Trowbridge-Reitz Sample, near normal, slope_y

Percentage Accurate: 98.3% → 98.1%
Time: 12.3s
Alternatives: 24
Speedup: 1.0×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * sinf((6.28318530718f * u2));
}
real(4) function code(costheta_i, u1, u2)
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right)
\end{array}

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 24 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: 98.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * sinf((6.28318530718f * u2));
}
real(4) function code(costheta_i, u1, u2)
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right)
\end{array}

Alternative 1: 98.1% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \sin \left(u2 \cdot 6.28318530718\right) \cdot \left(\sqrt{\frac{-1}{u1 - 1}} \cdot {\left(\frac{1}{u1}\right)}^{-0.5}\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sin (* u2 6.28318530718))
  (* (sqrt (/ -1.0 (- u1 1.0))) (pow (/ 1.0 u1) -0.5))))
float code(float cosTheta_i, float u1, float u2) {
	return sinf((u2 * 6.28318530718f)) * (sqrtf((-1.0f / (u1 - 1.0f))) * powf((1.0f / u1), -0.5f));
}
real(4) function code(costheta_i, u1, u2)
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sin((u2 * 6.28318530718e0)) * (sqrt(((-1.0e0) / (u1 - 1.0e0))) * ((1.0e0 / u1) ** (-0.5e0)))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sin(Float32(u2 * Float32(6.28318530718))) * Float32(sqrt(Float32(Float32(-1.0) / Float32(u1 - Float32(1.0)))) * (Float32(Float32(1.0) / u1) ^ Float32(-0.5))))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sin((u2 * single(6.28318530718))) * (sqrt((single(-1.0) / (u1 - single(1.0)))) * ((single(1.0) / u1) ^ single(-0.5)));
end
\begin{array}{l}

\\
\sin \left(u2 \cdot 6.28318530718\right) \cdot \left(\sqrt{\frac{-1}{u1 - 1}} \cdot {\left(\frac{1}{u1}\right)}^{-0.5}\right)
\end{array}
Derivation
  1. Initial program 98.1%

    \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-sqrt.f32N/A

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    2. pow1/2N/A

      \[\leadsto \color{blue}{{\left(\frac{u1}{1 - u1}\right)}^{\frac{1}{2}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    3. lift-/.f32N/A

      \[\leadsto {\color{blue}{\left(\frac{u1}{1 - u1}\right)}}^{\frac{1}{2}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    4. clear-numN/A

      \[\leadsto {\color{blue}{\left(\frac{1}{\frac{1 - u1}{u1}}\right)}}^{\frac{1}{2}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    5. inv-powN/A

      \[\leadsto {\color{blue}{\left({\left(\frac{1 - u1}{u1}\right)}^{-1}\right)}}^{\frac{1}{2}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    6. pow-powN/A

      \[\leadsto \color{blue}{{\left(\frac{1 - u1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    7. clear-numN/A

      \[\leadsto {\color{blue}{\left(\frac{1}{\frac{u1}{1 - u1}}\right)}}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    8. associate-/r/N/A

      \[\leadsto {\color{blue}{\left(\frac{1}{u1} \cdot \left(1 - u1\right)\right)}}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    9. unpow-prod-downN/A

      \[\leadsto \color{blue}{\left({\left(\frac{1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot {\left(1 - u1\right)}^{\left(-1 \cdot \frac{1}{2}\right)}\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    10. pow-powN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot \color{blue}{{\left({\left(1 - u1\right)}^{-1}\right)}^{\frac{1}{2}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    11. inv-powN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot {\color{blue}{\left(\frac{1}{1 - u1}\right)}}^{\frac{1}{2}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    12. lower-*.f32N/A

      \[\leadsto \color{blue}{\left({\left(\frac{1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot {\left(\frac{1}{1 - u1}\right)}^{\frac{1}{2}}\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    13. lower-pow.f32N/A

      \[\leadsto \left(\color{blue}{{\left(\frac{1}{u1}\right)}^{\left(-1 \cdot \frac{1}{2}\right)}} \cdot {\left(\frac{1}{1 - u1}\right)}^{\frac{1}{2}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    14. lower-/.f32N/A

      \[\leadsto \left({\color{blue}{\left(\frac{1}{u1}\right)}}^{\left(-1 \cdot \frac{1}{2}\right)} \cdot {\left(\frac{1}{1 - u1}\right)}^{\frac{1}{2}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    15. metadata-evalN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\color{blue}{\frac{-1}{2}}} \cdot {\left(\frac{1}{1 - u1}\right)}^{\frac{1}{2}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    16. pow1/2N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \color{blue}{\sqrt{\frac{1}{1 - u1}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    17. lower-sqrt.f32N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \color{blue}{\sqrt{\frac{1}{1 - u1}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    18. frac-2negN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{\mathsf{neg}\left(\left(1 - u1\right)\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    19. metadata-evalN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{\color{blue}{-1}}{\mathsf{neg}\left(\left(1 - u1\right)\right)}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    20. lower-/.f32N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\color{blue}{\frac{-1}{\mathsf{neg}\left(\left(1 - u1\right)\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    21. neg-sub0N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{\color{blue}{0 - \left(1 - u1\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    22. lift--.f32N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{0 - \color{blue}{\left(1 - u1\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    23. sub-negN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{0 - \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    24. +-commutativeN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{0 - \color{blue}{\left(\left(\mathsf{neg}\left(u1\right)\right) + 1\right)}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    25. associate--r+N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{\color{blue}{\left(0 - \left(\mathsf{neg}\left(u1\right)\right)\right) - 1}}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    26. neg-sub0N/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{\color{blue}{\left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1\right)\right)\right)\right)} - 1}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    27. remove-double-negN/A

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{\frac{-1}{2}} \cdot \sqrt{\frac{-1}{\color{blue}{u1} - 1}}\right) \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    28. lower--.f3298.2

      \[\leadsto \left({\left(\frac{1}{u1}\right)}^{-0.5} \cdot \sqrt{\frac{-1}{\color{blue}{u1 - 1}}}\right) \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  4. Applied rewrites98.2%

    \[\leadsto \color{blue}{\left({\left(\frac{1}{u1}\right)}^{-0.5} \cdot \sqrt{\frac{-1}{u1 - 1}}\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  5. Final simplification98.2%

    \[\leadsto \sin \left(u2 \cdot 6.28318530718\right) \cdot \left(\sqrt{\frac{-1}{u1 - 1}} \cdot {\left(\frac{1}{u1}\right)}^{-0.5}\right) \]
  6. Add Preprocessing

Alternative 2: 97.3% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1 + 1, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= (* u2 6.28318530718) 1.399999976158142)
   (*
    (*
     (fma
      (fma
       (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
       (* u2 u2)
       -41.341702240407926)
      (* u2 u2)
      6.28318530718)
     u2)
    (sqrt (/ u1 (- 1.0 u1))))
   (* (sqrt (* (fma (+ u1 1.0) u1 1.0) u1)) (sin (* u2 6.28318530718)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if ((u2 * 6.28318530718f) <= 1.399999976158142f) {
		tmp = (fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
	} else {
		tmp = sqrtf((fmaf((u1 + 1.0f), u1, 1.0f) * u1)) * sinf((u2 * 6.28318530718f));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (Float32(u2 * Float32(6.28318530718)) <= Float32(1.399999976158142))
		tmp = Float32(Float32(fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
	else
		tmp = Float32(sqrt(Float32(fma(Float32(u1 + Float32(1.0)), u1, Float32(1.0)) * u1)) * sin(Float32(u2 * Float32(6.28318530718))));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\
\;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\mathsf{fma}\left(u1 + 1, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 1.39999998

    1. Initial program 98.4%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      2. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      5. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      6. sub-negN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      7. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      8. metadata-evalN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      10. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      11. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right)}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      12. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      13. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      14. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      15. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      16. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      17. lower-*.f3297.9

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
    5. Applied rewrites97.9%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]

    if 1.39999998 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

    1. Initial program 94.4%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. lift--.f32N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. flip--N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1 \cdot 1 - u1 \cdot u1}{1 + u1}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. associate-/r/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 \cdot 1 - u1 \cdot u1} \cdot \left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. associate-*l/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 \cdot 1 - u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1 \cdot \color{blue}{\left(u1 + 1\right)}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. distribute-rgt-outN/A

        \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot u1 + 1 \cdot u1}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. frac-2negN/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. lower-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      10. lower-neg.f32N/A

        \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      11. *-lft-identityN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + \color{blue}{u1}\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      12. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      13. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. sub-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)}\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      15. distribute-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      16. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1} + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      17. distribute-rgt-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \left(\mathsf{neg}\left(\color{blue}{u1 \cdot \left(\mathsf{neg}\left(u1\right)\right)}\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      18. distribute-lft-neg-outN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{\left(\mathsf{neg}\left(u1\right)\right) \cdot \left(\mathsf{neg}\left(u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      19. sqr-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      20. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1 + u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      21. lower-*.f3294.6

        \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Applied rewrites94.6%

      \[\leadsto \sqrt{\color{blue}{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites94.4%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    6. Taylor expanded in u1 around 0

      \[\leadsto \sqrt{\color{blue}{\left(1 + u1 \cdot \left(1 + u1\right)\right)} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sqrt{\color{blue}{\left(u1 \cdot \left(1 + u1\right) + 1\right)} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. *-commutativeN/A

        \[\leadsto \sqrt{\left(\color{blue}{\left(1 + u1\right) \cdot u1} + 1\right) \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. lower-fma.f32N/A

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(1 + u1, u1, 1\right)} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. lower-+.f3291.7

        \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{1 + u1}, u1, 1\right) \cdot u1} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    8. Applied rewrites91.7%

      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(1 + u1, u1, 1\right)} \cdot u1} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification97.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1 + 1, u1, 1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 97.3% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\left(\mathsf{fma}\left(u1, u1, 1\right) + u1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= (* u2 6.28318530718) 1.399999976158142)
   (*
    (*
     (fma
      (fma
       (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
       (* u2 u2)
       -41.341702240407926)
      (* u2 u2)
      6.28318530718)
     u2)
    (sqrt (/ u1 (- 1.0 u1))))
   (* (sqrt (* (+ (fma u1 u1 1.0) u1) u1)) (sin (* u2 6.28318530718)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if ((u2 * 6.28318530718f) <= 1.399999976158142f) {
		tmp = (fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
	} else {
		tmp = sqrtf(((fmaf(u1, u1, 1.0f) + u1) * u1)) * sinf((u2 * 6.28318530718f));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (Float32(u2 * Float32(6.28318530718)) <= Float32(1.399999976158142))
		tmp = Float32(Float32(fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
	else
		tmp = Float32(sqrt(Float32(Float32(fma(u1, u1, Float32(1.0)) + u1) * u1)) * sin(Float32(u2 * Float32(6.28318530718))));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\
\;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\left(\mathsf{fma}\left(u1, u1, 1\right) + u1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 1.39999998

    1. Initial program 98.4%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      2. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      5. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      6. sub-negN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      7. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      8. metadata-evalN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      10. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      11. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right)}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      12. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      13. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      14. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      15. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      16. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      17. lower-*.f3297.9

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
    5. Applied rewrites97.9%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]

    if 1.39999998 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

    1. Initial program 94.4%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u1 around 0

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    4. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 \cdot \left(1 + u1\right) + 1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. distribute-rgt-inN/A

        \[\leadsto \sqrt{\color{blue}{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + 1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. *-lft-identityN/A

        \[\leadsto \sqrt{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + \color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. lower-fma.f32N/A

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1 \cdot \left(1 + u1\right), u1, u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. +-commutativeN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot \color{blue}{\left(u1 + 1\right)}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. distribute-lft-inN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{u1 \cdot u1 + u1 \cdot 1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. *-rgt-identityN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot u1 + \color{blue}{u1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. lower-fma.f3291.5

        \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1, u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites91.5%

      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    6. Step-by-step derivation
      1. Applied rewrites91.6%

        \[\leadsto \sqrt{\left(\mathsf{fma}\left(u1, u1, 1\right) + u1\right) \cdot \color{blue}{u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    7. Recombined 2 regimes into one program.
    8. Final simplification97.5%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\left(\mathsf{fma}\left(u1, u1, 1\right) + u1\right) \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \]
    9. Add Preprocessing

    Alternative 4: 98.3% accurate, 0.9× speedup?

    \[\begin{array}{l} \\ \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{\mathsf{fma}\left(u1, u1, -1\right)}} \cdot \sin \left(u2 \cdot 6.28318530718\right) \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (* (sqrt (/ (- (fma u1 u1 u1)) (fma u1 u1 -1.0))) (sin (* u2 6.28318530718))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf((-fmaf(u1, u1, u1) / fmaf(u1, u1, -1.0f))) * sinf((u2 * 6.28318530718f));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(Float32(Float32(-fma(u1, u1, u1)) / fma(u1, u1, Float32(-1.0)))) * sin(Float32(u2 * Float32(6.28318530718))))
    end
    
    \begin{array}{l}
    
    \\
    \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{\mathsf{fma}\left(u1, u1, -1\right)}} \cdot \sin \left(u2 \cdot 6.28318530718\right)
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. lift--.f32N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. flip--N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1 \cdot 1 - u1 \cdot u1}{1 + u1}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. associate-/r/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 \cdot 1 - u1 \cdot u1} \cdot \left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. associate-*l/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 \cdot 1 - u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1 \cdot \color{blue}{\left(u1 + 1\right)}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. distribute-rgt-outN/A

        \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot u1 + 1 \cdot u1}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. frac-2negN/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. lower-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      10. lower-neg.f32N/A

        \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      11. *-lft-identityN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + \color{blue}{u1}\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      12. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      13. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. sub-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)}\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      15. distribute-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      16. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1} + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      17. distribute-rgt-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \left(\mathsf{neg}\left(\color{blue}{u1 \cdot \left(\mathsf{neg}\left(u1\right)\right)}\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      18. distribute-lft-neg-outN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{\left(\mathsf{neg}\left(u1\right)\right) \cdot \left(\mathsf{neg}\left(u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      19. sqr-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      20. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1 + u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      21. lower-*.f3298.1

        \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Applied rewrites98.1%

      \[\leadsto \sqrt{\color{blue}{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Step-by-step derivation
      1. lift-+.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1 + u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. +-commutativeN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{u1 \cdot u1 + -1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. lift-*.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{u1 \cdot u1} + -1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. lower-fma.f3298.2

        \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{\color{blue}{\mathsf{fma}\left(u1, u1, -1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    6. Applied rewrites98.2%

      \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{\color{blue}{\mathsf{fma}\left(u1, u1, -1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    7. Final simplification98.2%

      \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{\mathsf{fma}\left(u1, u1, -1\right)}} \cdot \sin \left(u2 \cdot 6.28318530718\right) \]
    8. Add Preprocessing

    Alternative 5: 97.3% accurate, 0.9× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 1.399999976158142)
       (*
        (*
         (fma
          (fma
           (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
           (* u2 u2)
           -41.341702240407926)
          (* u2 u2)
          6.28318530718)
         u2)
        (sqrt (/ u1 (- 1.0 u1))))
       (* (sqrt (fma (fma u1 u1 u1) u1 u1)) (sin (* u2 6.28318530718)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 1.399999976158142f) {
    		tmp = (fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
    	} else {
    		tmp = sqrtf(fmaf(fmaf(u1, u1, u1), u1, u1)) * sinf((u2 * 6.28318530718f));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(1.399999976158142))
    		tmp = Float32(Float32(fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
    	else
    		tmp = Float32(sqrt(fma(fma(u1, u1, u1), u1, u1)) * sin(Float32(u2 * Float32(6.28318530718))));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\
    \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 1.39999998

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. sub-negN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        8. metadata-evalN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        9. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        10. +-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        11. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right)}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        12. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        13. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        14. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        15. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        16. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        17. lower-*.f3297.9

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
      5. Applied rewrites97.9%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]

      if 1.39999998 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 94.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 \cdot \left(1 + u1\right) + 1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        2. distribute-rgt-inN/A

          \[\leadsto \sqrt{\color{blue}{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + 1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. *-lft-identityN/A

          \[\leadsto \sqrt{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + \color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. lower-fma.f32N/A

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1 \cdot \left(1 + u1\right), u1, u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        5. +-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot \color{blue}{\left(u1 + 1\right)}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        6. distribute-lft-inN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{u1 \cdot u1 + u1 \cdot 1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        7. *-rgt-identityN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot u1 + \color{blue}{u1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        8. lower-fma.f3291.5

          \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1, u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites91.5%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    3. Recombined 2 regimes into one program.
    4. Final simplification97.5%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \]
    5. Add Preprocessing

    Alternative 6: 98.2% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \sqrt{\frac{-1}{u1 - 1} \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right) \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (* (sqrt (* (/ -1.0 (- u1 1.0)) u1)) (sin (* u2 6.28318530718))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf(((-1.0f / (u1 - 1.0f)) * u1)) * sinf((u2 * 6.28318530718f));
    }
    
    real(4) function code(costheta_i, u1, u2)
        real(4), intent (in) :: costheta_i
        real(4), intent (in) :: u1
        real(4), intent (in) :: u2
        code = sqrt((((-1.0e0) / (u1 - 1.0e0)) * u1)) * sin((u2 * 6.28318530718e0))
    end function
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(Float32(Float32(Float32(-1.0) / Float32(u1 - Float32(1.0))) * u1)) * sin(Float32(u2 * Float32(6.28318530718))))
    end
    
    function tmp = code(cosTheta_i, u1, u2)
    	tmp = sqrt(((single(-1.0) / (u1 - single(1.0))) * u1)) * sin((u2 * single(6.28318530718)));
    end
    
    \begin{array}{l}
    
    \\
    \sqrt{\frac{-1}{u1 - 1} \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right)
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. clear-numN/A

        \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{1 - u1}{u1}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. associate-/r/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. lower-*.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. frac-2negN/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{\mathsf{neg}\left(\left(1 - u1\right)\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\color{blue}{-1}}{\mathsf{neg}\left(\left(1 - u1\right)\right)} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. lower-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{-1}{\mathsf{neg}\left(\left(1 - u1\right)\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. neg-sub0N/A

        \[\leadsto \sqrt{\frac{-1}{\color{blue}{0 - \left(1 - u1\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. lift--.f32N/A

        \[\leadsto \sqrt{\frac{-1}{0 - \color{blue}{\left(1 - u1\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      10. sub-negN/A

        \[\leadsto \sqrt{\frac{-1}{0 - \color{blue}{\left(1 + \left(\mathsf{neg}\left(u1\right)\right)\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      11. +-commutativeN/A

        \[\leadsto \sqrt{\frac{-1}{0 - \color{blue}{\left(\left(\mathsf{neg}\left(u1\right)\right) + 1\right)}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      12. associate--r+N/A

        \[\leadsto \sqrt{\frac{-1}{\color{blue}{\left(0 - \left(\mathsf{neg}\left(u1\right)\right)\right) - 1}} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      13. neg-sub0N/A

        \[\leadsto \sqrt{\frac{-1}{\color{blue}{\left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1\right)\right)\right)\right)} - 1} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. remove-double-negN/A

        \[\leadsto \sqrt{\frac{-1}{\color{blue}{u1} - 1} \cdot u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      15. lower--.f3298.1

        \[\leadsto \sqrt{\frac{-1}{\color{blue}{u1 - 1}} \cdot u1} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Applied rewrites98.1%

      \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1} \cdot u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Final simplification98.1%

      \[\leadsto \sqrt{\frac{-1}{u1 - 1} \cdot u1} \cdot \sin \left(u2 \cdot 6.28318530718\right) \]
    6. Add Preprocessing

    Alternative 7: 97.0% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 1.399999976158142)
       (*
        (*
         (fma
          (fma
           (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
           (* u2 u2)
           -41.341702240407926)
          (* u2 u2)
          6.28318530718)
         u2)
        (sqrt (/ u1 (- 1.0 u1))))
       (* (sqrt (fma u1 u1 u1)) (sin (* u2 6.28318530718)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 1.399999976158142f) {
    		tmp = (fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
    	} else {
    		tmp = sqrtf(fmaf(u1, u1, u1)) * sinf((u2 * 6.28318530718f));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(1.399999976158142))
    		tmp = Float32(Float32(fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
    	else
    		tmp = Float32(sqrt(fma(u1, u1, u1)) * sin(Float32(u2 * Float32(6.28318530718))));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\
    \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 1.39999998

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. sub-negN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        8. metadata-evalN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        9. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        10. +-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        11. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right)}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        12. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        13. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        14. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        15. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        16. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        17. lower-*.f3297.9

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
      5. Applied rewrites97.9%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]

      if 1.39999998 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 94.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        2. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. *-rgt-identityN/A

          \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. lower-fma.f3288.8

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites88.8%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    3. Recombined 2 regimes into one program.
    4. Final simplification97.3%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 1.399999976158142:\\ \;\;\;\;\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(u2 \cdot 6.28318530718\right)\\ \end{array} \]
    5. Add Preprocessing

    Alternative 8: 98.3% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(u2 \cdot 6.28318530718\right) \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (* (sqrt (/ u1 (- 1.0 u1))) (sin (* u2 6.28318530718))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf((u1 / (1.0f - u1))) * sinf((u2 * 6.28318530718f));
    }
    
    real(4) function code(costheta_i, u1, u2)
        real(4), intent (in) :: costheta_i
        real(4), intent (in) :: u1
        real(4), intent (in) :: u2
        code = sqrt((u1 / (1.0e0 - u1))) * sin((u2 * 6.28318530718e0))
    end function
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(u2 * Float32(6.28318530718))))
    end
    
    function tmp = code(cosTheta_i, u1, u2)
    	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((u2 * single(6.28318530718)));
    end
    
    \begin{array}{l}
    
    \\
    \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(u2 \cdot 6.28318530718\right)
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Final simplification98.1%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(u2 \cdot 6.28318530718\right) \]
    4. Add Preprocessing

    Alternative 9: 93.5% accurate, 2.0× speedup?

    \[\begin{array}{l} \\ \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (*
      (*
       (fma
        (fma
         (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
         (* u2 u2)
         -41.341702240407926)
        (* u2 u2)
        6.28318530718)
       u2)
      (sqrt (/ u1 (- 1.0 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	return (fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(Float32(fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))))
    end
    
    \begin{array}{l}
    
    \\
    \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      2. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      5. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      6. sub-negN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      7. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      8. metadata-evalN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      10. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      11. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right)}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      12. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      13. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      14. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      15. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      16. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      17. lower-*.f3293.9

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
    5. Applied rewrites93.9%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
    6. Final simplification93.9%

      \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
    7. Add Preprocessing

    Alternative 10: 91.1% accurate, 2.4× speedup?

    \[\begin{array}{l} \\ \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (*
      (*
       (fma
        (fma 81.6052492761019 (* u2 u2) -41.341702240407926)
        (* u2 u2)
        6.28318530718)
       u2)
      (sqrt (/ u1 (- 1.0 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	return (fmaf(fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(Float32(fma(fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))))
    end
    
    \begin{array}{l}
    
    \\
    \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      2. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot u2\right)} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      5. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      6. sub-negN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      7. metadata-evalN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      8. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}, {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      9. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      10. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), {u2}^{2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      11. unpow2N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right), \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      12. lower-*.f3291.7

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
    5. Applied rewrites91.7%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
    6. Final simplification91.7%

      \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
    7. Add Preprocessing

    Alternative 11: 91.1% accurate, 2.4× speedup?

    \[\begin{array}{l} \\ \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (*
      (*
       (fma
        (fma 81.6052492761019 (* u2 u2) -41.341702240407926)
        (* u2 u2)
        6.28318530718)
       (sqrt (/ u1 (- 1.0 u1))))
      u2))
    float code(float cosTheta_i, float u1, float u2) {
    	return (fmaf(fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f) * sqrtf((u1 / (1.0f - u1)))) * u2;
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(Float32(fma(fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718)) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))) * u2)
    end
    
    \begin{array}{l}
    
    \\
    \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Taylor expanded in u2 around 0

      \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)\right)} \]
    4. Applied rewrites91.6%

      \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right)\right) \cdot u2} \]
    5. Final simplification91.6%

      \[\leadsto \left(\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \]
    6. Add Preprocessing

    Alternative 12: 86.6% accurate, 2.5× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 0.0017999999690800905)
       (* (* u2 6.28318530718) (sqrt (* (/ -1.0 (- u1 1.0)) u1)))
       (*
        (* (fma (* u2 u2) -41.341702240407926 6.28318530718) u2)
        (sqrt (fma (fma u1 u1 u1) u1 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 0.0017999999690800905f) {
    		tmp = (u2 * 6.28318530718f) * sqrtf(((-1.0f / (u1 - 1.0f)) * u1));
    	} else {
    		tmp = (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * u2) * sqrtf(fmaf(fmaf(u1, u1, u1), u1, u1));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.0017999999690800905))
    		tmp = Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(Float32(Float32(Float32(-1.0) / Float32(u1 - Float32(1.0))) * u1)));
    	else
    		tmp = Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * u2) * sqrt(fma(fma(u1, u1, u1), u1, u1)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\
    \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.00179999997

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3298.1

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites98.1%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Step-by-step derivation
        1. lift-/.f32N/A

          \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        2. clear-numN/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{1 - u1}{u1}}}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        3. associate-/r/N/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        4. lift--.f32N/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{1 - u1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        5. sub-negN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        6. +-commutativeN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(u1\right)\right) + 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. metadata-evalN/A

          \[\leadsto \sqrt{\frac{1}{\left(\mathsf{neg}\left(u1\right)\right) + \color{blue}{\left(\mathsf{neg}\left(-1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        8. distribute-neg-inN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{\mathsf{neg}\left(\left(u1 + -1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        9. metadata-evalN/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\left(u1 + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}\right)\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        10. sub-negN/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\color{blue}{\left(u1 - 1\right)}\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        11. lift--.f32N/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\color{blue}{\left(u1 - 1\right)}\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        12. metadata-evalN/A

          \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(-1\right)}}{\mathsf{neg}\left(\left(u1 - 1\right)\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        13. frac-2negN/A

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        14. lift-/.f32N/A

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        15. lower-*.f3298.2

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1} \cdot u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      7. Applied rewrites98.2%

        \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1} \cdot u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]

      if 0.00179999997 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 97.5%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 \cdot \left(1 + u1\right) + 1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        2. distribute-rgt-inN/A

          \[\leadsto \sqrt{\color{blue}{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + 1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. *-lft-identityN/A

          \[\leadsto \sqrt{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + \color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. lower-fma.f32N/A

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1 \cdot \left(1 + u1\right), u1, u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        5. +-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot \color{blue}{\left(u1 + 1\right)}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        6. distribute-lft-inN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{u1 \cdot u1 + u1 \cdot 1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        7. *-rgt-identityN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot u1 + \color{blue}{u1}, u1, u1\right)} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        8. lower-fma.f3289.2

          \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1, u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites89.2%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
      7. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \left(\left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. unpow2N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. lower-*.f3268.1

          \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \]
      8. Applied rewrites68.1%

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot \color{blue}{\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right)} \]
    3. Recombined 2 regimes into one program.
    4. Final simplification88.1%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\ \end{array} \]
    5. Add Preprocessing

    Alternative 13: 85.8% accurate, 2.6× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 0.0017999999690800905)
       (* (* u2 6.28318530718) (sqrt (* (/ -1.0 (- u1 1.0)) u1)))
       (*
        (* (fma (* u2 u2) -41.341702240407926 6.28318530718) u2)
        (sqrt (fma u1 u1 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 0.0017999999690800905f) {
    		tmp = (u2 * 6.28318530718f) * sqrtf(((-1.0f / (u1 - 1.0f)) * u1));
    	} else {
    		tmp = (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * u2) * sqrtf(fmaf(u1, u1, u1));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.0017999999690800905))
    		tmp = Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(Float32(Float32(Float32(-1.0) / Float32(u1 - Float32(1.0))) * u1)));
    	else
    		tmp = Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * u2) * sqrt(fma(u1, u1, u1)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\
    \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.00179999997

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3298.1

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites98.1%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Step-by-step derivation
        1. lift-/.f32N/A

          \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        2. clear-numN/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{\frac{1 - u1}{u1}}}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        3. associate-/r/N/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        4. lift--.f32N/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{1 - u1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        5. sub-negN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        6. +-commutativeN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(u1\right)\right) + 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. metadata-evalN/A

          \[\leadsto \sqrt{\frac{1}{\left(\mathsf{neg}\left(u1\right)\right) + \color{blue}{\left(\mathsf{neg}\left(-1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        8. distribute-neg-inN/A

          \[\leadsto \sqrt{\frac{1}{\color{blue}{\mathsf{neg}\left(\left(u1 + -1\right)\right)}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        9. metadata-evalN/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\left(u1 + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}\right)\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        10. sub-negN/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\color{blue}{\left(u1 - 1\right)}\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        11. lift--.f32N/A

          \[\leadsto \sqrt{\frac{1}{\mathsf{neg}\left(\color{blue}{\left(u1 - 1\right)}\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        12. metadata-evalN/A

          \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(-1\right)}}{\mathsf{neg}\left(\left(u1 - 1\right)\right)} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        13. frac-2negN/A

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        14. lift-/.f32N/A

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1}} \cdot u1} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        15. lower-*.f3298.2

          \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1} \cdot u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      7. Applied rewrites98.2%

        \[\leadsto \sqrt{\color{blue}{\frac{-1}{u1 - 1} \cdot u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]

      if 0.00179999997 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 97.5%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3250.6

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites50.6%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        2. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        3. *-rgt-identityN/A

          \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        4. lower-fma.f3249.6

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      8. Applied rewrites49.6%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      9. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
      10. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. unpow2N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. lower-*.f3266.0

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \]
      11. Applied rewrites66.0%

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right)} \]
    3. Recombined 2 regimes into one program.
    4. Final simplification87.4%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{-1}{u1 - 1} \cdot u1}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \]
    5. Add Preprocessing

    Alternative 14: 88.6% accurate, 2.6× speedup?

    \[\begin{array}{l} \\ \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{1}{1 - u1} \cdot u1} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (*
      (* (fma (* u2 u2) -41.341702240407926 6.28318530718) u2)
      (sqrt (* (/ 1.0 (- 1.0 u1)) u1))))
    float code(float cosTheta_i, float u1, float u2) {
    	return (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * u2) * sqrtf(((1.0f / (1.0f - u1)) * u1));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * u2) * sqrt(Float32(Float32(Float32(1.0) / Float32(Float32(1.0) - u1)) * u1)))
    end
    
    \begin{array}{l}
    
    \\
    \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{1}{1 - u1} \cdot u1}
    \end{array}
    
    Derivation
    1. Initial program 98.1%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. lift--.f32N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. flip--N/A

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1 \cdot 1 - u1 \cdot u1}{1 + u1}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. associate-/r/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 \cdot 1 - u1 \cdot u1} \cdot \left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. associate-*l/N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 \cdot 1 - u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. +-commutativeN/A

        \[\leadsto \sqrt{\frac{u1 \cdot \color{blue}{\left(u1 + 1\right)}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. distribute-rgt-outN/A

        \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot u1 + 1 \cdot u1}}{1 \cdot 1 - u1 \cdot u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. frac-2negN/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. lower-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      10. lower-neg.f32N/A

        \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(\left(u1 \cdot u1 + 1 \cdot u1\right)\right)}}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      11. *-lft-identityN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\left(u1 \cdot u1 + \color{blue}{u1}\right)\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      12. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}\right)}{\mathsf{neg}\left(\left(1 \cdot 1 - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      13. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - u1 \cdot u1\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. sub-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)}\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      15. distribute-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      16. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1} + \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(u1 \cdot u1\right)\right)\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      17. distribute-rgt-neg-inN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \left(\mathsf{neg}\left(\color{blue}{u1 \cdot \left(\mathsf{neg}\left(u1\right)\right)}\right)\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      18. distribute-lft-neg-outN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{\left(\mathsf{neg}\left(u1\right)\right) \cdot \left(\mathsf{neg}\left(u1\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      19. sqr-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      20. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, u1, u1\right)\right)}{\color{blue}{-1 + u1 \cdot u1}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      21. lower-*.f3298.1

        \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + \color{blue}{u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Applied rewrites98.1%

      \[\leadsto \sqrt{\color{blue}{\frac{-\mathsf{fma}\left(u1, u1, u1\right)}{-1 + u1 \cdot u1}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.1%

      \[\leadsto \sqrt{\color{blue}{\frac{1}{1 - u1} \cdot u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    6. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
    7. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
      2. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      4. *-commutativeN/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \left(\left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      5. lower-fma.f32N/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
      6. unpow2N/A

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
      7. lower-*.f3289.5

        \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \]
    8. Applied rewrites89.5%

      \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \cdot \color{blue}{\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right)} \]
    9. Final simplification89.5%

      \[\leadsto \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{1}{1 - u1} \cdot u1} \]
    10. Add Preprocessing

    Alternative 15: 85.9% accurate, 2.8× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 0.0017999999690800905)
       (* (* u2 6.28318530718) (sqrt (/ u1 (- 1.0 u1))))
       (*
        (* (fma (* u2 u2) -41.341702240407926 6.28318530718) u2)
        (sqrt (fma u1 u1 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 0.0017999999690800905f) {
    		tmp = (u2 * 6.28318530718f) * sqrtf((u1 / (1.0f - u1)));
    	} else {
    		tmp = (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * u2) * sqrtf(fmaf(u1, u1, u1));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.0017999999690800905))
    		tmp = Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
    	else
    		tmp = Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * u2) * sqrt(fma(u1, u1, u1)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\
    \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.00179999997

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3298.1

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites98.1%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]

      if 0.00179999997 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 97.5%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3250.6

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites50.6%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        2. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        3. *-rgt-identityN/A

          \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        4. lower-fma.f3249.6

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      8. Applied rewrites49.6%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      9. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
      10. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. unpow2N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. lower-*.f3266.0

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \]
      11. Applied rewrites66.0%

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right)} \]
    3. Recombined 2 regimes into one program.
    4. Final simplification87.3%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.0017999999690800905:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \]
    5. Add Preprocessing

    Alternative 16: 83.8% accurate, 2.9× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 0.004900000058114529)
       (* (* u2 6.28318530718) (sqrt (/ u1 (- 1.0 u1))))
       (* (* (fma -41.341702240407926 (* u2 u2) 6.28318530718) u2) (sqrt u1))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 0.004900000058114529f) {
    		tmp = (u2 * 6.28318530718f) * sqrtf((u1 / (1.0f - u1)));
    	} else {
    		tmp = (fmaf(-41.341702240407926f, (u2 * u2), 6.28318530718f) * u2) * sqrtf(u1);
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.004900000058114529))
    		tmp = Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))));
    	else
    		tmp = Float32(Float32(fma(Float32(-41.341702240407926), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(u1));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\
    \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.00490000006

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3297.5

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites97.5%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]

      if 0.00490000006 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

      1. Initial program 97.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3245.8

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites45.8%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Taylor expanded in u1 around 0

        \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
      7. Step-by-step derivation
        1. lower-sqrt.f3243.6

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      8. Applied rewrites43.6%

        \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
      9. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
      10. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. lower-fma.f32N/A

          \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        5. unpow2N/A

          \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        6. lower-*.f3256.7

          \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(-41.341702240407926, \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
      11. Applied rewrites56.7%

        \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
    3. Recombined 2 regimes into one program.
    4. Final simplification85.4%

      \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
    5. Add Preprocessing

    Alternative 17: 83.8% accurate, 2.9× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\ \;\;\;\;\left(\sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot u2\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (* u2 6.28318530718) 0.004900000058114529)
       (* (* (sqrt (/ u1 (- 1.0 u1))) 6.28318530718) u2)
       (* (* (fma -41.341702240407926 (* u2 u2) 6.28318530718) u2) (sqrt u1))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((u2 * 6.28318530718f) <= 0.004900000058114529f) {
    		tmp = (sqrtf((u1 / (1.0f - u1))) * 6.28318530718f) * u2;
    	} else {
    		tmp = (fmaf(-41.341702240407926f, (u2 * u2), 6.28318530718f) * u2) * sqrtf(u1);
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.004900000058114529))
    		tmp = Float32(Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(6.28318530718)) * u2);
    	else
    		tmp = Float32(Float32(fma(Float32(-41.341702240407926), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(u1));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\
    \;\;\;\;\left(\sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot u2\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.00490000006

      1. Initial program 98.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3297.5

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites97.5%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      7. Applied rewrites98.4%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right), \left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2} \]
      8. Taylor expanded in u2 around 0

        \[\leadsto \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \]
      9. Step-by-step derivation
        1. Applied rewrites97.5%

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot u2 \]

        if 0.00490000006 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

        1. Initial program 97.4%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
          2. lower-*.f3245.8

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        5. Applied rewrites45.8%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        6. Taylor expanded in u1 around 0

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. Step-by-step derivation
          1. lower-sqrt.f3243.6

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        8. Applied rewrites43.6%

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        9. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
        10. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
          2. lower-*.f32N/A

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
          3. +-commutativeN/A

            \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
          4. lower-fma.f32N/A

            \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
          5. unpow2N/A

            \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
          6. lower-*.f3256.7

            \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(-41.341702240407926, \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
        11. Applied rewrites56.7%

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
      10. Recombined 2 regimes into one program.
      11. Final simplification85.4%

        \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.004900000058114529:\\ \;\;\;\;\left(\sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot u2\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
      12. Add Preprocessing

      Alternative 18: 88.7% accurate, 2.9× speedup?

      \[\begin{array}{l} \\ \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (* (fma (* u2 u2) -41.341702240407926 6.28318530718) u2)
        (sqrt (/ u1 (- 1.0 u1)))))
      float code(float cosTheta_i, float u1, float u2) {
      	return (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * u2) * sqrtf((u1 / (1.0f - u1)));
      }
      
      function code(cosTheta_i, u1, u2)
      	return Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * u2) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1))))
      end
      
      \begin{array}{l}
      
      \\
      \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}
      \end{array}
      
      Derivation
      1. Initial program 98.1%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        2. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        4. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        5. lower-fma.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
        6. unpow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
        7. lower-*.f3289.5

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \]
      5. Applied rewrites89.5%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right)} \]
      6. Final simplification89.5%

        \[\leadsto \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
      7. Add Preprocessing

      Alternative 19: 88.7% accurate, 2.9× speedup?

      \[\begin{array}{l} \\ \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (*
         (fma (* u2 u2) -41.341702240407926 6.28318530718)
         (sqrt (/ u1 (- 1.0 u1))))
        u2))
      float code(float cosTheta_i, float u1, float u2) {
      	return (fmaf((u2 * u2), -41.341702240407926f, 6.28318530718f) * sqrtf((u1 / (1.0f - u1)))) * u2;
      }
      
      function code(cosTheta_i, u1, u2)
      	return Float32(Float32(fma(Float32(u2 * u2), Float32(-41.341702240407926), Float32(6.28318530718)) * sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))) * u2)
      end
      
      \begin{array}{l}
      
      \\
      \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2
      \end{array}
      
      Derivation
      1. Initial program 98.1%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
        2. lower-*.f3282.1

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      5. Applied rewrites82.1%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \color{blue}{u2 \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
      7. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2} \]
        2. lower-*.f32N/A

          \[\leadsto \color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2} \]
        3. *-commutativeN/A

          \[\leadsto \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \]
        4. associate-*r*N/A

          \[\leadsto \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \]
        5. distribute-rgt-outN/A

          \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)\right)} \cdot u2 \]
        6. +-commutativeN/A

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)}\right) \cdot u2 \]
        7. lower-*.f32N/A

          \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \cdot u2 \]
        8. lower-sqrt.f32N/A

          \[\leadsto \left(\color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right) \cdot u2 \]
        9. lower-/.f32N/A

          \[\leadsto \left(\sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right) \cdot u2 \]
        10. lower--.f32N/A

          \[\leadsto \left(\sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right) \cdot u2 \]
        11. +-commutativeN/A

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)}\right) \cdot u2 \]
        12. *-commutativeN/A

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}} + \frac{314159265359}{50000000000}\right)\right) \cdot u2 \]
        13. lower-fma.f32N/A

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)}\right) \cdot u2 \]
        14. unpow2N/A

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \frac{314159265359}{50000000000}\right)\right) \cdot u2 \]
        15. lower-*.f3289.5

          \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -41.341702240407926, 6.28318530718\right)\right) \cdot u2 \]
      8. Applied rewrites89.5%

        \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right)\right) \cdot u2} \]
      9. Final simplification89.5%

        \[\leadsto \left(\mathsf{fma}\left(u2 \cdot u2, -41.341702240407926, 6.28318530718\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 \]
      10. Add Preprocessing

      Alternative 20: 78.2% accurate, 3.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= (* u2 6.28318530718) 0.002199999988079071)
         (* (* u2 6.28318530718) (sqrt (fma (fma u1 u1 u1) u1 u1)))
         (* (* (fma -41.341702240407926 (* u2 u2) 6.28318530718) u2) (sqrt u1))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if ((u2 * 6.28318530718f) <= 0.002199999988079071f) {
      		tmp = (u2 * 6.28318530718f) * sqrtf(fmaf(fmaf(u1, u1, u1), u1, u1));
      	} else {
      		tmp = (fmaf(-41.341702240407926f, (u2 * u2), 6.28318530718f) * u2) * sqrtf(u1);
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.002199999988079071))
      		tmp = Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(fma(fma(u1, u1, u1), u1, u1)));
      	else
      		tmp = Float32(Float32(fma(Float32(-41.341702240407926), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(u1));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\
      \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\
      
      \mathbf{else}:\\
      \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.0022

        1. Initial program 98.4%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
          2. lower-*.f3298.0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        5. Applied rewrites98.0%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        6. Taylor expanded in u1 around 0

          \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 \cdot \left(1 + u1\right) + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          2. distribute-rgt-inN/A

            \[\leadsto \sqrt{\color{blue}{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + 1 \cdot u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          3. *-lft-identityN/A

            \[\leadsto \sqrt{\left(u1 \cdot \left(1 + u1\right)\right) \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          4. lower-fma.f32N/A

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1 \cdot \left(1 + u1\right), u1, u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          5. +-commutativeN/A

            \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot \color{blue}{\left(u1 + 1\right)}, u1, u1\right)} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          6. distribute-lft-inN/A

            \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{u1 \cdot u1 + u1 \cdot 1}, u1, u1\right)} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          7. *-rgt-identityN/A

            \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot u1 + \color{blue}{u1}, u1, u1\right)} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          8. lower-fma.f3289.3

            \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1, u1\right)} \cdot \left(u2 \cdot 6.28318530718\right) \]
        8. Applied rewrites89.3%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]

        if 0.0022 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

        1. Initial program 97.5%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
          2. lower-*.f3249.2

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        5. Applied rewrites49.2%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        6. Taylor expanded in u1 around 0

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. Step-by-step derivation
          1. lower-sqrt.f3246.3

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        8. Applied rewrites46.3%

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        9. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
        10. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
          2. lower-*.f32N/A

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
          3. +-commutativeN/A

            \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
          4. lower-fma.f32N/A

            \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
          5. unpow2N/A

            \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
          6. lower-*.f3258.8

            \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(-41.341702240407926, \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
        11. Applied rewrites58.8%

          \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
      3. Recombined 2 regimes into one program.
      4. Final simplification79.4%

        \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\ \;\;\;\;\left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
      5. Add Preprocessing

      Alternative 21: 75.7% accurate, 3.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\ \;\;\;\;\sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= (* u2 6.28318530718) 0.002199999988079071)
         (* (sqrt (* (+ u1 1.0) u1)) (* u2 6.28318530718))
         (* (* (fma -41.341702240407926 (* u2 u2) 6.28318530718) u2) (sqrt u1))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if ((u2 * 6.28318530718f) <= 0.002199999988079071f) {
      		tmp = sqrtf(((u1 + 1.0f) * u1)) * (u2 * 6.28318530718f);
      	} else {
      		tmp = (fmaf(-41.341702240407926f, (u2 * u2), 6.28318530718f) * u2) * sqrtf(u1);
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (Float32(u2 * Float32(6.28318530718)) <= Float32(0.002199999988079071))
      		tmp = Float32(sqrt(Float32(Float32(u1 + Float32(1.0)) * u1)) * Float32(u2 * Float32(6.28318530718)));
      	else
      		tmp = Float32(Float32(fma(Float32(-41.341702240407926), Float32(u2 * u2), Float32(6.28318530718)) * u2) * sqrt(u1));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\
      \;\;\;\;\sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.0022

        1. Initial program 98.4%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
          2. lower-*.f3298.0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        5. Applied rewrites98.0%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        6. Taylor expanded in u1 around 0

          \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          2. distribute-lft-inN/A

            \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          3. *-rgt-identityN/A

            \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          4. lower-fma.f3285.3

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        8. Applied rewrites85.3%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        9. Step-by-step derivation
          1. Applied rewrites85.4%

            \[\leadsto \sqrt{\left(1 + u1\right) \cdot \color{blue}{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]

          if 0.0022 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

          1. Initial program 97.5%

            \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
          2. Add Preprocessing
          3. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
            2. lower-*.f3249.2

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          5. Applied rewrites49.2%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          6. Taylor expanded in u1 around 0

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          7. Step-by-step derivation
            1. lower-sqrt.f3246.3

              \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          8. Applied rewrites46.3%

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          9. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
          10. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
            2. lower-*.f32N/A

              \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
            4. lower-fma.f32N/A

              \[\leadsto \sqrt{u1} \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, {u2}^{2}, \frac{314159265359}{50000000000}\right)} \cdot u2\right) \]
            5. unpow2N/A

              \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{314159265359}{50000000000}\right) \cdot u2\right) \]
            6. lower-*.f3258.8

              \[\leadsto \sqrt{u1} \cdot \left(\mathsf{fma}\left(-41.341702240407926, \color{blue}{u2 \cdot u2}, 6.28318530718\right) \cdot u2\right) \]
          11. Applied rewrites58.8%

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right)} \]
        10. Recombined 2 regimes into one program.
        11. Final simplification76.8%

          \[\leadsto \begin{array}{l} \mathbf{if}\;u2 \cdot 6.28318530718 \leq 0.002199999988079071:\\ \;\;\;\;\sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(-41.341702240407926, u2 \cdot u2, 6.28318530718\right) \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
        12. Add Preprocessing

        Alternative 22: 72.3% accurate, 4.7× speedup?

        \[\begin{array}{l} \\ \sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right) \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (* (sqrt (* (+ u1 1.0) u1)) (* u2 6.28318530718)))
        float code(float cosTheta_i, float u1, float u2) {
        	return sqrtf(((u1 + 1.0f) * u1)) * (u2 * 6.28318530718f);
        }
        
        real(4) function code(costheta_i, u1, u2)
            real(4), intent (in) :: costheta_i
            real(4), intent (in) :: u1
            real(4), intent (in) :: u2
            code = sqrt(((u1 + 1.0e0) * u1)) * (u2 * 6.28318530718e0)
        end function
        
        function code(cosTheta_i, u1, u2)
        	return Float32(sqrt(Float32(Float32(u1 + Float32(1.0)) * u1)) * Float32(u2 * Float32(6.28318530718)))
        end
        
        function tmp = code(cosTheta_i, u1, u2)
        	tmp = sqrt(((u1 + single(1.0)) * u1)) * (u2 * single(6.28318530718));
        end
        
        \begin{array}{l}
        
        \\
        \sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right)
        \end{array}
        
        Derivation
        1. Initial program 98.1%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
          2. lower-*.f3282.1

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        5. Applied rewrites82.1%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
        6. Taylor expanded in u1 around 0

          \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
        7. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          2. distribute-lft-inN/A

            \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          3. *-rgt-identityN/A

            \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          4. lower-fma.f3273.3

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        8. Applied rewrites73.3%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
        9. Step-by-step derivation
          1. Applied rewrites73.3%

            \[\leadsto \sqrt{\left(1 + u1\right) \cdot \color{blue}{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          2. Final simplification73.3%

            \[\leadsto \sqrt{\left(u1 + 1\right) \cdot u1} \cdot \left(u2 \cdot 6.28318530718\right) \]
          3. Add Preprocessing

          Alternative 23: 72.3% accurate, 5.0× speedup?

          \[\begin{array}{l} \\ \left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (* (* u2 6.28318530718) (sqrt (fma u1 u1 u1))))
          float code(float cosTheta_i, float u1, float u2) {
          	return (u2 * 6.28318530718f) * sqrtf(fmaf(u1, u1, u1));
          }
          
          function code(cosTheta_i, u1, u2)
          	return Float32(Float32(u2 * Float32(6.28318530718)) * sqrt(fma(u1, u1, u1)))
          end
          
          \begin{array}{l}
          
          \\
          \left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}
          \end{array}
          
          Derivation
          1. Initial program 98.1%

            \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
          2. Add Preprocessing
          3. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
            2. lower-*.f3282.1

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          5. Applied rewrites82.1%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          6. Taylor expanded in u1 around 0

            \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          7. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
            2. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
            3. *-rgt-identityN/A

              \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
            4. lower-fma.f3273.3

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          8. Applied rewrites73.3%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          9. Final simplification73.3%

            \[\leadsto \left(u2 \cdot 6.28318530718\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \]
          10. Add Preprocessing

          Alternative 24: 64.1% accurate, 6.4× speedup?

          \[\begin{array}{l} \\ \sqrt{u1} \cdot \left(u2 \cdot 6.28318530718\right) \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (* (sqrt u1) (* u2 6.28318530718)))
          float code(float cosTheta_i, float u1, float u2) {
          	return sqrtf(u1) * (u2 * 6.28318530718f);
          }
          
          real(4) function code(costheta_i, u1, u2)
              real(4), intent (in) :: costheta_i
              real(4), intent (in) :: u1
              real(4), intent (in) :: u2
              code = sqrt(u1) * (u2 * 6.28318530718e0)
          end function
          
          function code(cosTheta_i, u1, u2)
          	return Float32(sqrt(u1) * Float32(u2 * Float32(6.28318530718)))
          end
          
          function tmp = code(cosTheta_i, u1, u2)
          	tmp = sqrt(u1) * (u2 * single(6.28318530718));
          end
          
          \begin{array}{l}
          
          \\
          \sqrt{u1} \cdot \left(u2 \cdot 6.28318530718\right)
          \end{array}
          
          Derivation
          1. Initial program 98.1%

            \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
          2. Add Preprocessing
          3. Taylor expanded in u2 around 0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \frac{314159265359}{50000000000}\right)} \]
            2. lower-*.f3282.1

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          5. Applied rewrites82.1%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot 6.28318530718\right)} \]
          6. Taylor expanded in u1 around 0

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot \frac{314159265359}{50000000000}\right) \]
          7. Step-by-step derivation
            1. lower-sqrt.f3265.8

              \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          8. Applied rewrites65.8%

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \left(u2 \cdot 6.28318530718\right) \]
          9. Add Preprocessing

          Reproduce

          ?
          herbie shell --seed 2024240 
          (FPCore (cosTheta_i u1 u2)
            :name "Trowbridge-Reitz 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 (/ u1 (- 1.0 u1))) (sin (* 6.28318530718 u2))))