Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.0%
Time: 14.3s
Alternatives: 22
Speedup: 1.0×

Specification

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

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \cos \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 22 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 99.0% accurate, 1.0× speedup?

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

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

Alternative 1: 99.0% accurate, 1.0× speedup?

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

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right)
\end{array}
Derivation
  1. Initial program 99.1%

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

Alternative 2: 92.7% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10000000149011612:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\left(u1 + 1\right) \cdot \frac{u1}{1 - u1 \cdot u1}}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<=
      (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2)))
      0.10000000149011612)
   (*
    (fma
     (* u2 u2)
     (fma
      u2
      (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
      -19.739208802181317)
     1.0)
    (sqrt (fma u1 (fma u1 u1 u1) u1)))
   (*
    (fma u2 (* u2 -19.739208802181317) 1.0)
    (sqrt (* (+ u1 1.0) (/ u1 (- 1.0 (* u1 u1))))))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if ((sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2))) <= 0.10000000149011612f) {
		tmp = fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f) * sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1));
	} else {
		tmp = fmaf(u2, (u2 * -19.739208802181317f), 1.0f) * sqrtf(((u1 + 1.0f) * (u1 / (1.0f - (u1 * u1)))));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2))) <= Float32(0.10000000149011612))
		tmp = Float32(fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)) * sqrt(fma(u1, fma(u1, u1, u1), u1)));
	else
		tmp = Float32(fma(u2, Float32(u2 * Float32(-19.739208802181317)), Float32(1.0)) * sqrt(Float32(Float32(u1 + Float32(1.0)) * Float32(u1 / Float32(Float32(1.0) - Float32(u1 * u1))))));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10000000149011612:\\
\;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\left(u1 + 1\right) \cdot \frac{u1}{1 - u1 \cdot u1}}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))) < 0.100000001

    1. Initial program 99.0%

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. flip3--N/A

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

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. associate-*l/N/A

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

        \[\leadsto \sqrt{\color{blue}{\frac{u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{{1}^{3} - {u1}^{3}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. metadata-evalN/A

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

        \[\leadsto \sqrt{\frac{u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}}{{1}^{3} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. distribute-lft-inN/A

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

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

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

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

        \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)}{{1}^{3} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. metadata-evalN/A

        \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{1} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      15. sub-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      16. cube-negN/A

        \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      17. +-commutativeN/A

        \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3} + 1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    4. Applied rewrites97.6%

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\left(u1 + 1\right)} \cdot u1, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      7. distribute-lft1-inN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{u1 \cdot u1 + u1}, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      8. lower-fma.f3297.8

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    7. Applied rewrites97.8%

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

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
    9. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
      2. lower-fma.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
      3. unpow2N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
      4. lower-*.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
      5. sub-negN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
      6. unpow2N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
      7. associate-*l*N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
      8. metadata-evalN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
      10. lower-*.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      11. +-commutativeN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      12. *-commutativeN/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      13. lower-fma.f32N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      14. unpow2N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      15. lower-*.f3290.2

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
    10. Applied rewrites90.2%

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]

    if 0.100000001 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    1. Initial program 99.3%

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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
      2. associate-*r*N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
      3. distribute-rgt1-inN/A

        \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
      4. *-commutativeN/A

        \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
      5. lower-*.f32N/A

        \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
      6. unpow2N/A

        \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
      7. associate-*l*N/A

        \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
      8. lower-fma.f32N/A

        \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
      9. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
      10. *-rgt-identityN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
      11. sub-negN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
      12. rgt-mult-inverseN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
      13. mul-1-negN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
      14. distribute-neg-frac2N/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
      15. mul-1-negN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
      16. *-rgt-identityN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
      17. distribute-lft-inN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
      18. +-commutativeN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
      19. sub-negN/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
      20. associate-*r*N/A

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
    5. Applied rewrites95.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
    6. Step-by-step derivation
      1. Applied rewrites95.5%

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1 \cdot u1} \cdot \left(u1 + 1\right)} \]
    7. Recombined 2 regimes into one program.
    8. Final simplification91.6%

      \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10000000149011612:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\left(u1 + 1\right) \cdot \frac{u1}{1 - u1 \cdot u1}}\\ \end{array} \]
    9. Add Preprocessing

    Alternative 3: 87.1% accurate, 0.8× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10499999672174454:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \frac{1}{1 - u1}}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<=
          (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2)))
          0.10499999672174454)
       (*
        (sqrt (fma u1 (fma u1 u1 u1) u1))
        (fma u2 (* u2 -19.739208802181317) 1.0))
       (sqrt (* u1 (/ 1.0 (- 1.0 u1))))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if ((sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2))) <= 0.10499999672174454f) {
    		tmp = sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1)) * fmaf(u2, (u2 * -19.739208802181317f), 1.0f);
    	} else {
    		tmp = sqrtf((u1 * (1.0f / (1.0f - u1))));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2))) <= Float32(0.10499999672174454))
    		tmp = Float32(sqrt(fma(u1, fma(u1, u1, u1), u1)) * fma(u2, Float32(u2 * Float32(-19.739208802181317)), Float32(1.0)));
    	else
    		tmp = sqrt(Float32(u1 * Float32(Float32(1.0) / Float32(Float32(1.0) - u1))));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10499999672174454:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{u1 \cdot \frac{1}{1 - u1}}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))) < 0.104999997

      1. Initial program 99.0%

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

        \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
      4. Step-by-step derivation
        1. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
        2. associate-*r*N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
        3. distribute-rgt1-inN/A

          \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
        4. *-commutativeN/A

          \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
        5. lower-*.f32N/A

          \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
        6. unpow2N/A

          \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
        7. associate-*l*N/A

          \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
        8. lower-fma.f32N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
        9. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
        10. *-rgt-identityN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
        11. sub-negN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
        12. rgt-mult-inverseN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
        13. mul-1-negN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
        14. distribute-neg-frac2N/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
        15. mul-1-negN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
        16. *-rgt-identityN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
        17. distribute-lft-inN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
        18. +-commutativeN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
        19. sub-negN/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
        20. associate-*r*N/A

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
      5. Applied rewrites84.6%

        \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
      6. Taylor expanded in u1 around 0

        \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)} \]
      7. Step-by-step derivation
        1. Applied rewrites84.5%

          \[\leadsto \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \]

        if 0.104999997 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

        1. Initial program 99.3%

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

          \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
        4. Step-by-step derivation
          1. *-rgt-identityN/A

            \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
          2. sub-negN/A

            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
          3. rgt-mult-inverseN/A

            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
          4. mul-1-negN/A

            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
          5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
        5. Applied rewrites84.8%

          \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
        6. Step-by-step derivation
          1. Applied rewrites84.8%

            \[\leadsto \sqrt{\frac{1}{1 - u1} \cdot u1} \]
        7. Recombined 2 regimes into one program.
        8. Final simplification84.6%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.10499999672174454:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \frac{1}{1 - u1}}\\ \end{array} \]
        9. Add Preprocessing

        Alternative 4: 86.2% accurate, 0.8× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.057999998331069946:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
           (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.057999998331069946)
             (* (sqrt (fma u1 u1 u1)) (fma u2 (* u2 -19.739208802181317) 1.0))
             t_0)))
        float code(float cosTheta_i, float u1, float u2) {
        	float t_0 = sqrtf((u1 / (1.0f - u1)));
        	float tmp;
        	if ((t_0 * cosf((6.28318530718f * u2))) <= 0.057999998331069946f) {
        		tmp = sqrtf(fmaf(u1, u1, u1)) * fmaf(u2, (u2 * -19.739208802181317f), 1.0f);
        	} else {
        		tmp = t_0;
        	}
        	return tmp;
        }
        
        function code(cosTheta_i, u1, u2)
        	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
        	tmp = Float32(0.0)
        	if (Float32(t_0 * cos(Float32(Float32(6.28318530718) * u2))) <= Float32(0.057999998331069946))
        		tmp = Float32(sqrt(fma(u1, u1, u1)) * fma(u2, Float32(u2 * Float32(-19.739208802181317)), Float32(1.0)));
        	else
        		tmp = t_0;
        	end
        	return tmp
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        t_0 := \sqrt{\frac{u1}{1 - u1}}\\
        \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.057999998331069946:\\
        \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;t\_0\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))) < 0.0579999983

          1. Initial program 99.0%

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

            \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
            2. associate-*r*N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
            3. distribute-rgt1-inN/A

              \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
            4. *-commutativeN/A

              \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
            5. lower-*.f32N/A

              \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
            6. unpow2N/A

              \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
            7. associate-*l*N/A

              \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
            8. lower-fma.f32N/A

              \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
            9. lower-*.f32N/A

              \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
            10. *-rgt-identityN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
            11. sub-negN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
            12. rgt-mult-inverseN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
            13. mul-1-negN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
            14. distribute-neg-frac2N/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
            15. mul-1-negN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
            16. *-rgt-identityN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
            17. distribute-lft-inN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
            18. +-commutativeN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
            19. sub-negN/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
            20. associate-*r*N/A

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
          5. Applied rewrites84.7%

            \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
          6. Taylor expanded in u1 around 0

            \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{u1 \cdot \left(1 + u1\right)} \]
          7. Step-by-step derivation
            1. Applied rewrites84.2%

              \[\leadsto \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \]

            if 0.0579999983 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

            1. Initial program 99.3%

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

              \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
            4. Step-by-step derivation
              1. *-rgt-identityN/A

                \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
              2. sub-negN/A

                \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
              3. rgt-mult-inverseN/A

                \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
              4. mul-1-negN/A

                \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
              5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
            5. Applied rewrites83.6%

              \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
          8. Recombined 2 regimes into one program.
          9. Final simplification84.0%

            \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.057999998331069946:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \end{array} \]
          10. Add Preprocessing

          Alternative 5: 83.9% accurate, 0.8× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.0006200000061653554:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(-19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
             (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.0006200000061653554)
               (* (sqrt u1) (fma -19.739208802181317 (* u2 u2) 1.0))
               t_0)))
          float code(float cosTheta_i, float u1, float u2) {
          	float t_0 = sqrtf((u1 / (1.0f - u1)));
          	float tmp;
          	if ((t_0 * cosf((6.28318530718f * u2))) <= 0.0006200000061653554f) {
          		tmp = sqrtf(u1) * fmaf(-19.739208802181317f, (u2 * u2), 1.0f);
          	} else {
          		tmp = t_0;
          	}
          	return tmp;
          }
          
          function code(cosTheta_i, u1, u2)
          	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
          	tmp = Float32(0.0)
          	if (Float32(t_0 * cos(Float32(Float32(6.28318530718) * u2))) <= Float32(0.0006200000061653554))
          		tmp = Float32(sqrt(u1) * fma(Float32(-19.739208802181317), Float32(u2 * u2), Float32(1.0)));
          	else
          		tmp = t_0;
          	end
          	return tmp
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          t_0 := \sqrt{\frac{u1}{1 - u1}}\\
          \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.0006200000061653554:\\
          \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(-19.739208802181317, u2 \cdot u2, 1\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;t\_0\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))) < 6.20000006e-4

            1. Initial program 98.8%

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

              \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
            4. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
              2. associate-*r*N/A

                \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
              3. distribute-rgt1-inN/A

                \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
              4. *-commutativeN/A

                \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
              5. lower-*.f32N/A

                \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
              6. unpow2N/A

                \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
              7. associate-*l*N/A

                \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
              8. lower-fma.f32N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
              9. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
              10. *-rgt-identityN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
              11. sub-negN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
              12. rgt-mult-inverseN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
              13. mul-1-negN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
              14. distribute-neg-frac2N/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
              15. mul-1-negN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
              16. *-rgt-identityN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
              17. distribute-lft-inN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
              18. +-commutativeN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
              19. sub-negN/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
              20. associate-*r*N/A

                \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
            5. Applied rewrites78.8%

              \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
            6. Taylor expanded in u1 around 0

              \[\leadsto \sqrt{u1} \cdot \color{blue}{\left(1 + \frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right)} \]
            7. Step-by-step derivation
              1. Applied rewrites78.4%

                \[\leadsto \sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(-19.739208802181317, u2 \cdot u2, 1\right)} \]

              if 6.20000006e-4 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

              1. Initial program 99.2%

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

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              4. Step-by-step derivation
                1. *-rgt-identityN/A

                  \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                2. sub-negN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                3. rgt-mult-inverseN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                4. mul-1-negN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
              5. Applied rewrites83.4%

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
            8. Recombined 2 regimes into one program.
            9. Add Preprocessing

            Alternative 6: 98.2% accurate, 0.9× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1 \cdot \mathsf{fma}\left(u1, u1 + 1, 1\right)}\\ \end{array} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (if (<= (* 6.28318530718 u2) 0.6000000238418579)
               (*
                (sqrt (/ (fma u1 (fma u1 u1 u1) u1) (- (- -1.0) (* u1 (* u1 u1)))))
                (fma
                 (* u2 u2)
                 (fma
                  u2
                  (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                  -19.739208802181317)
                 1.0))
               (* (cos (* 6.28318530718 u2)) (sqrt (* u1 (fma u1 (+ u1 1.0) 1.0))))))
            float code(float cosTheta_i, float u1, float u2) {
            	float tmp;
            	if ((6.28318530718f * u2) <= 0.6000000238418579f) {
            		tmp = sqrtf((fmaf(u1, fmaf(u1, u1, u1), u1) / (-(-1.0f) - (u1 * (u1 * u1))))) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
            	} else {
            		tmp = cosf((6.28318530718f * u2)) * sqrtf((u1 * fmaf(u1, (u1 + 1.0f), 1.0f)));
            	}
            	return tmp;
            }
            
            function code(cosTheta_i, u1, u2)
            	tmp = Float32(0.0)
            	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.6000000238418579))
            		tmp = Float32(sqrt(Float32(fma(u1, fma(u1, u1, u1), u1) / Float32(Float32(-Float32(-1.0)) - Float32(u1 * Float32(u1 * u1))))) * fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)));
            	else
            		tmp = Float32(cos(Float32(Float32(6.28318530718) * u2)) * sqrt(Float32(u1 * fma(u1, Float32(u1 + Float32(1.0)), Float32(1.0)))));
            	end
            	return tmp
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\
            \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1 \cdot \mathsf{fma}\left(u1, u1 + 1, 1\right)}\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.600000024

              1. Initial program 99.5%

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                3. flip3--N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                5. associate-*l/N/A

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

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

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

                  \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)\right)}}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                9. metadata-evalN/A

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                11. distribute-lft-inN/A

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

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

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

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                16. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                17. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)\right)}\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                18. cube-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Applied rewrites99.5%

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
                2. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
                3. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                4. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                5. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
                6. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                7. associate-*l*N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                8. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
                9. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
                10. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                11. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                12. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                13. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                14. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                15. lower-*.f3299.4

                  \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
              7. Applied rewrites99.4%

                \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]

              if 0.600000024 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

              1. Initial program 96.4%

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                3. flip3--N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                5. associate-*l/N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}{{1}^{3} - {u1}^{3}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                7. metadata-evalN/A

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

                  \[\leadsto \sqrt{\frac{u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}}{{1}^{3} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                9. distribute-lft-inN/A

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

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

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

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

                  \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)}{{1}^{3} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                14. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{1} - {u1}^{3}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                15. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                16. cube-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                17. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3} + 1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Applied rewrites88.2%

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

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

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

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

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

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

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

                  \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\left(u1 + 1\right)} \cdot u1, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                7. distribute-lft1-inN/A

                  \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{u1 \cdot u1 + u1}, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                8. lower-fma.f3288.9

                  \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              7. Applied rewrites88.9%

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

                \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1 + 1, 1\right) \cdot \color{blue}{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            3. Recombined 2 regimes into one program.
            4. Final simplification98.2%

              \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1 \cdot \mathsf{fma}\left(u1, u1 + 1, 1\right)}\\ \end{array} \]
            5. Add Preprocessing

            Alternative 7: 98.2% accurate, 0.9× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\\ \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{t\_0}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{t\_0}\\ \end{array} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (let* ((t_0 (fma u1 (fma u1 u1 u1) u1)))
               (if (<= (* 6.28318530718 u2) 0.6000000238418579)
                 (*
                  (sqrt (/ t_0 (- (- -1.0) (* u1 (* u1 u1)))))
                  (fma
                   (* u2 u2)
                   (fma
                    u2
                    (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                    -19.739208802181317)
                   1.0))
                 (* (cos (* 6.28318530718 u2)) (sqrt t_0)))))
            float code(float cosTheta_i, float u1, float u2) {
            	float t_0 = fmaf(u1, fmaf(u1, u1, u1), u1);
            	float tmp;
            	if ((6.28318530718f * u2) <= 0.6000000238418579f) {
            		tmp = sqrtf((t_0 / (-(-1.0f) - (u1 * (u1 * u1))))) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
            	} else {
            		tmp = cosf((6.28318530718f * u2)) * sqrtf(t_0);
            	}
            	return tmp;
            }
            
            function code(cosTheta_i, u1, u2)
            	t_0 = fma(u1, fma(u1, u1, u1), u1)
            	tmp = Float32(0.0)
            	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.6000000238418579))
            		tmp = Float32(sqrt(Float32(t_0 / Float32(Float32(-Float32(-1.0)) - Float32(u1 * Float32(u1 * u1))))) * fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)));
            	else
            		tmp = Float32(cos(Float32(Float32(6.28318530718) * u2)) * sqrt(t_0));
            	end
            	return tmp
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\\
            \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\
            \;\;\;\;\sqrt{\frac{t\_0}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{t\_0}\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.600000024

              1. Initial program 99.5%

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                3. flip3--N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                5. associate-*l/N/A

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

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

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

                  \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)\right)}}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                9. metadata-evalN/A

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                11. distribute-lft-inN/A

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

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

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

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                16. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                17. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)\right)}\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                18. cube-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Applied rewrites99.5%

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
                2. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
                3. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                4. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                5. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
                6. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                7. associate-*l*N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                8. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
                9. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
                10. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                11. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                12. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                13. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                14. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                15. lower-*.f3299.4

                  \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
              7. Applied rewrites99.4%

                \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]

              if 0.600000024 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

              1. Initial program 96.4%

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

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

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

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

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

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

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

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

                  \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1 \cdot u1 + \color{blue}{u1}, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                8. lower-fma.f3288.9

                  \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              5. Applied rewrites88.9%

                \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            3. Recombined 2 regimes into one program.
            4. Final simplification98.2%

              \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\ \end{array} \]
            5. Add Preprocessing

            Alternative 8: 97.9% accurate, 1.0× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (if (<= (* 6.28318530718 u2) 0.6000000238418579)
               (*
                (sqrt (/ (fma u1 (fma u1 u1 u1) u1) (- (- -1.0) (* u1 (* u1 u1)))))
                (fma
                 (* u2 u2)
                 (fma
                  u2
                  (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                  -19.739208802181317)
                 1.0))
               (* (cos (* 6.28318530718 u2)) (sqrt (fma u1 u1 u1)))))
            float code(float cosTheta_i, float u1, float u2) {
            	float tmp;
            	if ((6.28318530718f * u2) <= 0.6000000238418579f) {
            		tmp = sqrtf((fmaf(u1, fmaf(u1, u1, u1), u1) / (-(-1.0f) - (u1 * (u1 * u1))))) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
            	} else {
            		tmp = cosf((6.28318530718f * u2)) * sqrtf(fmaf(u1, u1, u1));
            	}
            	return tmp;
            }
            
            function code(cosTheta_i, u1, u2)
            	tmp = Float32(0.0)
            	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.6000000238418579))
            		tmp = Float32(sqrt(Float32(fma(u1, fma(u1, u1, u1), u1) / Float32(Float32(-Float32(-1.0)) - Float32(u1 * Float32(u1 * u1))))) * fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)));
            	else
            		tmp = Float32(cos(Float32(Float32(6.28318530718) * u2)) * sqrt(fma(u1, u1, u1)));
            	end
            	return tmp
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\
            \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\cos \left(6.28318530718 \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) < 0.600000024

              1. Initial program 99.5%

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                3. flip3--N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                5. associate-*l/N/A

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

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

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

                  \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)\right)}}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                9. metadata-evalN/A

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                11. distribute-lft-inN/A

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

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

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

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                16. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                17. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)\right)}\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                18. cube-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Applied rewrites99.5%

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
                2. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
                3. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                4. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                5. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
                6. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                7. associate-*l*N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                8. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
                9. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
                10. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                11. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                12. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                13. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                14. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                15. lower-*.f3299.4

                  \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
              7. Applied rewrites99.4%

                \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]

              if 0.600000024 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

              1. Initial program 96.4%

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

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

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

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

                  \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                4. lower-fma.f3284.4

                  \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              5. Applied rewrites84.4%

                \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            3. Recombined 2 regimes into one program.
            4. Final simplification97.6%

              \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.6000000238418579:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \]
            5. Add Preprocessing

            Alternative 9: 96.9% accurate, 1.0× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.9800000190734863:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (if (<= (* 6.28318530718 u2) 0.9800000190734863)
               (*
                (sqrt (/ (fma u1 (fma u1 u1 u1) u1) (- (- -1.0) (* u1 (* u1 u1)))))
                (fma
                 (* u2 u2)
                 (fma
                  u2
                  (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                  -19.739208802181317)
                 1.0))
               (* (cos (* 6.28318530718 u2)) (sqrt u1))))
            float code(float cosTheta_i, float u1, float u2) {
            	float tmp;
            	if ((6.28318530718f * u2) <= 0.9800000190734863f) {
            		tmp = sqrtf((fmaf(u1, fmaf(u1, u1, u1), u1) / (-(-1.0f) - (u1 * (u1 * u1))))) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
            	} else {
            		tmp = cosf((6.28318530718f * u2)) * sqrtf(u1);
            	}
            	return tmp;
            }
            
            function code(cosTheta_i, u1, u2)
            	tmp = Float32(0.0)
            	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.9800000190734863))
            		tmp = Float32(sqrt(Float32(fma(u1, fma(u1, u1, u1), u1) / Float32(Float32(-Float32(-1.0)) - Float32(u1 * Float32(u1 * u1))))) * fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)));
            	else
            		tmp = Float32(cos(Float32(Float32(6.28318530718) * u2)) * sqrt(u1));
            	end
            	return tmp
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.9800000190734863:\\
            \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\cos \left(6.28318530718 \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) < 0.980000019

              1. Initial program 99.4%

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                3. flip3--N/A

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                5. associate-*l/N/A

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

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

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

                  \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)\right)}}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                9. metadata-evalN/A

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                11. distribute-lft-inN/A

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

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

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

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

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                16. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                17. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)\right)}\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                18. cube-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Applied rewrites99.4%

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
                2. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
                3. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                4. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                5. sub-negN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
                6. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                7. associate-*l*N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                8. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
                9. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
                10. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                11. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                12. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                13. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                14. unpow2N/A

                  \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                15. lower-*.f3299.0

                  \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
              7. Applied rewrites99.0%

                \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]

              if 0.980000019 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

              1. Initial program 95.9%

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

                \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Step-by-step derivation
                1. lower-sqrt.f3267.0

                  \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              5. Applied rewrites67.0%

                \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            3. Recombined 2 regimes into one program.
            4. Final simplification95.9%

              \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.9800000190734863:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
            5. Add Preprocessing

            Alternative 10: 93.7% accurate, 1.6× speedup?

            \[\begin{array}{l} \\ \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (*
              (sqrt (/ (fma u1 (fma u1 u1 u1) u1) (- (- -1.0) (* u1 (* u1 u1)))))
              (fma
               (* u2 u2)
               (fma
                u2
                (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                -19.739208802181317)
               1.0)))
            float code(float cosTheta_i, float u1, float u2) {
            	return sqrtf((fmaf(u1, fmaf(u1, u1, u1), u1) / (-(-1.0f) - (u1 * (u1 * u1))))) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
            }
            
            function code(cosTheta_i, u1, u2)
            	return Float32(sqrt(Float32(fma(u1, fma(u1, u1, u1), u1) / Float32(Float32(-Float32(-1.0)) - Float32(u1 * Float32(u1 * u1))))) * fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)))
            end
            
            \begin{array}{l}
            
            \\
            \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)
            \end{array}
            
            Derivation
            1. Initial program 99.1%

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

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

                \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              3. flip3--N/A

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

                \[\leadsto \sqrt{\color{blue}{\frac{u1}{{1}^{3} - {u1}^{3}} \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              5. associate-*l/N/A

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

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

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

                \[\leadsto \sqrt{\frac{\color{blue}{\mathsf{neg}\left(u1 \cdot \left(1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)\right)\right)}}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              9. metadata-evalN/A

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(u1 \cdot \color{blue}{\left(\left(u1 \cdot u1 + 1 \cdot u1\right) + 1\right)}\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              11. distribute-lft-inN/A

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

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

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

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

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)\right)}{\mathsf{neg}\left(\left({1}^{3} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              16. metadata-evalN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(\color{blue}{1} - {u1}^{3}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              17. sub-negN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\color{blue}{\left(1 + \left(\mathsf{neg}\left({u1}^{3}\right)\right)\right)}\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              18. cube-negN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{\mathsf{neg}\left(\left(1 + \color{blue}{{\left(\mathsf{neg}\left(u1\right)\right)}^{3}}\right)\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
            4. Applied rewrites99.0%

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

              \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
              2. lower-fma.f32N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
              3. unpow2N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
              4. lower-*.f32N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
              5. sub-negN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
              6. unpow2N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
              7. associate-*l*N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
              8. metadata-evalN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
              9. lower-fma.f32N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
              10. lower-*.f32N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
              11. +-commutativeN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
              12. *-commutativeN/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
              13. lower-fma.f32N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
              14. unpow2N/A

                \[\leadsto \sqrt{\frac{\mathsf{neg}\left(\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
              15. lower-*.f3292.6

                \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
            7. Applied rewrites92.6%

              \[\leadsto \sqrt{\frac{-\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{-1 + u1 \cdot \left(u1 \cdot u1\right)}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]
            8. Final simplification92.6%

              \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}{\left(--1\right) - u1 \cdot \left(u1 \cdot u1\right)}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
            9. Add Preprocessing

            Alternative 11: 93.7% accurate, 1.6× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathsf{fma}\left(u2 \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right)\right), u2, t\_0\right) \end{array} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
               (fma
                (*
                 u2
                 (*
                  t_0
                  (fma
                   (* u2 u2)
                   (fma u2 (* u2 -85.45681720672748) 64.93939402268539)
                   -19.739208802181317)))
                u2
                t_0)))
            float code(float cosTheta_i, float u1, float u2) {
            	float t_0 = sqrtf((u1 / (1.0f - u1)));
            	return fmaf((u2 * (t_0 * fmaf((u2 * u2), fmaf(u2, (u2 * -85.45681720672748f), 64.93939402268539f), -19.739208802181317f))), u2, t_0);
            }
            
            function code(cosTheta_i, u1, u2)
            	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
            	return fma(Float32(u2 * Float32(t_0 * fma(Float32(u2 * u2), fma(u2, Float32(u2 * Float32(-85.45681720672748)), Float32(64.93939402268539)), Float32(-19.739208802181317)))), u2, t_0)
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \sqrt{\frac{u1}{1 - u1}}\\
            \mathsf{fma}\left(u2 \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right)\right), u2, t\_0\right)
            \end{array}
            \end{array}
            
            Derivation
            1. Initial program 99.1%

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

              \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)} \]
            4. Applied rewrites92.5%

              \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot -85.45681720672748, \mathsf{fma}\left(u2, u2 \cdot 64.93939402268539, -19.739208802181317\right)\right), \sqrt{\frac{u1}{1 - u1}}\right)} \]
            5. Step-by-step derivation
              1. Applied rewrites92.5%

                \[\leadsto \mathsf{fma}\left(u2 \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right)\right), \color{blue}{u2}, \sqrt{\frac{u1}{1 - u1}}\right) \]
              2. Add Preprocessing

              Alternative 12: 93.6% accurate, 1.6× speedup?

              \[\begin{array}{l} \\ \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\frac{u1}{\frac{-1 + u1 \cdot u1}{-1 - u1}}} \end{array} \]
              (FPCore (cosTheta_i u1 u2)
               :precision binary32
               (*
                (fma
                 (* u2 u2)
                 (fma
                  u2
                  (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
                  -19.739208802181317)
                 1.0)
                (sqrt (/ u1 (/ (+ -1.0 (* u1 u1)) (- -1.0 u1))))))
              float code(float cosTheta_i, float u1, float u2) {
              	return fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f) * sqrtf((u1 / ((-1.0f + (u1 * u1)) / (-1.0f - u1))));
              }
              
              function code(cosTheta_i, u1, u2)
              	return Float32(fma(Float32(u2 * u2), fma(u2, Float32(u2 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539))), Float32(-19.739208802181317)), Float32(1.0)) * sqrt(Float32(u1 / Float32(Float32(Float32(-1.0) + Float32(u1 * u1)) / Float32(Float32(-1.0) - u1)))))
              end
              
              \begin{array}{l}
              
              \\
              \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\frac{u1}{\frac{-1 + u1 \cdot u1}{-1 - u1}}}
              \end{array}
              
              Derivation
              1. Initial program 99.1%

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

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

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

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

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

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

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

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

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

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

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\color{blue}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
                11. lower-neg.f3299.0

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\color{blue}{\left(-u1\right)} - 1}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              4. Applied rewrites99.0%

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

                \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
              6. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)} \]
                2. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right)} \]
                3. unpow2N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                4. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, 1\right) \]
                5. sub-negN/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}, 1\right) \]
                6. unpow2N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\left(u2 \cdot u2\right)} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                7. associate-*l*N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} + \left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right), 1\right) \]
                8. metadata-evalN/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, u2 \cdot \left(u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)\right) + \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
                9. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right)}, 1\right) \]
                10. lower-*.f32N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                11. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                12. *-commutativeN/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \left(\color{blue}{{u2}^{2} \cdot \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                13. lower-fma.f32N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                14. unpow2N/A

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(\mathsf{neg}\left(u1\right)\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
                15. lower-*.f3292.5

                  \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(-u1\right) - 1}}} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
              7. Applied rewrites92.5%

                \[\leadsto \sqrt{\frac{u1}{\frac{u1 \cdot u1 - 1}{\left(-u1\right) - 1}}} \cdot \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)} \]
              8. Final simplification92.5%

                \[\leadsto \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \cdot \sqrt{\frac{u1}{\frac{-1 + u1 \cdot u1}{-1 - u1}}} \]
              9. Add Preprocessing

              Alternative 13: 91.8% accurate, 1.8× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathsf{fma}\left(t\_0 \cdot \left(u2 \cdot u2\right), \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), t\_0\right) \end{array} \end{array} \]
              (FPCore (cosTheta_i u1 u2)
               :precision binary32
               (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
                 (fma
                  (* t_0 (* u2 u2))
                  (fma (* u2 u2) 64.93939402268539 -19.739208802181317)
                  t_0)))
              float code(float cosTheta_i, float u1, float u2) {
              	float t_0 = sqrtf((u1 / (1.0f - u1)));
              	return fmaf((t_0 * (u2 * u2)), fmaf((u2 * u2), 64.93939402268539f, -19.739208802181317f), t_0);
              }
              
              function code(cosTheta_i, u1, u2)
              	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
              	return fma(Float32(t_0 * Float32(u2 * u2)), fma(Float32(u2 * u2), Float32(64.93939402268539), Float32(-19.739208802181317)), t_0)
              end
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              t_0 := \sqrt{\frac{u1}{1 - u1}}\\
              \mathsf{fma}\left(t\_0 \cdot \left(u2 \cdot u2\right), \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), t\_0\right)
              \end{array}
              \end{array}
              
              Derivation
              1. Initial program 99.1%

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

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              4. Step-by-step derivation
                1. *-rgt-identityN/A

                  \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                2. sub-negN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                3. rgt-mult-inverseN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                4. mul-1-negN/A

                  \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
              5. Applied rewrites78.4%

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              6. Taylor expanded in u1 around 0

                \[\leadsto \sqrt{u1} \]
              7. Step-by-step derivation
                1. Applied rewrites60.1%

                  \[\leadsto \sqrt{u1} \]
                2. Taylor expanded in u2 around 0

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)} \]
                3. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto \color{blue}{{u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right) + \sqrt{\frac{u1}{1 - u1}}} \]
                  2. distribute-rgt-inN/A

                    \[\leadsto \color{blue}{\left(\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot {u2}^{2} + \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right) \cdot {u2}^{2}\right)} + \sqrt{\frac{u1}{1 - u1}} \]
                  3. associate-*r*N/A

                    \[\leadsto \left(\color{blue}{\frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} + \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right) \cdot {u2}^{2}\right) + \sqrt{\frac{u1}{1 - u1}} \]
                  4. *-commutativeN/A

                    \[\leadsto \left(\color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right) \cdot {u2}^{2}\right) + \sqrt{\frac{u1}{1 - u1}} \]
                  5. *-commutativeN/A

                    \[\leadsto \left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000} + \color{blue}{\left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot {u2}^{2}\right) + \sqrt{\frac{u1}{1 - u1}} \]
                  6. associate-*l*N/A

                    \[\leadsto \left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000} + \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)}\right) + \sqrt{\frac{u1}{1 - u1}} \]
                  7. distribute-lft-outN/A

                    \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} + \sqrt{\frac{u1}{1 - u1}} \]
                  8. +-commutativeN/A

                    \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{-98696044010906577398881}{5000000000000000000000}\right)} + \sqrt{\frac{u1}{1 - u1}} \]
                  9. metadata-evalN/A

                    \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} + \color{blue}{\left(\mathsf{neg}\left(\frac{98696044010906577398881}{5000000000000000000000}\right)\right)}\right) + \sqrt{\frac{u1}{1 - u1}} \]
                  10. sub-negN/A

                    \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}\right)} + \sqrt{\frac{u1}{1 - u1}} \]
                  11. lower-fma.f32N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}\right)} \]
                4. Applied rewrites90.9%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(u2 \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}, \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), \sqrt{\frac{u1}{1 - u1}}\right)} \]
                5. Final simplification90.9%

                  \[\leadsto \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot u2\right), \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), \sqrt{\frac{u1}{1 - u1}}\right) \]
                6. Add Preprocessing

                Alternative 14: 91.8% accurate, 1.8× speedup?

                \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathsf{fma}\left(u2 \cdot u2, t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), t\_0\right) \end{array} \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
                   (fma
                    (* u2 u2)
                    (* t_0 (fma (* u2 u2) 64.93939402268539 -19.739208802181317))
                    t_0)))
                float code(float cosTheta_i, float u1, float u2) {
                	float t_0 = sqrtf((u1 / (1.0f - u1)));
                	return fmaf((u2 * u2), (t_0 * fmaf((u2 * u2), 64.93939402268539f, -19.739208802181317f)), t_0);
                }
                
                function code(cosTheta_i, u1, u2)
                	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
                	return fma(Float32(u2 * u2), Float32(t_0 * fma(Float32(u2 * u2), Float32(64.93939402268539), Float32(-19.739208802181317))), t_0)
                end
                
                \begin{array}{l}
                
                \\
                \begin{array}{l}
                t_0 := \sqrt{\frac{u1}{1 - u1}}\\
                \mathsf{fma}\left(u2 \cdot u2, t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), t\_0\right)
                \end{array}
                \end{array}
                
                Derivation
                1. Initial program 99.1%

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

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                4. Step-by-step derivation
                  1. *-rgt-identityN/A

                    \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                  2. sub-negN/A

                    \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                  3. rgt-mult-inverseN/A

                    \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                  4. mul-1-negN/A

                    \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                  5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                    \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                5. Applied rewrites78.4%

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                6. Taylor expanded in u2 around 0

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)} \]
                7. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto \color{blue}{{u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right) + \sqrt{\frac{u1}{1 - u1}}} \]
                  2. lower-fma.f32N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left({u2}^{2}, \frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right), \sqrt{\frac{u1}{1 - u1}}\right)} \]
                8. Applied rewrites90.9%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), \sqrt{\frac{u1}{1 - u1}}\right)} \]
                9. Add Preprocessing

                Alternative 15: 91.8% accurate, 2.2× speedup?

                \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot 64.93939402268539, \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\right) \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (*
                  (sqrt (/ u1 (- 1.0 u1)))
                  (fma
                   (* u2 u2)
                   (* (* u2 u2) 64.93939402268539)
                   (fma u2 (* u2 -19.739208802181317) 1.0))))
                float code(float cosTheta_i, float u1, float u2) {
                	return sqrtf((u1 / (1.0f - u1))) * fmaf((u2 * u2), ((u2 * u2) * 64.93939402268539f), fmaf(u2, (u2 * -19.739208802181317f), 1.0f));
                }
                
                function code(cosTheta_i, u1, u2)
                	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(u2 * u2), Float32(Float32(u2 * u2) * Float32(64.93939402268539)), fma(u2, Float32(u2 * Float32(-19.739208802181317)), Float32(1.0))))
                end
                
                \begin{array}{l}
                
                \\
                \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot 64.93939402268539, \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\right)
                \end{array}
                
                Derivation
                1. Initial program 99.1%

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

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)} \]
                4. Applied rewrites90.9%

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot 64.93939402268539, \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\right)} \]
                5. Add Preprocessing

                Alternative 16: 88.8% accurate, 3.1× speedup?

                \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \left(1 + u2 \cdot \left(u2 \cdot -19.739208802181317\right)\right) \end{array} \]
                (FPCore (cosTheta_i u1 u2)
                 :precision binary32
                 (* (sqrt (/ u1 (- 1.0 u1))) (+ 1.0 (* u2 (* u2 -19.739208802181317)))))
                float code(float cosTheta_i, float u1, float u2) {
                	return sqrtf((u1 / (1.0f - u1))) * (1.0f + (u2 * (u2 * -19.739208802181317f)));
                }
                
                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))) * (1.0e0 + (u2 * (u2 * (-19.739208802181317e0))))
                end function
                
                function code(cosTheta_i, u1, u2)
                	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(Float32(1.0) + Float32(u2 * Float32(u2 * Float32(-19.739208802181317)))))
                end
                
                function tmp = code(cosTheta_i, u1, u2)
                	tmp = sqrt((u1 / (single(1.0) - u1))) * (single(1.0) + (u2 * (u2 * single(-19.739208802181317))));
                end
                
                \begin{array}{l}
                
                \\
                \sqrt{\frac{u1}{1 - u1}} \cdot \left(1 + u2 \cdot \left(u2 \cdot -19.739208802181317\right)\right)
                \end{array}
                
                Derivation
                1. Initial program 99.1%

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

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
                4. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
                  2. associate-*r*N/A

                    \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                  3. distribute-rgt1-inN/A

                    \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                  4. *-commutativeN/A

                    \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                  5. lower-*.f32N/A

                    \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                  6. unpow2N/A

                    \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                  7. associate-*l*N/A

                    \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                  8. lower-fma.f32N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
                  9. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                  10. *-rgt-identityN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                  11. sub-negN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                  12. rgt-mult-inverseN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                  13. mul-1-negN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                  14. distribute-neg-frac2N/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                  15. mul-1-negN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
                  16. *-rgt-identityN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
                  17. distribute-lft-inN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
                  18. +-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
                  19. sub-negN/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
                  20. associate-*r*N/A

                    \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
                5. Applied rewrites87.3%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                6. Step-by-step derivation
                  1. Applied rewrites87.3%

                    \[\leadsto \left(u2 \cdot \left(u2 \cdot -19.739208802181317\right) + 1\right) \cdot \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
                  2. Final simplification87.3%

                    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(1 + u2 \cdot \left(u2 \cdot -19.739208802181317\right)\right) \]
                  3. Add Preprocessing

                  Alternative 17: 88.8% accurate, 3.3× speedup?

                  \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \end{array} \]
                  (FPCore (cosTheta_i u1 u2)
                   :precision binary32
                   (* (sqrt (/ u1 (- 1.0 u1))) (fma u2 (* u2 -19.739208802181317) 1.0)))
                  float code(float cosTheta_i, float u1, float u2) {
                  	return sqrtf((u1 / (1.0f - u1))) * fmaf(u2, (u2 * -19.739208802181317f), 1.0f);
                  }
                  
                  function code(cosTheta_i, u1, u2)
                  	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(u2, Float32(u2 * Float32(-19.739208802181317)), Float32(1.0)))
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)
                  \end{array}
                  
                  Derivation
                  1. Initial program 99.1%

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

                    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)} \]
                  4. Step-by-step derivation
                    1. *-commutativeN/A

                      \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \color{blue}{\left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
                    2. associate-*r*N/A

                      \[\leadsto \sqrt{\frac{u1}{1 - u1}} + \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                    3. distribute-rgt1-inN/A

                      \[\leadsto \color{blue}{\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                    4. *-commutativeN/A

                      \[\leadsto \left(\color{blue}{{u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000}} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                    5. lower-*.f32N/A

                      \[\leadsto \color{blue}{\left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                    6. unpow2N/A

                      \[\leadsto \left(\color{blue}{\left(u2 \cdot u2\right)} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                    7. associate-*l*N/A

                      \[\leadsto \left(\color{blue}{u2 \cdot \left(u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}\right)} + 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                    8. lower-fma.f32N/A

                      \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \cdot \sqrt{\frac{u1}{1 - u1}} \]
                    9. lower-*.f32N/A

                      \[\leadsto \mathsf{fma}\left(u2, \color{blue}{u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}} \]
                    10. *-rgt-identityN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                    11. sub-negN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                    12. rgt-mult-inverseN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    13. mul-1-negN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    14. distribute-neg-frac2N/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    15. mul-1-negN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{-1 \cdot u1}}} \]
                    16. *-rgt-identityN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \color{blue}{\left(-1 \cdot u1\right) \cdot 1}}} \]
                    17. distribute-lft-inN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + 1\right)}}} \]
                    18. +-commutativeN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 + \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right)\right)}}} \]
                    19. sub-negN/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \color{blue}{\left(1 - \frac{1}{u1}\right)}}} \]
                    20. associate-*r*N/A

                      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 \cdot 1}{\color{blue}{-1 \cdot \left(u1 \cdot \left(1 - \frac{1}{u1}\right)\right)}}} \]
                  5. Applied rewrites87.3%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
                  6. Final simplification87.3%

                    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \]
                  7. Add Preprocessing

                  Alternative 18: 80.5% accurate, 5.4× speedup?

                  \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \end{array} \]
                  (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (/ u1 (- 1.0 u1))))
                  float code(float cosTheta_i, float u1, float u2) {
                  	return sqrtf((u1 / (1.0f - u1)));
                  }
                  
                  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)))
                  end function
                  
                  function code(cosTheta_i, u1, u2)
                  	return sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
                  end
                  
                  function tmp = code(cosTheta_i, u1, u2)
                  	tmp = sqrt((u1 / (single(1.0) - u1)));
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  \sqrt{\frac{u1}{1 - u1}}
                  \end{array}
                  
                  Derivation
                  1. Initial program 99.1%

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

                    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                  4. Step-by-step derivation
                    1. *-rgt-identityN/A

                      \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                    2. sub-negN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                    3. rgt-mult-inverseN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    4. mul-1-negN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                  5. Applied rewrites78.4%

                    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                  6. Add Preprocessing

                  Alternative 19: 75.0% accurate, 5.9× speedup?

                  \[\begin{array}{l} \\ \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \end{array} \]
                  (FPCore (cosTheta_i u1 u2)
                   :precision binary32
                   (sqrt (fma u1 (fma u1 u1 u1) u1)))
                  float code(float cosTheta_i, float u1, float u2) {
                  	return sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1));
                  }
                  
                  function code(cosTheta_i, u1, u2)
                  	return sqrt(fma(u1, fma(u1, u1, u1), u1))
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}
                  \end{array}
                  
                  Derivation
                  1. Initial program 99.1%

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

                    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                  4. Step-by-step derivation
                    1. *-rgt-identityN/A

                      \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                    2. sub-negN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                    3. rgt-mult-inverseN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    4. mul-1-negN/A

                      \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                    5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                  5. Applied rewrites78.4%

                    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                  6. Taylor expanded in u1 around 0

                    \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)} \]
                  7. Step-by-step derivation
                    1. Applied rewrites71.4%

                      \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \]
                    2. Add Preprocessing

                    Alternative 20: 72.2% accurate, 7.1× speedup?

                    \[\begin{array}{l} \\ \sqrt{u1 + u1 \cdot u1} \end{array} \]
                    (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (+ u1 (* u1 u1))))
                    float code(float cosTheta_i, float u1, float u2) {
                    	return sqrtf((u1 + (u1 * u1)));
                    }
                    
                    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 + (u1 * u1)))
                    end function
                    
                    function code(cosTheta_i, u1, u2)
                    	return sqrt(Float32(u1 + Float32(u1 * u1)))
                    end
                    
                    function tmp = code(cosTheta_i, u1, u2)
                    	tmp = sqrt((u1 + (u1 * u1)));
                    end
                    
                    \begin{array}{l}
                    
                    \\
                    \sqrt{u1 + u1 \cdot u1}
                    \end{array}
                    
                    Derivation
                    1. Initial program 99.1%

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

                      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                    4. Step-by-step derivation
                      1. *-rgt-identityN/A

                        \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                      2. sub-negN/A

                        \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                      3. rgt-mult-inverseN/A

                        \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                      4. mul-1-negN/A

                        \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                      5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                    5. Applied rewrites78.4%

                      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                    6. Taylor expanded in u1 around 0

                      \[\leadsto \sqrt{u1 \cdot \left(1 + u1\right)} \]
                    7. Step-by-step derivation
                      1. Applied rewrites68.5%

                        \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \]
                      2. Step-by-step derivation
                        1. Applied rewrites68.5%

                          \[\leadsto \sqrt{u1 \cdot u1 + u1} \]
                        2. Final simplification68.5%

                          \[\leadsto \sqrt{u1 + u1 \cdot u1} \]
                        3. Add Preprocessing

                        Alternative 21: 72.2% accurate, 7.9× speedup?

                        \[\begin{array}{l} \\ \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \end{array} \]
                        (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (fma u1 u1 u1)))
                        float code(float cosTheta_i, float u1, float u2) {
                        	return sqrtf(fmaf(u1, u1, u1));
                        }
                        
                        function code(cosTheta_i, u1, u2)
                        	return sqrt(fma(u1, u1, u1))
                        end
                        
                        \begin{array}{l}
                        
                        \\
                        \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}
                        \end{array}
                        
                        Derivation
                        1. Initial program 99.1%

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

                          \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                        4. Step-by-step derivation
                          1. *-rgt-identityN/A

                            \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                          2. sub-negN/A

                            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                          3. rgt-mult-inverseN/A

                            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                          4. mul-1-negN/A

                            \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                          5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                            \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                        5. Applied rewrites78.4%

                          \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                        6. Taylor expanded in u1 around 0

                          \[\leadsto \sqrt{u1 \cdot \left(1 + u1\right)} \]
                        7. Step-by-step derivation
                          1. Applied rewrites68.5%

                            \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \]
                          2. Add Preprocessing

                          Alternative 22: 63.7% accurate, 12.3× speedup?

                          \[\begin{array}{l} \\ \sqrt{u1} \end{array} \]
                          (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt u1))
                          float code(float cosTheta_i, float u1, float u2) {
                          	return sqrtf(u1);
                          }
                          
                          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)
                          end function
                          
                          function code(cosTheta_i, u1, u2)
                          	return sqrt(u1)
                          end
                          
                          function tmp = code(cosTheta_i, u1, u2)
                          	tmp = sqrt(u1);
                          end
                          
                          \begin{array}{l}
                          
                          \\
                          \sqrt{u1}
                          \end{array}
                          
                          Derivation
                          1. Initial program 99.1%

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

                            \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                          4. Step-by-step derivation
                            1. *-rgt-identityN/A

                              \[\leadsto \sqrt{\frac{\color{blue}{u1 \cdot 1}}{1 - u1}} \]
                            2. sub-negN/A

                              \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{1 + \left(\mathsf{neg}\left(u1\right)\right)}}} \]
                            3. rgt-mult-inverseN/A

                              \[\leadsto \sqrt{\frac{u1 \cdot 1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \frac{1}{-1 \cdot u1}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                            4. mul-1-negN/A

                              \[\leadsto \sqrt{\frac{u1 \cdot 1}{\left(-1 \cdot u1\right) \cdot \frac{1}{\color{blue}{\mathsf{neg}\left(u1\right)}} + \left(\mathsf{neg}\left(u1\right)\right)}} \]
                            5. distribute-neg-frac2N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

                              \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot u1\right) \cdot \left(\mathsf{neg}\left(\frac{1}{u1}\right)\right) + \left(-1 \cdot u1\right) \cdot 1}}} \]
                          5. Applied rewrites78.4%

                            \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                          6. Taylor expanded in u1 around 0

                            \[\leadsto \sqrt{u1} \]
                          7. Step-by-step derivation
                            1. Applied rewrites60.1%

                              \[\leadsto \sqrt{u1} \]
                            2. Add Preprocessing

                            Reproduce

                            ?
                            herbie shell --seed 2024226 
                            (FPCore (cosTheta_i u1 u2)
                              :name "Trowbridge-Reitz Sample, near normal, slope_x"
                              :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))) (cos (* 6.28318530718 u2))))