997 < u2

      1. Initial program 56.8%

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

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

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

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

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

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \color{blue}{\frac{1}{3} \cdot u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        5. lower-*.f3291.9%

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot \color{blue}{u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. Applied rewrites91.9%

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      5. Step-by-step derivation
        1. lift-*.f32N/A

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

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

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

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

          \[\leadsto \sqrt{\left(u1 \cdot \left(\frac{1}{2} + \frac{1}{3} \cdot u1\right)\right) \cdot u1 + 1 \cdot u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        6. *-commutativeN/A

          \[\leadsto \sqrt{\left(\left(\frac{1}{2} + \frac{1}{3} \cdot u1\right) \cdot u1\right) \cdot u1 + 1 \cdot u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        7. associate-*l*N/A

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

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

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

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

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

          \[\leadsto \sqrt{\mathsf{fma}\left(\frac{1}{3} \cdot u1 + \frac{1}{2}, u1 \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        13. lower-fma.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{3}, u1, \frac{1}{2}\right), \color{blue}{u1} \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        14. lower-*.f3291.9%

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(0.3333333333333333, u1, 0.5\right), u1 \cdot \color{blue}{u1}, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      6. Applied rewrites91.9%

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

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

          \[\leadsto \sqrt{\mathsf{fma}\left(0.5, \color{blue}{u1} \cdot u1, u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        2. Evaluated real constant88.3%

          \[\leadsto \sqrt{\mathsf{fma}\left(0.5, u1 \cdot u1, u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
      9. Recombined 2 regimes into one program.
      10. Add Preprocessing

      Alternative 5: 94.4% accurate, 1.2× speedup?

      \[\begin{array}{l} \mathbf{if}\;u2 \leq 0.02500000037252903:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\ \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.02500000037252903)
         (*
          (sqrt (- (log1p (- u1))))
          (* u2 (+ 6.2831854820251465 (* -41.341705691712875 (pow u2 2.0)))))
         (* (sqrt u1) (sin (* 6.2831854820251465 u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.02500000037252903f) {
      		tmp = sqrtf(-log1pf(-u1)) * (u2 * (6.2831854820251465f + (-41.341705691712875f * powf(u2, 2.0f))));
      	} else {
      		tmp = sqrtf(u1) * sinf((6.2831854820251465f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.02500000037252903))
      		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(u2 * Float32(Float32(6.2831854820251465) + Float32(Float32(-41.341705691712875) * (u2 ^ Float32(2.0))))));
      	else
      		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.2831854820251465) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.02500000037252903:\\
      \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{u1} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\
      
      
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0250000004

        1. Initial program 56.8%

          \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        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.f3298.4%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        3. Applied rewrites98.4%

          \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        4. Evaluated real constant98.4%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
        5. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)\right)} \]
        6. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \color{blue}{\left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}\right)}\right) \]
          2. lower-+.f32N/A

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \color{blue}{\frac{-762619864465648886625}{18446744073709551616} \cdot {u2}^{2}}\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(\frac{13176795}{2097152} + \frac{-762619864465648886625}{18446744073709551616} \cdot \color{blue}{{u2}^{2}}\right)\right) \]
          4. lower-pow.f3289.3%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{\color{blue}{2}}\right)\right) \]
        7. Applied rewrites89.3%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(6.2831854820251465 + -41.341705691712875 \cdot {u2}^{2}\right)\right)} \]

        if 0.0250000004 < u2

        1. Initial program 56.8%

          \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        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.f3298.4%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        3. Applied rewrites98.4%

          \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
        4. Evaluated real constant98.4%

          \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
        5. Taylor expanded in u1 around 0

          \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
        6. Step-by-step derivation
          1. Applied rewrites77.2%

            \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
        7. Recombined 2 regimes into one program.
        8. Add Preprocessing

        Alternative 6: 90.8% accurate, 1.2× speedup?

        \[\begin{array}{l} \mathbf{if}\;u2 \leq 0.003000000026077032:\\ \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot u2\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\ \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (if (<= u2 0.003000000026077032)
           (* (sqrt (- (log1p (- u1)))) (* 6.2831854820251465 u2))
           (* (sqrt u1) (sin (* 6.2831854820251465 u2)))))
        float code(float cosTheta_i, float u1, float u2) {
        	float tmp;
        	if (u2 <= 0.003000000026077032f) {
        		tmp = sqrtf(-log1pf(-u1)) * (6.2831854820251465f * u2);
        	} else {
        		tmp = sqrtf(u1) * sinf((6.2831854820251465f * u2));
        	}
        	return tmp;
        }
        
        function code(cosTheta_i, u1, u2)
        	tmp = Float32(0.0)
        	if (u2 <= Float32(0.003000000026077032))
        		tmp = Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(Float32(6.2831854820251465) * u2));
        	else
        		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.2831854820251465) * u2)));
        	end
        	return tmp
        end
        
        \begin{array}{l}
        \mathbf{if}\;u2 \leq 0.003000000026077032:\\
        \;\;\;\;\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot u2\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\sqrt{u1} \cdot \sin \left(6.2831854820251465 \cdot u2\right)\\
        
        
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if u2 < 0.00300000003

          1. Initial program 56.8%

            \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          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.f3298.4%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          3. Applied rewrites98.4%

            \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          4. Evaluated real constant98.4%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
          5. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(\frac{13176795}{2097152} \cdot u2\right)} \]
          6. Step-by-step derivation
            1. lower-*.f3281.6%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot \color{blue}{u2}\right) \]
          7. Applied rewrites81.6%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(6.2831854820251465 \cdot u2\right)} \]

          if 0.00300000003 < u2

          1. Initial program 56.8%

            \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          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.f3298.4%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          3. Applied rewrites98.4%

            \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          4. Evaluated real constant98.4%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
          5. Taylor expanded in u1 around 0

            \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
          6. Step-by-step derivation
            1. Applied rewrites77.2%

              \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(6.2831854820251465 \cdot u2\right) \]
          7. Recombined 2 regimes into one program.
          8. Add Preprocessing

          Alternative 7: 81.6% accurate, 2.6× speedup?

          \[\sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot u2\right) \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (* (sqrt (- (log1p (- u1)))) (* 6.2831854820251465 u2)))
          float code(float cosTheta_i, float u1, float u2) {
          	return sqrtf(-log1pf(-u1)) * (6.2831854820251465f * u2);
          }
          
          function code(cosTheta_i, u1, u2)
          	return Float32(sqrt(Float32(-log1p(Float32(-u1)))) * Float32(Float32(6.2831854820251465) * u2))
          end
          
          \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot u2\right)
          
          Derivation
          1. Initial program 56.8%

            \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          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.f3298.4%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          3. Applied rewrites98.4%

            \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
          4. Evaluated real constant98.4%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
          5. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(\frac{13176795}{2097152} \cdot u2\right)} \]
          6. Step-by-step derivation
            1. lower-*.f3281.6%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \left(6.2831854820251465 \cdot \color{blue}{u2}\right) \]
          7. Applied rewrites81.6%

            \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \color{blue}{\left(6.2831854820251465 \cdot u2\right)} \]
          8. Add Preprocessing

          Alternative 8: 77.3% accurate, 1.8× speedup?

          \[\begin{array}{l} t_0 := \log \left(1 - u1\right)\\ \mathbf{if}\;t\_0 \leq -0.0002099999983329326:\\ \;\;\;\;6.2831854820251465 \cdot \left(u2 \cdot \sqrt{-t\_0}\right)\\ \mathbf{else}:\\ \;\;\;\;\left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right)\\ \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (let* ((t_0 (log (- 1.0 u1))))
             (if (<= t_0 -0.0002099999983329326)
               (* 6.2831854820251465 (* u2 (sqrt (- t_0))))
               (* (+ u2 u2) (* (sqrt u1) PI)))))
          float code(float cosTheta_i, float u1, float u2) {
          	float t_0 = logf((1.0f - u1));
          	float tmp;
          	if (t_0 <= -0.0002099999983329326f) {
          		tmp = 6.2831854820251465f * (u2 * sqrtf(-t_0));
          	} else {
          		tmp = (u2 + u2) * (sqrtf(u1) * ((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(-0.0002099999983329326))
          		tmp = Float32(Float32(6.2831854820251465) * Float32(u2 * sqrt(Float32(-t_0))));
          	else
          		tmp = Float32(Float32(u2 + u2) * Float32(sqrt(u1) * Float32(pi)));
          	end
          	return tmp
          end
          
          function tmp_2 = code(cosTheta_i, u1, u2)
          	t_0 = log((single(1.0) - u1));
          	tmp = single(0.0);
          	if (t_0 <= single(-0.0002099999983329326))
          		tmp = single(6.2831854820251465) * (u2 * sqrt(-t_0));
          	else
          		tmp = (u2 + u2) * (sqrt(u1) * single(pi));
          	end
          	tmp_2 = tmp;
          end
          
          \begin{array}{l}
          t_0 := \log \left(1 - u1\right)\\
          \mathbf{if}\;t\_0 \leq -0.0002099999983329326:\\
          \;\;\;\;6.2831854820251465 \cdot \left(u2 \cdot \sqrt{-t\_0}\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right)\\
          
          
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -2.09999998e-4

            1. Initial program 56.8%

              \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            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.f3298.4%

                \[\leadsto \sqrt{-\mathsf{log1p}\left(\color{blue}{-u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            3. Applied rewrites98.4%

              \[\leadsto \sqrt{-\color{blue}{\mathsf{log1p}\left(-u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
            4. Evaluated real constant98.4%

              \[\leadsto \sqrt{-\mathsf{log1p}\left(-u1\right)} \cdot \sin \left(\color{blue}{6.2831854820251465} \cdot u2\right) \]
            5. Taylor expanded in u2 around 0

              \[\leadsto \color{blue}{\frac{13176795}{2097152} \cdot \left(u2 \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)} \]
            6. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \frac{13176795}{2097152} \cdot \color{blue}{\left(u2 \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)} \]
              2. lower-*.f32N/A

                \[\leadsto \frac{13176795}{2097152} \cdot \left(u2 \cdot \color{blue}{\sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}}\right) \]
              3. lower-sqrt.f32N/A

                \[\leadsto \frac{13176795}{2097152} \cdot \left(u2 \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right) \]
              4. lower-neg.f32N/A

                \[\leadsto \frac{13176795}{2097152} \cdot \left(u2 \cdot \sqrt{-\log \left(1 - u1\right)}\right) \]
              5. lower-log.f32N/A

                \[\leadsto \frac{13176795}{2097152} \cdot \left(u2 \cdot \sqrt{-\log \left(1 - u1\right)}\right) \]
              6. lower--.f3250.1%

                \[\leadsto 6.2831854820251465 \cdot \left(u2 \cdot \sqrt{-\log \left(1 - u1\right)}\right) \]
            7. Applied rewrites50.1%

              \[\leadsto \color{blue}{6.2831854820251465 \cdot \left(u2 \cdot \sqrt{-\log \left(1 - u1\right)}\right)} \]

            if -2.09999998e-4 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

            1. Initial program 56.8%

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

              \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
            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--.f3250.1%

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

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

              \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
            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.f3266.8%

                \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
            7. Applied rewrites66.8%

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

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

                \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\pi \cdot \sqrt{u1}\right)}\right) \]
              3. associate-*r*N/A

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

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

                \[\leadsto \left(u2 + u2\right) \cdot \left(\color{blue}{\pi} \cdot \sqrt{u1}\right) \]
              6. lower-+.f3266.8%

                \[\leadsto \left(u2 + u2\right) \cdot \left(\color{blue}{\pi} \cdot \sqrt{u1}\right) \]
              7. lift-*.f32N/A

                \[\leadsto \left(u2 + u2\right) \cdot \left(\pi \cdot \sqrt{u1}\right) \]
              8. *-commutativeN/A

                \[\leadsto \left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right) \]
              9. lower-*.f3266.8%

                \[\leadsto \left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right) \]
            9. Applied rewrites66.8%

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

          Alternative 9: 66.8% accurate, 4.7× speedup?

          \[\left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right) \]
          (FPCore (cosTheta_i u1 u2) :precision binary32 (* (+ u2 u2) (* (sqrt u1) PI)))
          float code(float cosTheta_i, float u1, float u2) {
          	return (u2 + u2) * (sqrtf(u1) * ((float) M_PI));
          }
          
          function code(cosTheta_i, u1, u2)
          	return Float32(Float32(u2 + u2) * Float32(sqrt(u1) * Float32(pi)))
          end
          
          function tmp = code(cosTheta_i, u1, u2)
          	tmp = (u2 + u2) * (sqrt(u1) * single(pi));
          end
          
          \left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right)
          
          Derivation
          1. Initial program 56.8%

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

            \[\leadsto \color{blue}{2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{\mathsf{neg}\left(\log \left(1 - u1\right)\right)}\right)\right)} \]
          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--.f3250.1%

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

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

            \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \color{blue}{\sqrt{u1}}\right)\right) \]
          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.f3266.8%

              \[\leadsto 2 \cdot \left(u2 \cdot \left(\pi \cdot \sqrt{u1}\right)\right) \]
          7. Applied rewrites66.8%

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

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

              \[\leadsto 2 \cdot \left(u2 \cdot \color{blue}{\left(\pi \cdot \sqrt{u1}\right)}\right) \]
            3. associate-*r*N/A

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

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

              \[\leadsto \left(u2 + u2\right) \cdot \left(\color{blue}{\pi} \cdot \sqrt{u1}\right) \]
            6. lower-+.f3266.8%

              \[\leadsto \left(u2 + u2\right) \cdot \left(\color{blue}{\pi} \cdot \sqrt{u1}\right) \]
            7. lift-*.f32N/A

              \[\leadsto \left(u2 + u2\right) \cdot \left(\pi \cdot \sqrt{u1}\right) \]
            8. *-commutativeN/A

              \[\leadsto \left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right) \]
            9. lower-*.f3266.8%

              \[\leadsto \left(u2 + u2\right) \cdot \left(\sqrt{u1} \cdot \pi\right) \]
          9. Applied rewrites66.8%

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

          Reproduce

          ?
          herbie shell --seed 2025191 
          (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))))