Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.0%
Time: 12.3s
Alternatives: 20
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 20 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 99.0%

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

Alternative 2: 92.4% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(t\_0, \left(u2 \cdot u2\right) \cdot -19.739208802181317, t\_0\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.06499999761581421)
     (*
      (sqrt (fma u1 (fma u1 u1 u1) u1))
      (fma
       (* u2 u2)
       (fma
        (* u2 u2)
        (fma (* u2 u2) -85.45681720672748 64.93939402268539)
        -19.739208802181317)
       1.0))
     (fma t_0 (* (* u2 u2) -19.739208802181317) 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))) <= 0.06499999761581421f) {
		tmp = sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1)) * fmaf((u2 * u2), fmaf((u2 * u2), fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f), -19.739208802181317f), 1.0f);
	} else {
		tmp = fmaf(t_0, ((u2 * u2) * -19.739208802181317f), 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(0.06499999761581421))
		tmp = Float32(sqrt(fma(u1, fma(u1, u1, u1), u1)) * fma(Float32(u2 * u2), fma(Float32(u2 * u2), fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)), Float32(-19.739208802181317)), Float32(1.0)));
	else
		tmp = fma(t_0, Float32(Float32(u2 * u2) * Float32(-19.739208802181317)), 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 0.06499999761581421:\\
\;\;\;\;\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 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(t\_0, \left(u2 \cdot u2\right) \cdot -19.739208802181317, t\_0\right)\\


\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))) < 0.0649999976

    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 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.f3298.4

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.4%

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \]
      6. lower-*.f3286.7

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, \color{blue}{u2 \cdot -19.739208802181317}, 1\right) \]
    8. Applied rewrites86.7%

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      14. lower-*.f3291.6

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
    11. Applied rewrites91.6%

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

    if 0.0649999976 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    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. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites89.1%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(u2 \cdot u2\right), \sqrt{\color{blue}{\frac{u1}{1 + -1 \cdot u1}}}\right) \]
    8. Applied rewrites94.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, -19.739208802181317 \cdot \left(u2 \cdot u2\right), \sqrt{\frac{u1}{1 - u1}}\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification92.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \left(u2 \cdot u2\right) \cdot -19.739208802181317, \sqrt{\frac{u1}{1 - u1}}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 92.4% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.06499999761581421)
     (*
      (sqrt (fma u1 (fma u1 u1 u1) u1))
      (fma
       (* u2 u2)
       (fma
        (* u2 u2)
        (fma (* u2 u2) -85.45681720672748 64.93939402268539)
        -19.739208802181317)
       1.0))
     (* t_0 (fma (* u2 u2) -19.739208802181317 1.0)))))
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))) <= 0.06499999761581421f) {
		tmp = sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1)) * fmaf((u2 * u2), fmaf((u2 * u2), fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f), -19.739208802181317f), 1.0f);
	} else {
		tmp = t_0 * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
	}
	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(0.06499999761581421))
		tmp = Float32(sqrt(fma(u1, fma(u1, u1, u1), u1)) * fma(Float32(u2 * u2), fma(Float32(u2 * u2), fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)), Float32(-19.739208802181317)), Float32(1.0)));
	else
		tmp = Float32(t_0 * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
	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 0.06499999761581421:\\
\;\;\;\;\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 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\

\mathbf{else}:\\
\;\;\;\;t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\


\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))) < 0.0649999976

    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 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.f3298.4

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.4%

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \]
      6. lower-*.f3286.7

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, \color{blue}{u2 \cdot -19.739208802181317}, 1\right) \]
    8. Applied rewrites86.7%

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right), \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right) \]
      14. lower-*.f3291.6

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
    11. Applied rewrites91.6%

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

    if 0.0649999976 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + \color{blue}{1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites94.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification92.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 4: 92.4% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.06499999761581421)
     (*
      (sqrt (fma u1 (fma u1 u1 u1) u1))
      (fma
       (* u2 u2)
       (fma
        u2
        (* u2 (fma (* u2 u2) -85.45681720672748 64.93939402268539))
        -19.739208802181317)
       1.0))
     (* t_0 (fma (* u2 u2) -19.739208802181317 1.0)))))
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))) <= 0.06499999761581421f) {
		tmp = sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1)) * fmaf((u2 * u2), fmaf(u2, (u2 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f)), -19.739208802181317f), 1.0f);
	} else {
		tmp = t_0 * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
	}
	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(0.06499999761581421))
		tmp = Float32(sqrt(fma(u1, fma(u1, u1, 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(t_0 * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
	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 0.06499999761581421:\\
\;\;\;\;\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(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\

\mathbf{else}:\\
\;\;\;\;t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\


\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))) < 0.0649999976

    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 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.f3298.4

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.4%

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

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
    7. 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-*.f3291.6

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \]
    8. Applied rewrites91.6%

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

    if 0.0649999976 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + \color{blue}{1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites94.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification92.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.06499999761581421:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 5: 86.4% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.0989999994635582:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.0989999994635582)
     (*
      (sqrt (fma u1 (fma u1 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))) <= 0.0989999994635582f) {
		tmp = sqrtf(fmaf(u1, fmaf(u1, 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(0.0989999994635582))
		tmp = Float32(sqrt(fma(u1, fma(u1, 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 0.0989999994635582:\\
\;\;\;\;\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}:\\
\;\;\;\;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))) < 0.0989999995

    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 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.f3298.3

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.3%

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \]
      6. lower-*.f3286.9

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, \color{blue}{u2 \cdot -19.739208802181317}, 1\right) \]
    8. Applied rewrites86.9%

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

    if 0.0989999995 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
    4. Step-by-step derivation
      1. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites89.3%

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

Alternative 6: 85.6% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.04800000041723251:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.04800000041723251)
     (* (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))) <= 0.04800000041723251f) {
		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(0.04800000041723251))
		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 0.04800000041723251:\\
\;\;\;\;\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))) < 0.0480000004

    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 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.f3298.5

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \color{blue}{\mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right)} \]
      6. lower-*.f3286.8

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)} \cdot \mathsf{fma}\left(u2, \color{blue}{u2 \cdot -19.739208802181317}, 1\right) \]
    8. Applied rewrites86.8%

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

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

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

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

        \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
      4. lower-fma.f3286.0

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \]
    11. Applied rewrites86.0%

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

    if 0.0480000004 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    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. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites87.7%

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

Alternative 7: 97.8% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.20000000298023224:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, t\_0 \cdot \mathsf{fma}\left(64.93939402268539, u2 \cdot u2, -19.739208802181317\right), t\_0\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* 6.28318530718 u2) 0.20000000298023224)
     (fma
      (* u2 u2)
      (* t_0 (fma 64.93939402268539 (* u2 u2) -19.739208802181317))
      t_0)
     (* (cos (* 6.28318530718 u2)) (sqrt (fma u1 (fma u1 u1 u1) u1))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if ((6.28318530718f * u2) <= 0.20000000298023224f) {
		tmp = fmaf((u2 * u2), (t_0 * fmaf(64.93939402268539f, (u2 * u2), -19.739208802181317f)), t_0);
	} else {
		tmp = cosf((6.28318530718f * u2)) * sqrtf(fmaf(u1, fmaf(u1, u1, u1), u1));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.20000000298023224))
		tmp = fma(Float32(u2 * u2), Float32(t_0 * fma(Float32(64.93939402268539), Float32(u2 * u2), Float32(-19.739208802181317))), t_0);
	else
		tmp = Float32(cos(Float32(Float32(6.28318530718) * u2)) * sqrt(fma(u1, fma(u1, u1, u1), u1)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;6.28318530718 \cdot u2 \leq 0.20000000298023224:\\
\;\;\;\;\mathsf{fma}\left(u2 \cdot u2, t\_0 \cdot \mathsf{fma}\left(64.93939402268539, u2 \cdot u2, -19.739208802181317\right), t\_0\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}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 #s(literal 314159265359/50000000000 binary32) u2) < 0.200000003

    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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)} \]
    4. Applied rewrites99.3%

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

    if 0.200000003 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

    1. Initial program 97.7%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    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.f3291.6

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites91.6%

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

    \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.20000000298023224:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539, u2 \cdot u2, -19.739208802181317\right), \sqrt{\frac{u1}{1 - u1}}\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, \mathsf{fma}\left(u1, u1, u1\right), u1\right)}\\ \end{array} \]
  5. Add Preprocessing

Alternative 8: 97.7% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.699999988079071:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* 6.28318530718 u2) 0.699999988079071)
     (fma
      (* u2 u2)
      (*
       (* u2 u2)
       (* t_0 (fma (* u2 u2) -85.45681720672748 64.93939402268539)))
      (* t_0 (fma (* u2 u2) -19.739208802181317 1.0)))
     (* (cos (* 6.28318530718 u2)) (sqrt (fma u1 u1 u1))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if ((6.28318530718f * u2) <= 0.699999988079071f) {
		tmp = fmaf((u2 * u2), ((u2 * u2) * (t_0 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f))), (t_0 * fmaf((u2 * u2), -19.739208802181317f, 1.0f)));
	} else {
		tmp = cosf((6.28318530718f * u2)) * sqrtf(fmaf(u1, u1, u1));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (Float32(Float32(6.28318530718) * u2) <= Float32(0.699999988079071))
		tmp = fma(Float32(u2 * u2), Float32(Float32(u2 * u2) * Float32(t_0 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)))), Float32(t_0 * fma(Float32(u2 * u2), 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}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;6.28318530718 \cdot u2 \leq 0.699999988079071:\\
\;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\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) < 0.699999988

    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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)} \]
    4. Applied rewrites99.1%

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

    if 0.699999988 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

    1. Initial program 97.3%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    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.f3287.2

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites87.2%

      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification97.7%

    \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 0.699999988079071:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}\\ \end{array} \]
  5. Add Preprocessing

Alternative 9: 96.7% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;6.28318530718 \cdot u2 \leq 1.100000023841858:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* 6.28318530718 u2) 1.100000023841858)
     (fma
      (* u2 u2)
      (*
       (* u2 u2)
       (* t_0 (fma (* u2 u2) -85.45681720672748 64.93939402268539)))
      (* t_0 (fma (* u2 u2) -19.739208802181317 1.0)))
     (* (cos (* 6.28318530718 u2)) (sqrt u1)))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if ((6.28318530718f * u2) <= 1.100000023841858f) {
		tmp = fmaf((u2 * u2), ((u2 * u2) * (t_0 * fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f))), (t_0 * fmaf((u2 * u2), -19.739208802181317f, 1.0f)));
	} else {
		tmp = cosf((6.28318530718f * u2)) * sqrtf(u1);
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (Float32(Float32(6.28318530718) * u2) <= Float32(1.100000023841858))
		tmp = fma(Float32(u2 * u2), Float32(Float32(u2 * u2) * Float32(t_0 * fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)))), Float32(t_0 * fma(Float32(u2 * u2), 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}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;6.28318530718 \cdot u2 \leq 1.100000023841858:\\
\;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\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) < 1.10000002

    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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)} \]
    4. Applied rewrites98.1%

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

    if 1.10000002 < (*.f32 #s(literal 314159265359/50000000000 binary32) u2)

    1. Initial program 96.9%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    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.f3275.2

        \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites75.2%

      \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification96.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;6.28318530718 \cdot u2 \leq 1.100000023841858:\\ \;\;\;\;\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \left(6.28318530718 \cdot u2\right) \cdot \sqrt{u1}\\ \end{array} \]
  5. Add Preprocessing

Alternative 10: 93.4% accurate, 1.3× speedup?

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

\\
\begin{array}{l}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), t\_0 \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\right)
\end{array}
\end{array}
Derivation
  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

    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)} \]
  4. Applied rewrites92.7%

    \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, \left(u2 \cdot u2\right) \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right)\right), \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
  5. Final simplification92.7%

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

Alternative 11: 93.2% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}} \cdot \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (/ (sqrt (fma u1 u1 u1)) (sqrt (fma u1 (- u1) 1.0)))
  (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, u1, u1)) / sqrtf(fmaf(u1, -u1, 1.0f))) * 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(Float32(sqrt(fma(u1, u1, u1)) / sqrt(fma(u1, Float32(-u1), Float32(1.0)))) * fma(u2, Float32(u2 * fma(Float32(u2 * u2), fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)), Float32(-19.739208802181317))), Float32(1.0)))
end
\begin{array}{l}

\\
\frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}} \cdot \mathsf{fma}\left(u2, u2 \cdot \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)
\end{array}
Derivation
  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-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\color{blue}{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    20. lower-neg.f3298.8

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, \color{blue}{-u1}, 1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  4. Applied rewrites98.8%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Alternative 12: 93.1% accurate, 1.6× speedup?

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

\\
\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right), -19.739208802181317\right), 1\right)}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}}
\end{array}
Derivation
  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-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\color{blue}{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    20. lower-neg.f3298.8

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, \color{blue}{-u1}, 1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  4. Applied rewrites98.8%

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

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

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

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

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

      \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \]
    6. lower-/.f3298.8

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\frac{\cos \left(6.28318530718 \cdot u2\right)}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}}} \]
  6. Applied rewrites98.8%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Alternative 13: 91.4% accurate, 1.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathsf{fma}\left(u2 \cdot u2, t\_0 \cdot \mathsf{fma}\left(64.93939402268539, u2 \cdot u2, -19.739208802181317\right), t\_0\right) \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (fma
    (* u2 u2)
    (* t_0 (fma 64.93939402268539 (* u2 u2) -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(64.93939402268539f, (u2 * u2), -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(64.93939402268539), Float32(u2 * u2), 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(64.93939402268539, u2 \cdot u2, -19.739208802181317\right), t\_0\right)
\end{array}
\end{array}
Derivation
  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

    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right)\right)} \]
  4. Applied rewrites91.5%

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

Alternative 14: 91.1% accurate, 1.8× speedup?

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

\\
\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(u2 \cdot u2, 64.93939402268539, -19.739208802181317\right), 1\right)}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}}
\end{array}
Derivation
  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-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\color{blue}{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    20. lower-neg.f3298.8

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, \color{blue}{-u1}, 1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  4. Applied rewrites98.8%

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

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

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

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

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

      \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \]
    6. lower-/.f3298.8

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \color{blue}{\frac{\cos \left(6.28318530718 \cdot u2\right)}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}}} \]
  6. Applied rewrites98.8%

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}, \frac{-98696044010906577398881}{5000000000000000000000}\right), 1\right)}{\sqrt{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}} \]
    10. lower-*.f3291.3

      \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \frac{\mathsf{fma}\left(u2 \cdot u2, \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, 64.93939402268539, -19.739208802181317\right), 1\right)}{\sqrt{\mathsf{fma}\left(u1, -u1, 1\right)}} \]
  9. Applied rewrites91.3%

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

Alternative 15: 88.1% accurate, 2.6× speedup?

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

\\
\mathsf{fma}\left(u2, u2 \cdot -19.739208802181317, 1\right) \cdot \sqrt{\frac{\mathsf{fma}\left(u1, u1, u1\right)}{\mathsf{fma}\left(u1, -u1, 1\right)}}
\end{array}
Derivation
  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-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\color{blue}{\mathsf{fma}\left(u1, \mathsf{neg}\left(u1\right), 1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    20. lower-neg.f3298.8

      \[\leadsto \frac{\sqrt{\mathsf{fma}\left(u1, u1, u1\right)}}{\sqrt{\mathsf{fma}\left(u1, \color{blue}{-u1}, 1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  4. Applied rewrites98.8%

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1 + \color{blue}{u1 \cdot u1}}{1 + -1 \cdot {u1}^{2}}} \]
    13. *-rgt-identityN/A

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

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

      \[\leadsto \mathsf{fma}\left(u2, u2 \cdot \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 + -1 \cdot {u1}^{2}}}} \]
  7. Applied rewrites88.6%

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

Alternative 16: 88.1% accurate, 3.3× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \end{array} \]
(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(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)))
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)
\end{array}
Derivation
  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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \cdot \sqrt{\frac{u1}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + \color{blue}{1 \cdot \left(-1 \cdot u1\right)}}} \]
  5. Applied rewrites88.6%

    \[\leadsto \color{blue}{\mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \cdot \sqrt{\frac{u1}{1 - u1}}} \]
  6. Final simplification88.6%

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

Alternative 17: 79.9% 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 99.0%

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

    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
  4. Step-by-step derivation
    1. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
  5. Applied rewrites81.3%

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

Alternative 18: 74.2% 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 99.0%

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

    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
  4. Step-by-step derivation
    1. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
  5. Applied rewrites81.3%

    \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
  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 rewrites74.4%

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

    Alternative 19: 71.3% 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 99.0%

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

      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
    4. Step-by-step derivation
      1. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
    5. Applied rewrites81.3%

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

      \[\leadsto \sqrt{u1 \cdot \left(1 + u1\right)} \]
    7. Step-by-step derivation
      1. Applied rewrites71.3%

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

      Alternative 20: 63.0% 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 99.0%

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

        \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
      4. Step-by-step derivation
        1. lower-sqrt.f32N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(-1 \cdot \frac{1}{u1}\right) \cdot \left(-1 \cdot u1\right) + 1 \cdot \left(-1 \cdot u1\right)}}} \]
      5. Applied rewrites81.3%

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

        \[\leadsto \sqrt{u1} \]
      7. Step-by-step derivation
        1. Applied rewrites62.7%

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

        Reproduce

        ?
        herbie shell --seed 2024236 
        (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))))