Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.0%
Time: 6.1s
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}

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, 0.7× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1}{1 - \left(u1 \cdot u1\right) \cdot u1}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \pi\right)\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ (* (fma (+ 1.0 u1) u1 1.0) u1) (- 1.0 (* (* u1 u1) u1))))
  (sin (fma -6.28318530718 u2 (* 0.5 PI)))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf(((fmaf((1.0f + u1), u1, 1.0f) * u1) / (1.0f - ((u1 * u1) * u1)))) * sinf(fmaf(-6.28318530718f, u2, (0.5f * ((float) M_PI))));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(Float32(fma(Float32(Float32(1.0) + u1), u1, Float32(1.0)) * u1) / Float32(Float32(1.0) - Float32(Float32(u1 * u1) * u1)))) * sin(fma(Float32(-6.28318530718), u2, Float32(Float32(0.5) * Float32(pi)))))
end
\begin{array}{l}

\\
\sqrt{\frac{\mathsf{fma}\left(1 + u1, u1, 1\right) \cdot u1}{1 - \left(u1 \cdot u1\right) \cdot u1}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \pi\right)\right)
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{3}}}{1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    6. unpow3N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\color{blue}{\pi}}{2}\right) \]
  5. Applied rewrites98.9%

    \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \color{blue}{\sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right)} \]
  6. Taylor expanded in u2 around inf

    \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + \left(u1 + {u1}^{2}\right)\right)}{1 - {u1}^{3}}} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \frac{314159265359}{50000000000} \cdot u2\right)} \]
  7. Applied rewrites99.0%

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

Alternative 2: 99.0% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (sin (+ (- (* u2 6.28318530718)) (/ PI 2.0)))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * sinf((-(u2 * 6.28318530718f) + (((float) M_PI) / 2.0f)));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(Float32(-Float32(u2 * Float32(6.28318530718))) + Float32(Float32(pi) / Float32(2.0)))))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((-(u2 * single(6.28318530718)) + (single(pi) / single(2.0))));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right)
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{3}}}{1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    6. unpow3N/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\color{blue}{\pi}}{2}\right) \]
  5. Applied rewrites98.9%

    \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \color{blue}{\sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right)} \]
  6. Step-by-step derivation
    1. lift-/.f32N/A

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

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

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

      \[\leadsto \sqrt{\frac{u1}{\frac{{1}^{3} - \color{blue}{\left(u1 \cdot u1\right)} \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    5. lift-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{\frac{{1}^{3} - \color{blue}{\left(u1 \cdot u1\right) \cdot u1}}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    6. pow3N/A

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

      \[\leadsto \sqrt{\frac{u1}{\frac{{1}^{3} - {u1}^{3}}{\color{blue}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    8. metadata-evalN/A

      \[\leadsto \sqrt{\frac{u1}{\frac{{1}^{3} - {u1}^{3}}{\color{blue}{1 \cdot 1} + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    9. lift-*.f32N/A

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

      \[\leadsto \sqrt{\frac{u1}{\frac{{1}^{3} - {u1}^{3}}{1 \cdot 1 + \color{blue}{\left(u1 \cdot u1 + 1 \cdot u1\right)}}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    11. flip3--N/A

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \frac{\pi}{2}\right) \]
    12. lift--.f3299.0

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right) \]
  7. Applied rewrites99.0%

    \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right) \]
  8. Add Preprocessing

Alternative 3: 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 99.0%

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

Alternative 4: 97.7% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ t_1 := \cos \left(6.28318530718 \cdot u2\right)\\ \mathbf{if}\;t\_0 \cdot t\_1 \leq 0.020500000566244125:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot t\_1\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))) (t_1 (cos (* 6.28318530718 u2))))
   (if (<= (* t_0 t_1) 0.020500000566244125)
     (* (sqrt (fma u1 u1 u1)) t_1)
     (*
      t_0
      (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 t_0 = sqrtf((u1 / (1.0f - u1)));
	float t_1 = cosf((6.28318530718f * u2));
	float tmp;
	if ((t_0 * t_1) <= 0.020500000566244125f) {
		tmp = sqrtf(fmaf(u1, u1, u1)) * t_1;
	} else {
		tmp = t_0 * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	t_1 = cos(Float32(Float32(6.28318530718) * u2))
	tmp = Float32(0.0)
	if (Float32(t_0 * t_1) <= Float32(0.020500000566244125))
		tmp = Float32(sqrt(fma(u1, u1, u1)) * t_1);
	else
		tmp = Float32(t_0 * 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}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
t_1 := \cos \left(6.28318530718 \cdot u2\right)\\
\mathbf{if}\;t\_0 \cdot t\_1 \leq 0.020500000566244125:\\
\;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot t\_1\\

\mathbf{else}:\\
\;\;\;\;t\_0 \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 (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))) < 0.0205000006

    1. Initial program 98.9%

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{3}}}{1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. unpow3N/A

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    5. Step-by-step derivation
      1. lift-*.f32N/A

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

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

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

        \[\leadsto \sqrt{u1 \cdot \left(1 + u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    6. Applied rewrites98.0%

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

    if 0.0205000006 < (*.f32 (sqrt.f32 (/.f32 u1 (-.f32 #s(literal 1 binary32) u1))) (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)))

    1. Initial program 99.2%

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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
    3. 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-*.f3297.2

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
    4. Applied rewrites97.2%

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

Alternative 5: 96.7% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.10999999940395355:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sin \left(\mathsf{fma}\left(-6.28318530718, u2, 0.5 \cdot \pi\right)\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= u2 0.10999999940395355)
   (*
    (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))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if (u2 <= 0.10999999940395355f) {
		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
	} else {
		tmp = sinf(fmaf(-6.28318530718f, u2, (0.5f * ((float) M_PI)))) * sqrtf(u1);
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (u2 <= Float32(0.10999999940395355))
		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(sin(fma(Float32(-6.28318530718), u2, Float32(Float32(0.5) * Float32(pi)))) * sqrt(u1));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;u2 \leq 0.10999999940395355:\\
\;\;\;\;\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 \pi\right)\right) \cdot \sqrt{u1}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.109999999

    1. Initial program 99.3%

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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
    3. 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-*.f3299.2

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
    4. Applied rewrites99.2%

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

    if 0.109999999 < u2

    1. Initial program 95.9%

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{3}}}{1 \cdot 1 + \left(u1 \cdot u1 + 1 \cdot u1\right)}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. unpow3N/A

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \color{blue}{\mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      14. lower-*.f3295.8

        \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, \color{blue}{1 \cdot u1}\right)}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    3. Applied rewrites95.8%

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot \frac{314159265359}{50000000000}\right) + \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right) \]
      11. lower-PI.f3296.3

        \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\color{blue}{\pi}}{2}\right) \]
    5. Applied rewrites96.3%

      \[\leadsto \sqrt{\frac{u1}{\frac{1 - \left(u1 \cdot u1\right) \cdot u1}{1 + \mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}}} \cdot \color{blue}{\sin \left(\left(-u2 \cdot 6.28318530718\right) + \frac{\pi}{2}\right)} \]
    6. Taylor expanded in u1 around 0

      \[\leadsto \color{blue}{\sqrt{u1} \cdot \sin \left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \frac{314159265359}{50000000000} \cdot u2\right)} \]
    7. Step-by-step derivation
      1. Applied rewrites73.9%

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

    Alternative 6: 96.6% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.10999999940395355:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.10999999940395355)
       (*
        (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 <= 0.10999999940395355f) {
    		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(0.10999999940395355))
    		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 0.10999999940395355:\\
    \;\;\;\;\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 < 0.109999999

      1. Initial program 99.3%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3299.2

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      4. Applied rewrites99.2%

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

      if 0.109999999 < u2

      1. Initial program 95.9%

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

        \[\leadsto \sqrt{\color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. Step-by-step derivation
        1. Applied rewrites73.0%

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

      Alternative 7: 93.4% accurate, 1.3× 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 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3293.4

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot \color{blue}{u2}, 1\right) \]
      4. Applied rewrites93.4%

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

      Alternative 8: 91.5% accurate, 1.4× speedup?

      \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(64.93939402268539 - \frac{19.739208802181317}{u2 \cdot u2}\right) \cdot \left(u2 \cdot u2\right), u2 \cdot u2, 1\right) \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma
         (* (- 64.93939402268539 (/ 19.739208802181317 (* u2 u2))) (* u2 u2))
         (* u2 u2)
         1.0)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f - (19.739208802181317f / (u2 * u2))) * (u2 * u2)), (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(Float32(19.739208802181317) / Float32(u2 * u2))) * Float32(u2 * u2)), Float32(u2 * u2), Float32(1.0)))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(64.93939402268539 - \frac{19.739208802181317}{u2 \cdot u2}\right) \cdot \left(u2 \cdot u2\right), u2 \cdot u2, 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3291.5

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} - \frac{\frac{98696044010906577398881}{5000000000000000000000}}{u2 \cdot u2}\right) \cdot \left(u2 \cdot u2\right), u2 \cdot u2, 1\right) \]
        10. lift-*.f3291.5

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

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

      Alternative 9: 91.5% accurate, 1.7× 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 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3291.5

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

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

      Alternative 10: 91.5% accurate, 1.7× speedup?

      \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(\left(u2 \cdot u2\right) \cdot 64.93939402268539 - 19.739208802181317\right) \cdot u2, u2, 1\right) \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma (* (- (* (* u2 u2) 64.93939402268539) 19.739208802181317) u2) u2 1.0)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * fmaf(((((u2 * u2) * 64.93939402268539f) - 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(Float32(u2 * u2) * Float32(64.93939402268539)) - Float32(19.739208802181317)) * u2), u2, Float32(1.0)))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(\left(u2 \cdot u2\right) \cdot 64.93939402268539 - 19.739208802181317\right) \cdot u2, u2, 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3291.5

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)} \]
      5. Step-by-step derivation
        1. lift-fma.f32N/A

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) + 1\right) \]
        4. lift-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) + 1\right) \]
        5. lift-*.f32N/A

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\left(\left(u2 \cdot u2\right) \cdot \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot u2, u2, 1\right) \]
        14. lift-*.f3291.5

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

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

      Alternative 11: 88.5% accurate, 2.3× speedup?

      \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(u2 \cdot u2\right) \cdot -19.739208802181317 + 1\right) \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (* (sqrt (/ u1 (- 1.0 u1))) (+ (* (* u2 u2) -19.739208802181317) 1.0)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * (((u2 * u2) * -19.739208802181317f) + 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((u1 / (1.0e0 - u1))) * (((u2 * u2) * (-19.739208802181317e0)) + 1.0e0)
      end function
      
      function code(cosTheta_i, u1, u2)
      	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(Float32(Float32(u2 * u2) * Float32(-19.739208802181317)) + Float32(1.0)))
      end
      
      function tmp = code(cosTheta_i, u1, u2)
      	tmp = sqrt((u1 / (single(1.0) - u1))) * (((u2 * u2) * single(-19.739208802181317)) + single(1.0));
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(u2 \cdot u2\right) \cdot -19.739208802181317 + 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot {u2}^{2} - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)} \]
      3. 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-*.f3291.5

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)} \]
      5. Step-by-step derivation
        1. lift-fma.f32N/A

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) + 1\right) \]
        4. lift-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot \left(u2 \cdot u2\right) + 1\right) \]
        5. lift-*.f32N/A

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot u2\right) \cdot u2 + 1\right) \]
        10. pow2N/A

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\left({u2}^{2} \cdot \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot u2\right) \cdot u2 + 1\right) \]
        14. pow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\left(\left(u2 \cdot u2\right) \cdot \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot u2\right) \cdot u2 + 1\right) \]
        15. lift-*.f3291.5

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(\left(\left(u2 \cdot u2\right) \cdot 64.93939402268539 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + \color{blue}{1}\right) \]
      7. Taylor expanded in u2 around 0

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left({u2}^{2} \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \]
        3. pow2N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(\left(u2 \cdot u2\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000} + 1\right) \]
        4. lift-*.f3288.5

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

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

      Alternative 12: 88.5% accurate, 2.4× speedup?

      \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right) \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (* (sqrt (/ u1 (- 1.0 u1))) (fma (* u2 u2) -19.739208802181317 1.0)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
      }
      
      function code(cosTheta_i, u1, u2)
      	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(1 + \frac{-98696044010906577398881}{5000000000000000000000} \cdot {u2}^{2}\right)} \]
      3. 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-*.f3288.5

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

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

      Alternative 13: 83.3% accurate, 2.3× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.0008999999845400453:\\ \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, u1, u1\right)}{1 - u1 \cdot u1}}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.0008999999845400453)
         (sqrt (/ (fma u1 u1 u1) (- 1.0 (* u1 u1))))
         (fma (* (sqrt u1) -19.739208802181317) (* u2 u2) (sqrt u1))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.0008999999845400453f) {
      		tmp = sqrtf((fmaf(u1, u1, u1) / (1.0f - (u1 * u1))));
      	} else {
      		tmp = fmaf((sqrtf(u1) * -19.739208802181317f), (u2 * u2), sqrtf(u1));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.0008999999845400453))
      		tmp = sqrt(Float32(fma(u1, u1, u1) / Float32(Float32(1.0) - Float32(u1 * u1))));
      	else
      		tmp = fma(Float32(sqrt(u1) * Float32(-19.739208802181317)), Float32(u2 * u2), sqrt(u1));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.0008999999845400453:\\
      \;\;\;\;\sqrt{\frac{\mathsf{fma}\left(u1, u1, u1\right)}{1 - u1 \cdot u1}}\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 8.99999985e-4

        1. Initial program 99.5%

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          7. unpow2N/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-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{u1 \cdot u1}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          9. lower-+.f3299.3

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - u1 \cdot u1}{\color{blue}{1 + u1}}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        3. Applied rewrites99.3%

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

          \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}}} \]
        5. Step-by-step derivation
          1. pow2N/A

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
          2. metadata-evalN/A

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
          3. pow2N/A

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
          4. flip--N/A

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

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{\color{blue}{1} - {u1}^{2}}} \]
          6. sin-+PI/2N/A

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

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
          8. pow2N/A

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

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

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

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

            \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
          13. lift--.f32N/A

            \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
          14. lift-*.f3297.2

            \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
        6. Applied rewrites97.2%

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

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

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

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

            \[\leadsto \sqrt{\frac{u1 \cdot \left(u1 + 1\right)}{1 - u1 \cdot u1}} \]
          5. distribute-rgt-outN/A

            \[\leadsto \sqrt{\frac{u1 \cdot u1 + 1 \cdot u1}{1 - u1 \cdot u1}} \]
          6. lift-fma.f32N/A

            \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, u1, 1 \cdot u1\right)}{1 - u1 \cdot u1}} \]
          7. *-lft-identity97.3

            \[\leadsto \sqrt{\frac{\mathsf{fma}\left(u1, u1, u1\right)}{1 - u1 \cdot u1}} \]
        8. Applied rewrites97.3%

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

        if 8.99999985e-4 < u2

        1. Initial program 97.9%

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          7. unpow2N/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-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{u1 \cdot u1}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          9. lower-+.f3297.9

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - u1 \cdot u1}{\color{blue}{1 + u1}}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        3. Applied rewrites97.9%

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

          \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right)} \]
        5. Step-by-step derivation
          1. pow2N/A

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

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right) \]
          3. pow2N/A

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

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

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

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

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

            \[\leadsto \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000} + \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}}} \]
        6. Applied rewrites64.8%

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

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

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

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

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

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

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

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

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot \frac{-98696044010906577398881}{5000000000000000000000}, u2 \cdot u2, \sqrt{u1}\right) \]
          8. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot \frac{-98696044010906577398881}{5000000000000000000000}, u2 \cdot u2, \sqrt{u1}\right) \]
          9. lift-sqrt.f3253.0

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right) \]
        9. Applied rewrites53.0%

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

      Alternative 14: 83.3% accurate, 2.4× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.0008999999845400453:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.0008999999845400453)
         (sqrt (/ u1 (- 1.0 u1)))
         (fma (* (sqrt u1) -19.739208802181317) (* u2 u2) (sqrt u1))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.0008999999845400453f) {
      		tmp = sqrtf((u1 / (1.0f - u1)));
      	} else {
      		tmp = fmaf((sqrtf(u1) * -19.739208802181317f), (u2 * u2), sqrtf(u1));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.0008999999845400453))
      		tmp = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)));
      	else
      		tmp = fma(Float32(sqrt(u1) * Float32(-19.739208802181317)), Float32(u2 * u2), sqrt(u1));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.0008999999845400453:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 8.99999985e-4

        1. Initial program 99.5%

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
          3. lift-sqrt.f3297.4

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
        4. Applied rewrites97.4%

          \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]

        if 8.99999985e-4 < u2

        1. Initial program 97.9%

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          7. unpow2N/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-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - \color{blue}{u1 \cdot u1}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          9. lower-+.f3297.9

            \[\leadsto \sqrt{\frac{u1}{\frac{1 - u1 \cdot u1}{\color{blue}{1 + u1}}}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        3. Applied rewrites97.9%

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

          \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right)} \]
        5. Step-by-step derivation
          1. pow2N/A

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

            \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} + \frac{-98696044010906577398881}{5000000000000000000000} \cdot \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right) \]
          3. pow2N/A

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

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

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

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

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

            \[\leadsto \left(\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \cdot {u2}^{2}\right) \cdot \frac{-98696044010906577398881}{5000000000000000000000} + \sqrt{\color{blue}{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}}} \]
        6. Applied rewrites64.8%

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

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

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

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

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

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

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

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

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot \frac{-98696044010906577398881}{5000000000000000000000}, u2 \cdot u2, \sqrt{u1}\right) \]
          8. lift-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot \frac{-98696044010906577398881}{5000000000000000000000}, u2 \cdot u2, \sqrt{u1}\right) \]
          9. lift-sqrt.f3253.0

            \[\leadsto \mathsf{fma}\left(\sqrt{u1} \cdot -19.739208802181317, u2 \cdot u2, \sqrt{u1}\right) \]
        9. Applied rewrites53.0%

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

      Alternative 15: 80.2% accurate, 5.3× 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 99.0%

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
        3. lift-sqrt.f3280.2

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \]
      4. Applied rewrites80.2%

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

      Alternative 16: 71.9% accurate, 6.0× speedup?

      \[\begin{array}{l} \\ \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \end{array} \]
      (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (fma u1 u1 u1)))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf(fmaf(u1, u1, u1));
      }
      
      function code(cosTheta_i, u1, u2)
      	return sqrt(fma(u1, u1, u1))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{\mathsf{fma}\left(u1, u1, u1\right)}
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        7. unpow2N/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-*.f32N/A

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

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

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

        \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}}} \]
      5. Step-by-step derivation
        1. pow2N/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        2. metadata-evalN/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        3. pow2N/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        4. flip--N/A

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

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{\color{blue}{1} - {u1}^{2}}} \]
        6. sin-+PI/2N/A

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

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        8. pow2N/A

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

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

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

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

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
        13. lift--.f32N/A

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
        14. lift-*.f3280.0

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
      6. Applied rewrites80.0%

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

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

          \[\leadsto \sqrt{u1 \cdot \left(u1 + 1\right)} \]
        2. distribute-rgt-outN/A

          \[\leadsto \sqrt{u1 \cdot u1 + 1 \cdot u1} \]
        3. lift-fma.f32N/A

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, 1 \cdot u1\right)} \]
        4. *-lft-identity71.9

          \[\leadsto \sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \]
      9. Applied rewrites71.9%

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

      Alternative 17: 63.4% accurate, 16.2× 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 99.0%

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\frac{\color{blue}{1 - {u1}^{2}}}{1 + u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        7. unpow2N/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-*.f32N/A

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

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

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

        \[\leadsto \color{blue}{\sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}}} \]
      5. Step-by-step derivation
        1. pow2N/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        2. metadata-evalN/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        3. pow2N/A

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        4. flip--N/A

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

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{\color{blue}{1} - {u1}^{2}}} \]
        6. sin-+PI/2N/A

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

          \[\leadsto \sqrt{\frac{u1 \cdot \left(1 + u1\right)}{1 - {u1}^{2}}} \]
        8. pow2N/A

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

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

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

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

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
        13. lift--.f32N/A

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
        14. lift-*.f3280.0

          \[\leadsto \sqrt{\frac{\left(1 + u1\right) \cdot u1}{1 - u1 \cdot u1}} \]
      6. Applied rewrites80.0%

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

        \[\leadsto \sqrt{u1} \]
      8. Step-by-step derivation
        1. Applied rewrites63.4%

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

        Reproduce

        ?
        herbie shell --seed 2025113 
        (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))))