Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.0%
Time: 10.7s
Alternatives: 17
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));
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(4) function code(costheta_i, u1, u2)
use fmin_fmax_functions
    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 17 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));
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(4) function code(costheta_i, u1, u2)
use fmin_fmax_functions
    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, 0.4× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{\left(\left(1 + u1\right) \cdot u1\right) \cdot \left(\mathsf{fma}\left(u1, u1, {u1}^{4}\right) + 1\right)}{1 - {u1}^{6}}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt
   (/
    (* (* (+ 1.0 u1) u1) (+ (fma u1 u1 (pow u1 4.0)) 1.0))
    (- 1.0 (pow u1 6.0))))
  (sin (fma -6.28318530718 u2 (* 0.5 (PI))))))
\begin{array}{l}

\\
\sqrt{\frac{\left(\left(1 + u1\right) \cdot u1\right) \cdot \left(\mathsf{fma}\left(u1, u1, {u1}^{4}\right) + 1\right)}{1 - {u1}^{6}}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right)
\end{array}
Derivation
  1. Initial program 98.9%

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1} - u1 \cdot u1}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    4. unpow2N/A

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{u1 \cdot u1}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    8. lower-+.f3298.7

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

    \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1 - u1 \cdot u1}{1 + u1}}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  5. Step-by-step derivation
    1. pow2N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{{u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    2. flip3--N/A

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{\color{blue}{1} - {\left({u1}^{2}\right)}^{3}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{\color{blue}{1 - {\left({u1}^{2}\right)}^{3}}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    6. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - \color{blue}{{\left({u1}^{2}\right)}^{3}}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    7. pow2N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\color{blue}{\left(u1 \cdot u1\right)}}^{3}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    8. lower-*.f32N/A

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{\color{blue}{1} + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    10. lower-+.f32N/A

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{\color{blue}{\left(\frac{4}{2}\right)}} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    12. metadata-evalN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{\left(\frac{4}{2}\right)} \cdot {u1}^{\color{blue}{\left(\frac{4}{2}\right)}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    13. sqr-powN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left(\color{blue}{{u1}^{4}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    14. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \color{blue}{\left({u1}^{4} + 1 \cdot {u1}^{2}\right)}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    15. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left(\color{blue}{{u1}^{4}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    16. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + \color{blue}{1 \cdot {u1}^{2}}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    17. pow2N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \color{blue}{\left(u1 \cdot u1\right)}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    18. lower-*.f3298.7

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \color{blue}{\left(u1 \cdot u1\right)}\right)}}{1 + u1}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  6. Applied rewrites98.7%

    \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}}{1 + u1}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  7. Step-by-step derivation
    1. cos-neg-revN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)} \]
    2. sin-+PI/2-revN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
    3. lower-sin.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
    4. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
    5. lower-neg.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\color{blue}{\left(-\frac{314159265359}{50000000000} \cdot u2\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
    6. *-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-\color{blue}{u2 \cdot \frac{314159265359}{50000000000}}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
    7. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-\color{blue}{u2 \cdot \frac{314159265359}{50000000000}}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
    8. lower-/.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right) \]
    9. lower-PI.f3298.8

      \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right) \]
  8. Applied rewrites98.8%

    \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
  9. Taylor expanded in u2 around inf

    \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(\left(1 + u1\right) \cdot \left(1 + \left({u1}^{2} + {u1}^{4}\right)\right)\right)}{1 - {u1}^{6}}} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \frac{314159265359}{50000000000} \cdot u2\right)} \]
  10. Applied rewrites99.0%

    \[\leadsto \color{blue}{\sqrt{\frac{\left(\left(1 + u1\right) \cdot u1\right) \cdot \left(\mathsf{fma}\left(u1, u1, {u1}^{4}\right) + 1\right)}{1 - {u1}^{6}}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right)} \]
  11. Add Preprocessing

Alternative 2: 85.3% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;t\_0 \cdot \cos \left(6.28318530718 \cdot u2\right) \leq 0.035999998450279236:\\ \;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= (* t_0 (cos (* 6.28318530718 u2))) 0.035999998450279236)
     (* (sqrt (* (+ 1.0 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))) <= 0.035999998450279236f) {
		tmp = sqrtf(((1.0f + 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(0.035999998450279236))
		tmp = Float32(sqrt(Float32(Float32(Float32(1.0) + u1) * u1)) * fma(Float32(u2 * 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 0.035999998450279236:\\
\;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -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))) < 0.0359999985

    1. Initial program 98.7%

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      9. lower-+.f3298.7

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.7%

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left({u2}^{2}, \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
      4. pow2N/A

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
      5. lower-*.f3285.6

        \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
    8. Applied rewrites85.6%

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

      \[\leadsto \sqrt{\left(1 + u1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
    10. Step-by-step derivation
      1. lower-+.f3285.3

        \[\leadsto \sqrt{\left(1 + u1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
    11. Applied rewrites85.3%

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

    if 0.0359999985 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    1. Initial program 99.3%

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

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
      2. lower-/.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
      3. lower--.f3284.7

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
    5. Applied rewrites84.7%

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

Alternative 3: 98.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.1120000034570694:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, 64.93939402268539 \cdot t\_0\right), u2 \cdot u2, -19.739208802181317 \cdot t\_0\right), u2 \cdot u2, t\_0\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= u2 0.1120000034570694)
     (fma
      (fma
       (fma
        -85.45681720672748
        (* (* u2 u2) (sqrt u1))
        (* 64.93939402268539 t_0))
       (* u2 u2)
       (* -19.739208802181317 t_0))
      (* u2 u2)
      t_0)
     (* (sqrt (* (fma (+ 1.0 u1) u1 1.0) u1)) (cos (* 6.28318530718 u2))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if (u2 <= 0.1120000034570694f) {
		tmp = fmaf(fmaf(fmaf(-85.45681720672748f, ((u2 * u2) * sqrtf(u1)), (64.93939402268539f * t_0)), (u2 * u2), (-19.739208802181317f * t_0)), (u2 * u2), t_0);
	} else {
		tmp = sqrtf((fmaf((1.0f + u1), u1, 1.0f) * u1)) * cosf((6.28318530718f * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (u2 <= Float32(0.1120000034570694))
		tmp = fma(fma(fma(Float32(-85.45681720672748), Float32(Float32(u2 * u2) * sqrt(u1)), Float32(Float32(64.93939402268539) * t_0)), Float32(u2 * u2), Float32(Float32(-19.739208802181317) * t_0)), Float32(u2 * u2), t_0);
	else
		tmp = Float32(sqrt(Float32(fma(Float32(Float32(1.0) + u1), u1, Float32(1.0)) * u1)) * cos(Float32(Float32(6.28318530718) * u2)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;u2 \leq 0.1120000034570694:\\
\;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, 64.93939402268539 \cdot t\_0\right), u2 \cdot u2, -19.739208802181317 \cdot t\_0\right), u2 \cdot u2, t\_0\right)\\

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


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.112000003

    1. Initial program 99.4%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    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. Step-by-step derivation
      1. +-commutativeN/A

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

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

        \[\leadsto \mathsf{fma}\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), \color{blue}{{u2}^{2}}, \sqrt{\frac{u1}{1 - u1}}\right) \]
    5. Applied rewrites99.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}, 64.93939402268539 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, -19.739208802181317 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right)} \]
    6. Taylor expanded in u1 around 0

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

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

        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2} \cdot \sqrt{u1}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right) \]
      3. pow2N/A

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

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

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

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

    if 0.112000003 < u2

    1. Initial program 94.6%

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

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

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

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

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

        \[\leadsto \sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. lower-+.f3290.1

        \[\leadsto \sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites90.1%

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

Alternative 4: 82.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.9998999834060669:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= (cos (* 6.28318530718 u2)) 0.9998999834060669)
   (* (sqrt u1) (fma (* u2 u2) -19.739208802181317 1.0))
   (sqrt (/ u1 (- 1.0 u1)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if (cosf((6.28318530718f * u2)) <= 0.9998999834060669f) {
		tmp = sqrtf(u1) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
	} else {
		tmp = sqrtf((u1 / (1.0f - u1)));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (cos(Float32(Float32(6.28318530718) * u2)) <= Float32(0.9998999834060669))
		tmp = Float32(sqrt(u1) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
	else
		tmp = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.9998999834060669:\\
\;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)) < 0.999899983

    1. Initial program 97.4%

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

      \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    4. Step-by-step derivation
      1. Applied rewrites75.6%

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

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

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

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

          \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left({u2}^{2}, \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
        4. pow2N/A

          \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
        5. lower-*.f3252.1

          \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
      4. Applied rewrites52.1%

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

      if 0.999899983 < (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))

      1. Initial program 99.5%

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
        2. lower-/.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
        3. lower--.f3295.7

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
      5. Applied rewrites95.7%

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

    Alternative 5: 97.6% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.1720000058412552:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, 64.93939402268539 \cdot t\_0\right), u2 \cdot u2, -19.739208802181317 \cdot t\_0\right), u2 \cdot u2, t\_0\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
       (if (<= u2 0.1720000058412552)
         (fma
          (fma
           (fma
            -85.45681720672748
            (* (* u2 u2) (sqrt u1))
            (* 64.93939402268539 t_0))
           (* u2 u2)
           (* -19.739208802181317 t_0))
          (* u2 u2)
          t_0)
         (* (sqrt (* (+ 1.0 u1) u1)) (cos (* 6.28318530718 u2))))))
    float code(float cosTheta_i, float u1, float u2) {
    	float t_0 = sqrtf((u1 / (1.0f - u1)));
    	float tmp;
    	if (u2 <= 0.1720000058412552f) {
    		tmp = fmaf(fmaf(fmaf(-85.45681720672748f, ((u2 * u2) * sqrtf(u1)), (64.93939402268539f * t_0)), (u2 * u2), (-19.739208802181317f * t_0)), (u2 * u2), t_0);
    	} else {
    		tmp = sqrtf(((1.0f + u1) * u1)) * cosf((6.28318530718f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.1720000058412552))
    		tmp = fma(fma(fma(Float32(-85.45681720672748), Float32(Float32(u2 * u2) * sqrt(u1)), Float32(Float32(64.93939402268539) * t_0)), Float32(u2 * u2), Float32(Float32(-19.739208802181317) * t_0)), Float32(u2 * u2), t_0);
    	else
    		tmp = Float32(sqrt(Float32(Float32(Float32(1.0) + u1) * u1)) * cos(Float32(Float32(6.28318530718) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \sqrt{\frac{u1}{1 - u1}}\\
    \mathbf{if}\;u2 \leq 0.1720000058412552:\\
    \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, 64.93939402268539 \cdot t\_0\right), u2 \cdot u2, -19.739208802181317 \cdot t\_0\right), u2 \cdot u2, t\_0\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.172000006

      1. Initial program 99.4%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      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. Step-by-step derivation
        1. +-commutativeN/A

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

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

          \[\leadsto \mathsf{fma}\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), \color{blue}{{u2}^{2}}, \sqrt{\frac{u1}{1 - u1}}\right) \]
      5. Applied rewrites98.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}, 64.93939402268539 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, -19.739208802181317 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right)} \]
      6. Taylor expanded in u1 around 0

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

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

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2} \cdot \sqrt{u1}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right) \]
        3. pow2N/A

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

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right) \]
        5. lower-sqrt.f3298.8

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{u1}, 64.93939402268539 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, -19.739208802181317 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right) \]
      8. Applied rewrites98.8%

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

      if 0.172000006 < u2

      1. Initial program 93.8%

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

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

          \[\leadsto \sqrt{\left(1 + u1\right) \cdot \color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. lower-+.f3291.2

          \[\leadsto \sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites91.2%

        \[\leadsto \sqrt{\color{blue}{\left(1 + u1\right) \cdot u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 6: 97.6% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.1720000058412552:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.1720000058412552)
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma
         (-
          (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) (* u2 u2))
          19.739208802181317)
         (* u2 u2)
         1.0))
       (* (sqrt (* (+ 1.0 u1) u1)) (cos (* 6.28318530718 u2)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if (u2 <= 0.1720000058412552f) {
    		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
    	} else {
    		tmp = sqrtf(((1.0f + u1) * u1)) * cosf((6.28318530718f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.1720000058412552))
    		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)));
    	else
    		tmp = Float32(sqrt(Float32(Float32(Float32(1.0) + u1) * u1)) * cos(Float32(Float32(6.28318530718) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.1720000058412552:\\
    \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.172000006

      1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, u2 \cdot \color{blue}{u2}, 1\right) \]
        14. lower-*.f3298.8

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      5. Applied rewrites98.8%

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

      if 0.172000006 < u2

      1. Initial program 93.8%

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

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

          \[\leadsto \sqrt{\left(1 + u1\right) \cdot \color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. lower-+.f3291.2

          \[\leadsto \sqrt{\left(1 + u1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites91.2%

        \[\leadsto \sqrt{\color{blue}{\left(1 + u1\right) \cdot u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 7: 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));
    }
    
    module fmin_fmax_functions
        implicit none
        private
        public fmax
        public fmin
    
        interface fmax
            module procedure fmax88
            module procedure fmax44
            module procedure fmax84
            module procedure fmax48
        end interface
        interface fmin
            module procedure fmin88
            module procedure fmin44
            module procedure fmin84
            module procedure fmin48
        end interface
    contains
        real(8) function fmax88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(4) function fmax44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(8) function fmax84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmax48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
        end function
        real(8) function fmin88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(4) function fmin44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(8) function fmin84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmin48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
        end function
    end module
    
    real(4) function code(costheta_i, u1, u2)
    use fmin_fmax_functions
        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 98.9%

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

    Alternative 8: 96.7% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.1720000058412552:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.1720000058412552)
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma
         (-
          (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) (* u2 u2))
          19.739208802181317)
         (* u2 u2)
         1.0))
       (* (sin (fma -6.28318530718 u2 (* 0.5 (PI)))) (sqrt u1))))
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.1720000058412552:\\
    \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.172000006

      1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, u2 \cdot \color{blue}{u2}, 1\right) \]
        14. lower-*.f3298.8

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      5. Applied rewrites98.8%

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

      if 0.172000006 < u2

      1. Initial program 93.8%

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1} - u1 \cdot u1}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. unpow2N/A

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{u1 \cdot u1}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        8. lower-+.f3294.1

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1 - u1 \cdot u1}{1 + u1}}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Step-by-step derivation
        1. pow2N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{{u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        2. flip3--N/A

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

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{\color{blue}{1} - {\left({u1}^{2}\right)}^{3}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        5. lower--.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{\color{blue}{1 - {\left({u1}^{2}\right)}^{3}}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        6. lower-pow.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - \color{blue}{{\left({u1}^{2}\right)}^{3}}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        7. pow2N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\color{blue}{\left(u1 \cdot u1\right)}}^{3}}{1 \cdot 1 + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        8. lower-*.f32N/A

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{\color{blue}{1} + \left({u1}^{2} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        10. lower-+.f32N/A

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{\color{blue}{\left(\frac{4}{2}\right)}} \cdot {u1}^{2} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        12. metadata-evalN/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{\left(\frac{4}{2}\right)} \cdot {u1}^{\color{blue}{\left(\frac{4}{2}\right)}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        13. sqr-powN/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left(\color{blue}{{u1}^{4}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        14. lower-+.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \color{blue}{\left({u1}^{4} + 1 \cdot {u1}^{2}\right)}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        15. lower-pow.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left(\color{blue}{{u1}^{4}} + 1 \cdot {u1}^{2}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        16. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + \color{blue}{1 \cdot {u1}^{2}}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        17. pow2N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \color{blue}{\left(u1 \cdot u1\right)}\right)}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        18. lower-*.f3294.1

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \color{blue}{\left(u1 \cdot u1\right)}\right)}}{1 + u1}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      6. Applied rewrites94.1%

        \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}}{1 + u1}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      7. Step-by-step derivation
        1. cos-neg-revN/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)} \]
        2. sin-+PI/2-revN/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
        3. lower-sin.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
        4. lower-+.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
        5. lower-neg.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\color{blue}{\left(-\frac{314159265359}{50000000000} \cdot u2\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
        6. *-commutativeN/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-\color{blue}{u2 \cdot \frac{314159265359}{50000000000}}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
        7. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-\color{blue}{u2 \cdot \frac{314159265359}{50000000000}}\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \]
        8. lower-/.f32N/A

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right) \]
        9. lower-PI.f3295.7

          \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right) \]
      8. Applied rewrites95.7%

        \[\leadsto \sqrt{\frac{u1}{\frac{\frac{1 - {\left(u1 \cdot u1\right)}^{3}}{1 + \left({u1}^{4} + 1 \cdot \left(u1 \cdot u1\right)\right)}}{1 + u1}}} \cdot \color{blue}{\sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \]
      9. Taylor expanded in u1 around 0

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

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

          \[\leadsto \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \frac{314159265359}{50000000000} \cdot u2\right) \cdot \color{blue}{\sqrt{u1}} \]
        3. fp-cancel-sub-sign-invN/A

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

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

          \[\leadsto \sin \left(\frac{-314159265359}{50000000000} \cdot u2 + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{u1} \]
        6. lower-sin.f32N/A

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

          \[\leadsto \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1} \]
        8. lower-*.f32N/A

          \[\leadsto \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1} \]
        9. lower-PI.f32N/A

          \[\leadsto \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1} \]
        10. lower-sqrt.f3282.4

          \[\leadsto \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1} \]
      11. Applied rewrites82.4%

        \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \cdot \sqrt{u1}} \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 9: 96.7% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.1720000058412552:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.1720000058412552)
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma
         (-
          (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) (* u2 u2))
          19.739208802181317)
         (* u2 u2)
         1.0))
       (* (sqrt u1) (cos (* 6.28318530718 u2)))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if (u2 <= 0.1720000058412552f) {
    		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
    	} else {
    		tmp = sqrtf(u1) * cosf((6.28318530718f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.1720000058412552))
    		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)));
    	else
    		tmp = Float32(sqrt(u1) * cos(Float32(Float32(6.28318530718) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.1720000058412552:\\
    \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.172000006

      1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, u2 \cdot \color{blue}{u2}, 1\right) \]
        14. lower-*.f3298.8

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      5. Applied rewrites98.8%

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

      if 0.172000006 < u2

      1. Initial program 93.8%

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

        \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. Applied rewrites80.0%

          \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Recombined 2 regimes into one program.
      6. Add Preprocessing

      Alternative 10: 93.3% accurate, 2.1× speedup?

      \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right) \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma
         (-
          (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) (* u2 u2))
          19.739208802181317)
         (* u2 u2)
         1.0)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
      }
      
      function code(cosTheta_i, u1, u2)
      	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)
      \end{array}
      
      Derivation
      1. Initial program 98.9%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, u2 \cdot \color{blue}{u2}, 1\right) \]
        14. lower-*.f3294.0

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      5. Applied rewrites94.0%

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

      Alternative 11: 90.4% accurate, 2.4× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.029999999329447746:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.029999999329447746)
         (* (sqrt (/ u1 (- 1.0 u1))) (fma (* u2 u2) -19.739208802181317 1.0))
         (*
          (sqrt u1)
          (fma
           (-
            (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) (* u2 u2))
            19.739208802181317)
           (* u2 u2)
           1.0))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.029999999329447746f) {
      		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
      	} else {
      		tmp = sqrtf(u1) * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.029999999329447746))
      		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
      	else
      		tmp = Float32(sqrt(u1) * fma(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.029999999329447746:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0299999993

        1. Initial program 99.4%

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
          5. lower-*.f3298.0

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
        5. Applied rewrites98.0%

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

        if 0.0299999993 < u2

        1. Initial program 96.3%

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

          \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. Step-by-step derivation
          1. Applied rewrites78.0%

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

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

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

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

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

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

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

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

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

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right) \]
            9. pow2N/A

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

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right) \]
            11. pow2N/A

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

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right) \]
            13. pow2N/A

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, u2 \cdot \color{blue}{u2}, 1\right) \]
            14. lower-*.f3258.0

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
          4. Applied rewrites58.0%

            \[\leadsto \sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)} \]
        5. Recombined 2 regimes into one program.
        6. Add Preprocessing

        Alternative 12: 91.2% accurate, 2.5× speedup?

        \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right) \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (*
          (sqrt (/ u1 (- 1.0 u1)))
          (fma (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317) (* u2 u2) 1.0)))
        float code(float cosTheta_i, float u1, float u2) {
        	return sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
        }
        
        function code(cosTheta_i, u1, u2)
        	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(Float32(Float32(64.93939402268539) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)))
        end
        
        \begin{array}{l}
        
        \\
        \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)
        \end{array}
        
        Derivation
        1. Initial program 98.9%

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

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

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

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

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

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

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

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

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

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

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

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

        Alternative 13: 85.9% accurate, 2.9× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u1 \leq 0.009999999776482582:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \end{array} \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (if (<= u1 0.009999999776482582)
           (*
            (sqrt (* (fma (+ 1.0 u1) u1 1.0) u1))
            (fma (* u2 u2) -19.739208802181317 1.0))
           (sqrt (/ u1 (- 1.0 u1)))))
        float code(float cosTheta_i, float u1, float u2) {
        	float tmp;
        	if (u1 <= 0.009999999776482582f) {
        		tmp = sqrtf((fmaf((1.0f + u1), u1, 1.0f) * u1)) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
        	} else {
        		tmp = sqrtf((u1 / (1.0f - u1)));
        	}
        	return tmp;
        }
        
        function code(cosTheta_i, u1, u2)
        	tmp = Float32(0.0)
        	if (u1 <= Float32(0.009999999776482582))
        		tmp = Float32(sqrt(Float32(fma(Float32(Float32(1.0) + u1), u1, Float32(1.0)) * u1)) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
        	else
        		tmp = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)));
        	end
        	return tmp
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;u1 \leq 0.009999999776482582:\\
        \;\;\;\;\sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if u1 < 0.00999999978

          1. Initial program 98.7%

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

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

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

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

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

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

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

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

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

              \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
            9. lower-+.f3298.7

              \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          5. Applied rewrites98.7%

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

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

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

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

              \[\leadsto \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(1 + u1, u1, 1\right), u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left({u2}^{2}, \color{blue}{\frac{-98696044010906577398881}{5000000000000000000000}}, 1\right) \]
            4. pow2N/A

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

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

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

            \[\leadsto \sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
          10. Step-by-step derivation
            1. lower-+.f3286.5

              \[\leadsto \sqrt{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
          11. Applied rewrites86.5%

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

          if 0.00999999978 < u1

          1. Initial program 99.4%

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

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
            2. lower-/.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
            3. lower--.f3284.3

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
          5. Applied rewrites84.3%

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

        Alternative 14: 87.9% 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 98.9%

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
          5. lower-*.f3288.1

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \]
        5. Applied rewrites88.1%

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

        Alternative 15: 79.3% 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)));
        }
        
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(4) function code(costheta_i, u1, u2)
        use fmin_fmax_functions
            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 98.9%

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
          2. lower-/.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
          3. lower--.f3278.6

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
        5. Applied rewrites78.6%

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

        Alternative 16: 70.8% accurate, 5.6× speedup?

        \[\begin{array}{l} \\ \sqrt{\left(1 + u1\right) \cdot u1} \cdot 1 \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (* (sqrt (* (+ 1.0 u1) u1)) 1.0))
        float code(float cosTheta_i, float u1, float u2) {
        	return sqrtf(((1.0f + u1) * u1)) * 1.0f;
        }
        
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(4) function code(costheta_i, u1, u2)
        use fmin_fmax_functions
            real(4), intent (in) :: costheta_i
            real(4), intent (in) :: u1
            real(4), intent (in) :: u2
            code = sqrt(((1.0e0 + u1) * u1)) * 1.0e0
        end function
        
        function code(cosTheta_i, u1, u2)
        	return Float32(sqrt(Float32(Float32(Float32(1.0) + u1) * u1)) * Float32(1.0))
        end
        
        function tmp = code(cosTheta_i, u1, u2)
        	tmp = sqrt(((single(1.0) + u1) * u1)) * single(1.0);
        end
        
        \begin{array}{l}
        
        \\
        \sqrt{\left(1 + u1\right) \cdot u1} \cdot 1
        \end{array}
        
        Derivation
        1. Initial program 98.9%

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

          \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. Step-by-step derivation
          1. Applied rewrites73.8%

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

            \[\leadsto \sqrt{u1} \cdot \color{blue}{1} \]
          3. Step-by-step derivation
            1. Applied rewrites62.2%

              \[\leadsto \sqrt{u1} \cdot \color{blue}{1} \]
            2. Taylor expanded in u1 around 0

              \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot 1 \]
            3. Step-by-step derivation
              1. *-commutativeN/A

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

                \[\leadsto \sqrt{\left(1 + u1\right) \cdot \color{blue}{u1}} \cdot 1 \]
              3. lower-+.f3269.5

                \[\leadsto \sqrt{\left(1 + u1\right) \cdot u1} \cdot 1 \]
            4. Applied rewrites69.5%

              \[\leadsto \sqrt{\color{blue}{\left(1 + u1\right) \cdot u1}} \cdot 1 \]
            5. Add Preprocessing

            Alternative 17: 62.5% 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);
            }
            
            module fmin_fmax_functions
                implicit none
                private
                public fmax
                public fmin
            
                interface fmax
                    module procedure fmax88
                    module procedure fmax44
                    module procedure fmax84
                    module procedure fmax48
                end interface
                interface fmin
                    module procedure fmin88
                    module procedure fmin44
                    module procedure fmin84
                    module procedure fmin48
                end interface
            contains
                real(8) function fmax88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(4) function fmax44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                end function
                real(8) function fmax84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmax48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                end function
                real(8) function fmin88(x, y) result (res)
                    real(8), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(4) function fmin44(x, y) result (res)
                    real(4), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                end function
                real(8) function fmin84(x, y) result(res)
                    real(8), intent (in) :: x
                    real(4), intent (in) :: y
                    res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                end function
                real(8) function fmin48(x, y) result(res)
                    real(4), intent (in) :: x
                    real(8), intent (in) :: y
                    res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                end function
            end module
            
            real(4) function code(costheta_i, u1, u2)
            use fmin_fmax_functions
                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 98.9%

              \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            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. Step-by-step derivation
              1. +-commutativeN/A

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

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

                \[\leadsto \mathsf{fma}\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right), \color{blue}{{u2}^{2}}, \sqrt{\frac{u1}{1 - u1}}\right) \]
            5. Applied rewrites94.1%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, \left(u2 \cdot u2\right) \cdot \sqrt{\frac{u1}{1 - u1}}, 64.93939402268539 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, -19.739208802181317 \cdot \sqrt{\frac{u1}{1 - u1}}\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}}\right)} \]
            6. Taylor expanded in u1 around 0

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

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

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

                \[\leadsto \mathsf{fma}\left(\frac{-98696044010906577398881}{5000000000000000000000} \cdot \sqrt{u1} + {u2}^{2} \cdot \left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot \left(\sqrt{u1} \cdot {u2}^{2}\right) + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \sqrt{u1}\right), {u2}^{\color{blue}{2}}, \sqrt{u1}\right) \]
            8. Applied rewrites70.6%

              \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748 \cdot \sqrt{u1}, u2 \cdot u2, \sqrt{u1} \cdot 64.93939402268539\right), u2 \cdot u2, \sqrt{u1} \cdot -19.739208802181317\right), \color{blue}{u2 \cdot u2}, \sqrt{u1}\right) \]
            9. Taylor expanded in u2 around 0

              \[\leadsto \sqrt{u1} \]
            10. Step-by-step derivation
              1. lower-sqrt.f3262.2

                \[\leadsto \sqrt{u1} \]
            11. Applied rewrites62.2%

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

            Reproduce

            ?
            herbie shell --seed 2025043 
            (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))))