Beckmann Sample, near normal, slope_y

Percentage Accurate: 57.8% → 98.2%
Time: 3.7s
Alternatives: 11
Speedup: 3.4×

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 11 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: 57.8% 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: 98.2% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \mathbf{if}\;u1 \leq 0.03999999910593033:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot u1\right)\right)\right)} \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sin (* (* 2.0 PI) u2))))
   (if (<= u1 0.03999999910593033)
     (*
      (sqrt
       (* u1 (+ 1.0 (* u1 (+ 0.5 (* u1 (+ 0.3333333333333333 (* 0.25 u1))))))))
      t_0)
     (* (sqrt (- (log (- 1.0 u1)))) t_0))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sinf(((2.0f * ((float) M_PI)) * u2));
	float tmp;
	if (u1 <= 0.03999999910593033f) {
		tmp = sqrtf((u1 * (1.0f + (u1 * (0.5f + (u1 * (0.3333333333333333f + (0.25f * u1)))))))) * t_0;
	} else {
		tmp = sqrtf(-logf((1.0f - u1))) * t_0;
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2))
	tmp = Float32(0.0)
	if (u1 <= Float32(0.03999999910593033))
		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(u1 * Float32(Float32(0.5) + Float32(u1 * Float32(Float32(0.3333333333333333) + Float32(Float32(0.25) * u1)))))))) * t_0);
	else
		tmp = Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * t_0);
	end
	return tmp
end
function tmp_2 = code(cosTheta_i, u1, u2)
	t_0 = sin(((single(2.0) * single(pi)) * u2));
	tmp = single(0.0);
	if (u1 <= single(0.03999999910593033))
		tmp = sqrt((u1 * (single(1.0) + (u1 * (single(0.5) + (u1 * (single(0.3333333333333333) + (single(0.25) * u1)))))))) * t_0;
	else
		tmp = sqrt(-log((single(1.0) - u1))) * t_0;
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\
\mathbf{if}\;u1 \leq 0.03999999910593033:\\
\;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot u1\right)\right)\right)} \cdot t\_0\\

\mathbf{else}:\\
\;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u1 < 0.0399999991

    1. Initial program 57.8%

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + u1 \cdot \left(0.3333333333333333 + 0.25 \cdot \color{blue}{u1}\right)\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites93.3%

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

    if 0.0399999991 < u1

    1. Initial program 57.8%

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

Alternative 2: 97.9% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \mathbf{if}\;u1 \leq 0.017999999225139618:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sin (* (* 2.0 PI) u2))))
   (if (<= u1 0.017999999225139618)
     (* (sqrt (* u1 (+ 1.0 (* u1 (+ 0.5 (* 0.3333333333333333 u1)))))) t_0)
     (* (sqrt (- (log (- 1.0 u1)))) t_0))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sinf(((2.0f * ((float) M_PI)) * u2));
	float tmp;
	if (u1 <= 0.017999999225139618f) {
		tmp = sqrtf((u1 * (1.0f + (u1 * (0.5f + (0.3333333333333333f * u1)))))) * t_0;
	} else {
		tmp = sqrtf(-logf((1.0f - u1))) * t_0;
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2))
	tmp = Float32(0.0)
	if (u1 <= Float32(0.017999999225139618))
		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(u1 * Float32(Float32(0.5) + Float32(Float32(0.3333333333333333) * u1)))))) * t_0);
	else
		tmp = Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * t_0);
	end
	return tmp
end
function tmp_2 = code(cosTheta_i, u1, u2)
	t_0 = sin(((single(2.0) * single(pi)) * u2));
	tmp = single(0.0);
	if (u1 <= single(0.017999999225139618))
		tmp = sqrt((u1 * (single(1.0) + (u1 * (single(0.5) + (single(0.3333333333333333) * u1)))))) * t_0;
	else
		tmp = sqrt(-log((single(1.0) - u1))) * t_0;
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\
\mathbf{if}\;u1 \leq 0.017999999225139618:\\
\;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot t\_0\\

\mathbf{else}:\\
\;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u1 < 0.0179999992

    1. Initial program 57.8%

      \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    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-*.f3291.5

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot \color{blue}{u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites91.5%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]

    if 0.0179999992 < u1

    1. Initial program 57.8%

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

Alternative 3: 97.0% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \mathbf{if}\;u1 \leq 0.003000000026077032:\\ \;\;\;\;\sqrt{u1 \cdot \left(u1 \cdot \left(0.5 + \frac{1}{u1}\right)\right)} \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sin (* (* 2.0 PI) u2))))
   (if (<= u1 0.003000000026077032)
     (* (sqrt (* u1 (* u1 (+ 0.5 (/ 1.0 u1))))) t_0)
     (* (sqrt (- (log (- 1.0 u1)))) t_0))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sinf(((2.0f * ((float) M_PI)) * u2));
	float tmp;
	if (u1 <= 0.003000000026077032f) {
		tmp = sqrtf((u1 * (u1 * (0.5f + (1.0f / u1))))) * t_0;
	} else {
		tmp = sqrtf(-logf((1.0f - u1))) * t_0;
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2))
	tmp = Float32(0.0)
	if (u1 <= Float32(0.003000000026077032))
		tmp = Float32(sqrt(Float32(u1 * Float32(u1 * Float32(Float32(0.5) + Float32(Float32(1.0) / u1))))) * t_0);
	else
		tmp = Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * t_0);
	end
	return tmp
end
function tmp_2 = code(cosTheta_i, u1, u2)
	t_0 = sin(((single(2.0) * single(pi)) * u2));
	tmp = single(0.0);
	if (u1 <= single(0.003000000026077032))
		tmp = sqrt((u1 * (u1 * (single(0.5) + (single(1.0) / u1))))) * t_0;
	else
		tmp = sqrt(-log((single(1.0) - u1))) * t_0;
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\
\mathbf{if}\;u1 \leq 0.003000000026077032:\\
\;\;\;\;\sqrt{u1 \cdot \left(u1 \cdot \left(0.5 + \frac{1}{u1}\right)\right)} \cdot t\_0\\

\mathbf{else}:\\
\;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u1 < 0.00300000003

    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{\frac{1}{2} \cdot u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. lower-*.f3287.8

        \[\leadsto \sqrt{u1 \cdot \left(1 + 0.5 \cdot \color{blue}{u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites87.8%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + 0.5 \cdot u1\right)}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    5. Taylor expanded in u1 around inf

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

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

        \[\leadsto \sqrt{u1 \cdot \left(u1 \cdot \left(\frac{1}{2} + \frac{1}{\color{blue}{u1}}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. lower-/.f3287.8

        \[\leadsto \sqrt{u1 \cdot \left(u1 \cdot \left(0.5 + \frac{1}{u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    7. Applied rewrites87.8%

      \[\leadsto \sqrt{u1 \cdot \left(u1 \cdot \color{blue}{\left(0.5 + \frac{1}{u1}\right)}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]

    if 0.00300000003 < u1

    1. Initial program 57.8%

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

Alternative 4: 96.9% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ t_1 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \mathbf{if}\;t\_0 \leq -0.003000000026077032:\\ \;\;\;\;\sqrt{-t\_0} \cdot t\_1\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot t\_1\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (log (- 1.0 u1))) (t_1 (sin (* (* 2.0 PI) u2))))
   (if (<= t_0 -0.003000000026077032)
     (* (sqrt (- t_0)) t_1)
     (* (sqrt (* u1 (+ 1.0 (* 0.5 u1)))) t_1))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = logf((1.0f - u1));
	float t_1 = sinf(((2.0f * ((float) M_PI)) * u2));
	float tmp;
	if (t_0 <= -0.003000000026077032f) {
		tmp = sqrtf(-t_0) * t_1;
	} else {
		tmp = sqrtf((u1 * (1.0f + (0.5f * u1)))) * t_1;
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = log(Float32(Float32(1.0) - u1))
	t_1 = sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2))
	tmp = Float32(0.0)
	if (t_0 <= Float32(-0.003000000026077032))
		tmp = Float32(sqrt(Float32(-t_0)) * t_1);
	else
		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(Float32(0.5) * u1)))) * t_1);
	end
	return tmp
end
function tmp_2 = code(cosTheta_i, u1, u2)
	t_0 = log((single(1.0) - u1));
	t_1 = sin(((single(2.0) * single(pi)) * u2));
	tmp = single(0.0);
	if (t_0 <= single(-0.003000000026077032))
		tmp = sqrt(-t_0) * t_1;
	else
		tmp = sqrt((u1 * (single(1.0) + (single(0.5) * u1)))) * t_1;
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log \left(1 - u1\right)\\
t_1 := \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\
\mathbf{if}\;t\_0 \leq -0.003000000026077032:\\
\;\;\;\;\sqrt{-t\_0} \cdot t\_1\\

\mathbf{else}:\\
\;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot t\_1\\


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

    1. Initial program 57.8%

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

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

    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{\frac{1}{2} \cdot u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. lower-*.f3287.8

        \[\leadsto \sqrt{u1 \cdot \left(1 + 0.5 \cdot \color{blue}{u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites87.8%

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

Alternative 5: 93.0% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ \mathbf{if}\;t\_0 \leq -0.017500000074505806:\\ \;\;\;\;\sqrt{-t\_0} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (log (- 1.0 u1))))
   (if (<= t_0 -0.017500000074505806)
     (* (sqrt (- t_0)) (* 2.0 (* u2 PI)))
     (* (sqrt (* u1 (+ 1.0 (* 0.5 u1)))) (sin (* (* 2.0 PI) u2))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = logf((1.0f - u1));
	float tmp;
	if (t_0 <= -0.017500000074505806f) {
		tmp = sqrtf(-t_0) * (2.0f * (u2 * ((float) M_PI)));
	} else {
		tmp = sqrtf((u1 * (1.0f + (0.5f * u1)))) * sinf(((2.0f * ((float) M_PI)) * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = log(Float32(Float32(1.0) - u1))
	tmp = Float32(0.0)
	if (t_0 <= Float32(-0.017500000074505806))
		tmp = Float32(sqrt(Float32(-t_0)) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))));
	else
		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(Float32(0.5) * u1)))) * sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2)));
	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(-0.017500000074505806))
		tmp = sqrt(-t_0) * (single(2.0) * (u2 * single(pi)));
	else
		tmp = sqrt((u1 * (single(1.0) + (single(0.5) * u1)))) * sin(((single(2.0) * single(pi)) * u2));
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log \left(1 - u1\right)\\
\mathbf{if}\;t\_0 \leq -0.017500000074505806:\\
\;\;\;\;\sqrt{-t\_0} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\sqrt{u1 \cdot \left(1 + 0.5 \cdot u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.0175000001

    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
      3. lift-PI.f3250.6

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    4. Applied rewrites50.6%

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

    if -0.0175000001 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{\frac{1}{2} \cdot u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      3. lower-*.f3287.8

        \[\leadsto \sqrt{u1 \cdot \left(1 + 0.5 \cdot \color{blue}{u1}\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    4. Applied rewrites87.8%

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

Alternative 6: 87.0% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.0024999999441206455:\\ \;\;\;\;\sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= u2 0.0024999999441206455)
   (*
    (sqrt
     (-
      (*
       u1
       (- (* u1 (- (* u1 (- (* -0.25 u1) 0.3333333333333333)) 0.5)) 1.0))))
    (* 2.0 (* u2 PI)))
   (* (sqrt u1) (sin (* (* 2.0 PI) u2)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if (u2 <= 0.0024999999441206455f) {
		tmp = sqrtf(-(u1 * ((u1 * ((u1 * ((-0.25f * u1) - 0.3333333333333333f)) - 0.5f)) - 1.0f))) * (2.0f * (u2 * ((float) M_PI)));
	} else {
		tmp = sqrtf(u1) * sinf(((2.0f * ((float) M_PI)) * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (u2 <= Float32(0.0024999999441206455))
		tmp = Float32(sqrt(Float32(-Float32(u1 * Float32(Float32(u1 * Float32(Float32(u1 * Float32(Float32(Float32(-0.25) * u1) - Float32(0.3333333333333333))) - Float32(0.5))) - Float32(1.0))))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))));
	else
		tmp = Float32(sqrt(u1) * sin(Float32(Float32(Float32(2.0) * Float32(pi)) * u2)));
	end
	return tmp
end
function tmp_2 = code(cosTheta_i, u1, u2)
	tmp = single(0.0);
	if (u2 <= single(0.0024999999441206455))
		tmp = sqrt(-(u1 * ((u1 * ((u1 * ((single(-0.25) * u1) - single(0.3333333333333333))) - single(0.5))) - single(1.0)))) * (single(2.0) * (u2 * single(pi)));
	else
		tmp = sqrt(u1) * sin(((single(2.0) * single(pi)) * u2));
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;u2 \leq 0.0024999999441206455:\\
\;\;\;\;\sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\sqrt{u1} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.00249999994

    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
      3. lift-PI.f3250.6

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    4. Applied rewrites50.6%

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

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

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

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

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

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

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

        \[\leadsto \sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(\frac{-1}{4} \cdot u1 - \frac{1}{3}\right) - \frac{1}{2}\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      7. lower-*.f3277.7

        \[\leadsto \sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    7. Applied rewrites77.7%

      \[\leadsto \sqrt{-\color{blue}{u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]

    if 0.00249999994 < u2

    1. Initial program 57.8%

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

      \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
    3. Step-by-step derivation
      1. Applied rewrites76.4%

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

    Alternative 7: 81.2% accurate, 1.2× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ t_1 := 2 \cdot \left(u2 \cdot \pi\right)\\ \mathbf{if}\;t\_0 \leq -0.029999999329447746:\\ \;\;\;\;\sqrt{-t\_0} \cdot t\_1\\ \mathbf{else}:\\ \;\;\;\;\sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot t\_1\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (log (- 1.0 u1))) (t_1 (* 2.0 (* u2 PI))))
       (if (<= t_0 -0.029999999329447746)
         (* (sqrt (- t_0)) t_1)
         (*
          (sqrt
           (-
            (*
             u1
             (- (* u1 (- (* u1 (- (* -0.25 u1) 0.3333333333333333)) 0.5)) 1.0))))
          t_1))))
    float code(float cosTheta_i, float u1, float u2) {
    	float t_0 = logf((1.0f - u1));
    	float t_1 = 2.0f * (u2 * ((float) M_PI));
    	float tmp;
    	if (t_0 <= -0.029999999329447746f) {
    		tmp = sqrtf(-t_0) * t_1;
    	} else {
    		tmp = sqrtf(-(u1 * ((u1 * ((u1 * ((-0.25f * u1) - 0.3333333333333333f)) - 0.5f)) - 1.0f))) * t_1;
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	t_0 = log(Float32(Float32(1.0) - u1))
    	t_1 = Float32(Float32(2.0) * Float32(u2 * Float32(pi)))
    	tmp = Float32(0.0)
    	if (t_0 <= Float32(-0.029999999329447746))
    		tmp = Float32(sqrt(Float32(-t_0)) * t_1);
    	else
    		tmp = Float32(sqrt(Float32(-Float32(u1 * Float32(Float32(u1 * Float32(Float32(u1 * Float32(Float32(Float32(-0.25) * u1) - Float32(0.3333333333333333))) - Float32(0.5))) - Float32(1.0))))) * t_1);
    	end
    	return tmp
    end
    
    function tmp_2 = code(cosTheta_i, u1, u2)
    	t_0 = log((single(1.0) - u1));
    	t_1 = single(2.0) * (u2 * single(pi));
    	tmp = single(0.0);
    	if (t_0 <= single(-0.029999999329447746))
    		tmp = sqrt(-t_0) * t_1;
    	else
    		tmp = sqrt(-(u1 * ((u1 * ((u1 * ((single(-0.25) * u1) - single(0.3333333333333333))) - single(0.5))) - single(1.0)))) * t_1;
    	end
    	tmp_2 = tmp;
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \log \left(1 - u1\right)\\
    t_1 := 2 \cdot \left(u2 \cdot \pi\right)\\
    \mathbf{if}\;t\_0 \leq -0.029999999329447746:\\
    \;\;\;\;\sqrt{-t\_0} \cdot t\_1\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot t\_1\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.0299999993

      1. Initial program 57.8%

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

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

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

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        3. lift-PI.f3250.6

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      4. Applied rewrites50.6%

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

      if -0.0299999993 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

      1. Initial program 57.8%

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

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

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

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        3. lift-PI.f3250.6

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      4. Applied rewrites50.6%

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

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

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

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

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

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

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

          \[\leadsto \sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(\frac{-1}{4} \cdot u1 - \frac{1}{3}\right) - \frac{1}{2}\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
        7. lower-*.f3277.7

          \[\leadsto \sqrt{-u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      7. Applied rewrites77.7%

        \[\leadsto \sqrt{-\color{blue}{u1 \cdot \left(u1 \cdot \left(u1 \cdot \left(-0.25 \cdot u1 - 0.3333333333333333\right) - 0.5\right) - 1\right)}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 8: 81.0% accurate, 1.4× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \left(1 - u1\right)\\ \mathbf{if}\;t\_0 \leq -0.010999999940395355:\\ \;\;\;\;\sqrt{-t\_0} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \left(u2 \cdot \left(2 \cdot \pi\right)\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (log (- 1.0 u1))))
       (if (<= t_0 -0.010999999940395355)
         (* (sqrt (- t_0)) (* 2.0 (* u2 PI)))
         (*
          (sqrt (* u1 (+ 1.0 (* u1 (+ 0.5 (* 0.3333333333333333 u1))))))
          (* u2 (* 2.0 PI))))))
    float code(float cosTheta_i, float u1, float u2) {
    	float t_0 = logf((1.0f - u1));
    	float tmp;
    	if (t_0 <= -0.010999999940395355f) {
    		tmp = sqrtf(-t_0) * (2.0f * (u2 * ((float) M_PI)));
    	} else {
    		tmp = sqrtf((u1 * (1.0f + (u1 * (0.5f + (0.3333333333333333f * u1)))))) * (u2 * (2.0f * ((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(-0.010999999940395355))
    		tmp = Float32(sqrt(Float32(-t_0)) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))));
    	else
    		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + Float32(u1 * Float32(Float32(0.5) + Float32(Float32(0.3333333333333333) * u1)))))) * Float32(u2 * Float32(Float32(2.0) * 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(-0.010999999940395355))
    		tmp = sqrt(-t_0) * (single(2.0) * (u2 * single(pi)));
    	else
    		tmp = sqrt((u1 * (single(1.0) + (u1 * (single(0.5) + (single(0.3333333333333333) * u1)))))) * (u2 * (single(2.0) * single(pi)));
    	end
    	tmp_2 = tmp;
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \log \left(1 - u1\right)\\
    \mathbf{if}\;t\_0 \leq -0.010999999940395355:\\
    \;\;\;\;\sqrt{-t\_0} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \left(u2 \cdot \left(2 \cdot \pi\right)\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (log.f32 (-.f32 #s(literal 1 binary32) u1)) < -0.0109999999

      1. Initial program 57.8%

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

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

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

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        3. lift-PI.f3250.6

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      4. Applied rewrites50.6%

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

      if -0.0109999999 < (log.f32 (-.f32 #s(literal 1 binary32) u1))

      1. Initial program 57.8%

        \[\sqrt{-\log \left(1 - u1\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      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-*.f3291.5

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot \color{blue}{u1}\right)\right)} \cdot \sin \left(\left(2 \cdot \pi\right) \cdot u2\right) \]
      4. Applied rewrites91.5%

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \frac{1}{3} \cdot u1\right)\right)} \cdot \left(u2 \cdot \mathsf{fma}\left(\frac{-4}{3}, {u2}^{2} \cdot {\pi}^{3}, 2 \cdot \mathsf{PI}\left(\right)\right)\right) \]
        8. lift-PI.f3283.2

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \left(u2 \cdot \mathsf{fma}\left(-1.3333333333333333, {u2}^{2} \cdot {\pi}^{3}, 2 \cdot \pi\right)\right) \]
      7. Applied rewrites83.2%

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \color{blue}{\left(u2 \cdot \mathsf{fma}\left(-1.3333333333333333, {u2}^{2} \cdot {\pi}^{3}, 2 \cdot \pi\right)\right)} \]
      8. Taylor expanded in u2 around 0

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

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(\frac{1}{2} + \frac{1}{3} \cdot u1\right)\right)} \cdot \left(u2 \cdot \left(2 \cdot \mathsf{PI}\left(\right)\right)\right) \]
        2. lift-PI.f3276.5

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \left(u2 \cdot \left(2 \cdot \pi\right)\right) \]
      10. Applied rewrites76.5%

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(0.5 + 0.3333333333333333 \cdot u1\right)\right)} \cdot \left(u2 \cdot \left(2 \cdot \color{blue}{\pi}\right)\right) \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 9: 80.4% accurate, 2.1× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \left(u2 \cdot \pi\right)\\ \mathbf{if}\;u1 \leq 0.004000000189989805:\\ \;\;\;\;\sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (* 2.0 (* u2 PI))))
       (if (<= u1 0.004000000189989805)
         (* (sqrt (- (* u1 (- (* -0.5 u1) 1.0)))) t_0)
         (* (sqrt (- (log (- 1.0 u1)))) t_0))))
    float code(float cosTheta_i, float u1, float u2) {
    	float t_0 = 2.0f * (u2 * ((float) M_PI));
    	float tmp;
    	if (u1 <= 0.004000000189989805f) {
    		tmp = sqrtf(-(u1 * ((-0.5f * u1) - 1.0f))) * t_0;
    	} else {
    		tmp = sqrtf(-logf((1.0f - u1))) * t_0;
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	t_0 = Float32(Float32(2.0) * Float32(u2 * Float32(pi)))
    	tmp = Float32(0.0)
    	if (u1 <= Float32(0.004000000189989805))
    		tmp = Float32(sqrt(Float32(-Float32(u1 * Float32(Float32(Float32(-0.5) * u1) - Float32(1.0))))) * t_0);
    	else
    		tmp = Float32(sqrt(Float32(-log(Float32(Float32(1.0) - u1)))) * t_0);
    	end
    	return tmp
    end
    
    function tmp_2 = code(cosTheta_i, u1, u2)
    	t_0 = single(2.0) * (u2 * single(pi));
    	tmp = single(0.0);
    	if (u1 <= single(0.004000000189989805))
    		tmp = sqrt(-(u1 * ((single(-0.5) * u1) - single(1.0)))) * t_0;
    	else
    		tmp = sqrt(-log((single(1.0) - u1))) * t_0;
    	end
    	tmp_2 = tmp;
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := 2 \cdot \left(u2 \cdot \pi\right)\\
    \mathbf{if}\;u1 \leq 0.004000000189989805:\\
    \;\;\;\;\sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot t\_0\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{-\log \left(1 - u1\right)} \cdot t\_0\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u1 < 0.00400000019

      1. Initial program 57.8%

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

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

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

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        3. lift-PI.f3250.6

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      4. Applied rewrites50.6%

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

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

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

          \[\leadsto \sqrt{-u1 \cdot \left(\frac{-1}{2} \cdot u1 - \color{blue}{1}\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
        3. lower-*.f3274.0

          \[\leadsto \sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      7. Applied rewrites74.0%

        \[\leadsto \sqrt{-\color{blue}{u1 \cdot \left(-0.5 \cdot u1 - 1\right)}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]

      if 0.00400000019 < u1

      1. Initial program 57.8%

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

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

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

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
        3. lift-PI.f3250.6

          \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      4. Applied rewrites50.6%

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

    Alternative 10: 74.0% accurate, 2.5× speedup?

    \[\begin{array}{l} \\ \sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (* (sqrt (- (* u1 (- (* -0.5 u1) 1.0)))) (* 2.0 (* u2 PI))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf(-(u1 * ((-0.5f * u1) - 1.0f))) * (2.0f * (u2 * ((float) M_PI)));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(Float32(-Float32(u1 * Float32(Float32(Float32(-0.5) * u1) - Float32(1.0))))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))))
    end
    
    function tmp = code(cosTheta_i, u1, u2)
    	tmp = sqrt(-(u1 * ((single(-0.5) * u1) - single(1.0)))) * (single(2.0) * (u2 * single(pi)));
    end
    
    \begin{array}{l}
    
    \\
    \sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)
    \end{array}
    
    Derivation
    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
      3. lift-PI.f3250.6

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    4. Applied rewrites50.6%

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

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

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

        \[\leadsto \sqrt{-u1 \cdot \left(\frac{-1}{2} \cdot u1 - \color{blue}{1}\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
      3. lower-*.f3274.0

        \[\leadsto \sqrt{-u1 \cdot \left(-0.5 \cdot u1 - 1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    7. Applied rewrites74.0%

      \[\leadsto \sqrt{-\color{blue}{u1 \cdot \left(-0.5 \cdot u1 - 1\right)}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    8. Add Preprocessing

    Alternative 11: 65.9% accurate, 3.4× speedup?

    \[\begin{array}{l} \\ \sqrt{--1 \cdot u1} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (* (sqrt (- (* -1.0 u1))) (* 2.0 (* u2 PI))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf(-(-1.0f * u1)) * (2.0f * (u2 * ((float) M_PI)));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(Float32(-Float32(Float32(-1.0) * u1))) * Float32(Float32(2.0) * Float32(u2 * Float32(pi))))
    end
    
    function tmp = code(cosTheta_i, u1, u2)
    	tmp = sqrt(-(single(-1.0) * u1)) * (single(2.0) * (u2 * single(pi)));
    end
    
    \begin{array}{l}
    
    \\
    \sqrt{--1 \cdot u1} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right)
    \end{array}
    
    Derivation
    1. Initial program 57.8%

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

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

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

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
      3. lift-PI.f3250.6

        \[\leadsto \sqrt{-\log \left(1 - u1\right)} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    4. Applied rewrites50.6%

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

      \[\leadsto \sqrt{-\color{blue}{-1 \cdot u1}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    6. Step-by-step derivation
      1. lower-*.f3265.9

        \[\leadsto \sqrt{--1 \cdot \color{blue}{u1}} \cdot \left(2 \cdot \left(u2 \cdot \pi\right)\right) \]
    7. Applied rewrites65.9%

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

    Reproduce

    ?
    herbie shell --seed 2025132 
    (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))))