Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.1%
Time: 9.6s
Alternatives: 22
Speedup: 1.0×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2));
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(4) function code(costheta_i, u1, u2)
use fmin_fmax_functions
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * cos((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * cos((single(6.28318530718) * u2));
end
\begin{array}{l}

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

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 22 alternatives:

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

Initial Program: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2));
}
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: 99.1% accurate, 1.0× speedup?

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \]
    10. lower-PI.f3299.1

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \]
  4. Applied rewrites99.1%

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

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

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

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

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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\color{blue}{\mathsf{PI}\left(\right)}, \frac{1}{2}, \frac{-314159265359}{50000000000} \cdot u2\right)\right) \]
    5. lower-*.f3299.1

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, \color{blue}{-6.28318530718 \cdot u2}\right)\right) \]
  7. Applied rewrites99.1%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -6.28318530718 \cdot u2\right)\right)} \]
  8. Step-by-step derivation
    1. Applied rewrites99.1%

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

    Alternative 2: 97.4% accurate, 0.6× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(6.28318530718 \cdot u2\right)\\ \mathbf{if}\;t\_0 \leq 0.9959999918937683:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot t\_0\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (cos (* 6.28318530718 u2))))
       (if (<= t_0 0.9959999918937683)
         (* (sqrt (fma (fma u1 u1 u1) u1 u1)) t_0)
         (*
          (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) {
    	float t_0 = cosf((6.28318530718f * u2));
    	float tmp;
    	if (t_0 <= 0.9959999918937683f) {
    		tmp = sqrtf(fmaf(fmaf(u1, u1, u1), u1, u1)) * t_0;
    	} else {
    		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	t_0 = cos(Float32(Float32(6.28318530718) * u2))
    	tmp = Float32(0.0)
    	if (t_0 <= Float32(0.9959999918937683))
    		tmp = Float32(sqrt(fma(fma(u1, u1, u1), u1, u1)) * t_0);
    	else
    		tmp = 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
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \cos \left(6.28318530718 \cdot u2\right)\\
    \mathbf{if}\;t\_0 \leq 0.9959999918937683:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(\mathsf{fma}\left(u1, u1, u1\right), u1, u1\right)} \cdot t\_0\\
    
    \mathbf{else}:\\
    \;\;\;\;\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}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)) < 0.995999992

      1. Initial program 96.6%

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\mathsf{fma}\left(u1 \cdot u1 + \color{blue}{u1}, u1, u1\right)} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        8. lower-fma.f3292.4

          \[\leadsto \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}, u1, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites92.4%

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

      if 0.995999992 < (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))

      1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

    Alternative 3: 90.7% accurate, 0.8× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.9941999912261963:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= (cos (* 6.28318530718 u2)) 0.9941999912261963)
       (*
        (sqrt u1)
        (fma
         (-
          (* (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) u2) u2)
          19.739208802181317)
         (* u2 u2)
         1.0))
       (* (sqrt (/ u1 (- 1.0 u1))) (fma (* u2 u2) -19.739208802181317 1.0))))
    float code(float cosTheta_i, float u1, float u2) {
    	float tmp;
    	if (cosf((6.28318530718f * u2)) <= 0.9941999912261963f) {
    		tmp = sqrtf(u1) * fmaf((((fmaf(-85.45681720672748f, (u2 * u2), 64.93939402268539f) * u2) * u2) - 19.739208802181317f), (u2 * u2), 1.0f);
    	} else {
    		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	tmp = Float32(0.0)
    	if (cos(Float32(Float32(6.28318530718) * u2)) <= Float32(0.9941999912261963))
    		tmp = Float32(sqrt(u1) * fma(Float32(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)));
    	else
    		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.9941999912261963:\\
    \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)) < 0.994199991

      1. Initial program 96.5%

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

        \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. lower-sqrt.f3281.6

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites81.6%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
        15. lower-*.f3259.9

          \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right) \]
      8. Applied rewrites59.9%

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

      if 0.994199991 < (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))

      1. Initial program 99.4%

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
        5. lower-*.f3299.0

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

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

    Alternative 4: 96.8% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.011500000022351742:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(\mathsf{fma}\left(u2, -6.28318530718, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (if (<= u2 0.011500000022351742)
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317) (* u2 u2) 1.0))
       (* (sqrt (fma u1 u1 u1)) (sin (fma u2 -6.28318530718 (* 0.5 (PI)))))))
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;u2 \leq 0.011500000022351742:\\
    \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(\mathsf{fma}\left(u2, -6.28318530718, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.0115

      1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

      if 0.0115 < u2

      1. Initial program 96.6%

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \]
        10. lower-PI.f3297.7

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \]
      4. Applied rewrites97.7%

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\color{blue}{\mathsf{PI}\left(\right)}, \frac{1}{2}, \frac{-314159265359}{50000000000} \cdot u2\right)\right) \]
        5. lower-*.f3297.4

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, \color{blue}{-6.28318530718 \cdot u2}\right)\right) \]
      7. Applied rewrites97.4%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -6.28318530718 \cdot u2\right)\right)} \]
      8. Step-by-step derivation
        1. Applied rewrites97.7%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(u2, \color{blue}{-6.28318530718}, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \]
        2. Taylor expanded in u1 around 0

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

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

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

            \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \sin \left(\mathsf{fma}\left(u2, \frac{-314159265359}{50000000000}, \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)\right) \]
          4. lower-fma.f3291.9

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \sin \left(\mathsf{fma}\left(u2, -6.28318530718, 0.5 \cdot \mathsf{PI}\left(\right)\right)\right) \]
        4. Applied rewrites91.9%

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

      Alternative 5: 97.2% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.027000000700354576:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\sqrt{u1} \cdot \mathsf{fma}\left(0.5, u1, 1\right)\right) \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.027000000700354576)
         (*
          (sqrt (/ u1 (- 1.0 u1)))
          (fma (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317) (* u2 u2) 1.0))
         (* (* (sqrt u1) (fma 0.5 u1 1.0)) (cos (* 6.28318530718 u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.027000000700354576f) {
      		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
      	} else {
      		tmp = (sqrtf(u1) * fmaf(0.5f, u1, 1.0f)) * cosf((6.28318530718f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.027000000700354576))
      		tmp = 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)));
      	else
      		tmp = Float32(Float32(sqrt(u1) * fma(Float32(0.5), u1, Float32(1.0))) * cos(Float32(Float32(6.28318530718) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.027000000700354576:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\left(\sqrt{u1} \cdot \mathsf{fma}\left(0.5, u1, 1\right)\right) \cdot \cos \left(6.28318530718 \cdot u2\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0270000007

        1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

        if 0.0270000007 < u2

        1. Initial program 96.2%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Applied rewrites95.9%

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

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

            \[\leadsto \left(\sqrt{u1} \cdot \color{blue}{\left(\frac{1}{2} \cdot u1 + 1\right)}\right) \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          2. lower-fma.f3290.2

            \[\leadsto \left(\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(0.5, u1, 1\right)}\right) \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        6. Applied rewrites90.2%

          \[\leadsto \left(\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(0.5, u1, 1\right)}\right) \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 6: 83.5% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.999970018863678:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= (cos (* 6.28318530718 u2)) 0.999970018863678)
         (* (sqrt u1) (fma (* u2 u2) -19.739208802181317 1.0))
         (sqrt (/ u1 (- 1.0 u1)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (cosf((6.28318530718f * u2)) <= 0.999970018863678f) {
      		tmp = sqrtf(u1) * fmaf((u2 * u2), -19.739208802181317f, 1.0f);
      	} else {
      		tmp = sqrtf((u1 / (1.0f - u1)));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (cos(Float32(Float32(6.28318530718) * u2)) <= Float32(0.999970018863678))
      		tmp = Float32(sqrt(u1) * fma(Float32(u2 * u2), Float32(-19.739208802181317), Float32(1.0)));
      	else
      		tmp = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;\cos \left(6.28318530718 \cdot u2\right) \leq 0.999970018863678:\\
      \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(u2 \cdot u2, -19.739208802181317, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2)) < 0.999970019

        1. Initial program 97.6%

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

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. Step-by-step derivation
          1. lower-sqrt.f3280.4

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        5. Applied rewrites80.4%

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

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

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

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

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

            \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
          5. lower-*.f3257.0

            \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -19.739208802181317, 1\right) \]
        8. Applied rewrites57.0%

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

        if 0.999970019 < (cos.f32 (*.f32 #s(literal 314159265359/50000000000 binary32) u2))

        1. Initial program 99.5%

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

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

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

            \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
          3. lower--.f3297.4

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

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

      Alternative 7: 96.8% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.017000000923871994:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.017000000923871994)
         (*
          (sqrt (/ u1 (- 1.0 u1)))
          (fma (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317) (* u2 u2) 1.0))
         (* (sqrt (* u1 (+ 1.0 u1))) (cos (* 6.28318530718 u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.017000000923871994f) {
      		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
      	} else {
      		tmp = sqrtf((u1 * (1.0f + u1))) * cosf((6.28318530718f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.017000000923871994))
      		tmp = 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)));
      	else
      		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + u1))) * cos(Float32(Float32(6.28318530718) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.017000000923871994:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{u1 \cdot \left(1 + u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0170000009

        1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

        if 0.0170000009 < u2

        1. Initial program 96.5%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Applied rewrites96.6%

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

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        5. Step-by-step derivation
          1. lower-+.f3290.9

            \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        6. Applied rewrites90.9%

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

      Alternative 8: 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
      3. Add Preprocessing

      Alternative 9: 96.6% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.011500000022351742:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.011500000022351742)
         (*
          (sqrt (/ u1 (- 1.0 u1)))
          (fma (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317) (* u2 u2) 1.0))
         (* (sqrt (fma u1 u1 u1)) (cos (* 6.28318530718 u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.011500000022351742f) {
      		tmp = sqrtf((u1 / (1.0f - u1))) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
      	} else {
      		tmp = sqrtf(fmaf(u1, u1, u1)) * cosf((6.28318530718f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.011500000022351742))
      		tmp = 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)));
      	else
      		tmp = Float32(sqrt(fma(u1, u1, u1)) * cos(Float32(Float32(6.28318530718) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.011500000022351742:\\
      \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0115

        1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

        if 0.0115 < u2

        1. Initial program 96.6%

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

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

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

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

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

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        5. Applied rewrites91.4%

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

      Alternative 10: 96.6% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.10999999940395355:\\ \;\;\;\;\sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -6.28318530718 \cdot u2\right)\right) \cdot \sqrt{u1}\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.10999999940395355)
         (*
          (sqrt (/ u1 (* (- (/ 1.0 u1) 1.0) u1)))
          (fma
           (-
            (* (* (fma -85.45681720672748 (* u2 u2) 64.93939402268539) u2) u2)
            19.739208802181317)
           (* u2 u2)
           1.0))
         (* (sin (fma (PI) 0.5 (* -6.28318530718 u2))) (sqrt u1))))
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.10999999940395355:\\
      \;\;\;\;\sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -6.28318530718 \cdot u2\right)\right) \cdot \sqrt{u1}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.109999999

        1. Initial program 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        if 0.109999999 < u2

        1. Initial program 94.7%

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

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

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

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(\frac{-314159265359}{50000000000}, u2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \]
          10. lower-PI.f3296.9

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(\mathsf{fma}\left(-6.28318530718, u2, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \]
        4. Applied rewrites96.9%

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

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

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

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

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

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

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

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

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

            \[\leadsto \sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), \frac{1}{2}, \color{blue}{\frac{-314159265359}{50000000000} \cdot u2}\right)\right) \cdot \sqrt{u1} \]
          9. lower-sqrt.f3277.9

            \[\leadsto \sin \left(\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -6.28318530718 \cdot u2\right)\right) \cdot \color{blue}{\sqrt{u1}} \]
        7. Applied rewrites77.9%

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

      Alternative 11: 96.6% accurate, 1.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.10999999940395355:\\ \;\;\;\;\sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.10999999940395355)
         (*
          (sqrt (/ u1 (* (- (/ 1.0 u1) 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) - 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(Float32(Float32(1.0) / u1) - Float32(1.0)) * u1))) * fma(Float32(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * 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}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 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 99.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        if 0.109999999 < u2

        1. Initial program 94.7%

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

          \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. Step-by-step derivation
          1. lower-sqrt.f3277.8

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        5. Applied rewrites77.8%

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

      Alternative 12: 93.4% accurate, 1.6× speedup?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
        15. lower-*.f3293.8

          \[\leadsto \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right) \]
      8. Applied rewrites93.8%

        \[\leadsto \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)} \]
      9. Step-by-step derivation
        1. Applied rewrites93.8%

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

        Alternative 13: 93.4% accurate, 1.7× speedup?

        \[\begin{array}{l} \\ \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right) \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (*
          (sqrt (/ u1 (* (- (/ 1.0 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) - 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(Float32(Float32(1.0) / u1) - Float32(1.0)) * u1))) * fma(Float32(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)))
        end
        
        \begin{array}{l}
        
        \\
        \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 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. Add Preprocessing
        3. Taylor expanded in u1 around inf

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
          15. lower-*.f3293.8

            \[\leadsto \sqrt{\frac{u1}{\left(\frac{1}{u1} - 1\right) \cdot u1}} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right) \]
        8. Applied rewrites93.8%

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

        Alternative 14: 93.0% accurate, 1.7× speedup?

        \[\begin{array}{l} \\ \left(\sqrt{u1} \cdot \sqrt{\frac{1}{1 - u1}}\right) \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right) \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (*
          (* (sqrt u1) (sqrt (/ 1.0 (- 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) * sqrtf((1.0f / (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(Float32(sqrt(u1) * sqrt(Float32(Float32(1.0) / Float32(Float32(1.0) - u1)))) * fma(Float32(Float32(Float32(fma(Float32(-85.45681720672748), Float32(u2 * u2), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)))
        end
        
        \begin{array}{l}
        
        \\
        \left(\sqrt{u1} \cdot \sqrt{\frac{1}{1 - u1}}\right) \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 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. Add Preprocessing
        3. Applied rewrites98.4%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \left(\sqrt{u1} \cdot \sqrt{\frac{1}{1 - u1}}\right) \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
          15. lower-*.f3293.4

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

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

        Alternative 15: 91.6% accurate, 2.5× speedup?

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
          9. lower-*.f3292.4

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right) \]
        5. Applied rewrites92.4%

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

        Alternative 16: 85.4% accurate, 2.9× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.0012499999720603228:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\ \end{array} \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (if (<= u2 0.0012499999720603228)
           (sqrt (/ u1 (- 1.0 u1)))
           (*
            (sqrt u1)
            (fma
             (- (* 64.93939402268539 (* u2 u2)) 19.739208802181317)
             (* u2 u2)
             1.0))))
        float code(float cosTheta_i, float u1, float u2) {
        	float tmp;
        	if (u2 <= 0.0012499999720603228f) {
        		tmp = sqrtf((u1 / (1.0f - u1)));
        	} else {
        		tmp = sqrtf(u1) * fmaf(((64.93939402268539f * (u2 * u2)) - 19.739208802181317f), (u2 * u2), 1.0f);
        	}
        	return tmp;
        }
        
        function code(cosTheta_i, u1, u2)
        	tmp = Float32(0.0)
        	if (u2 <= Float32(0.0012499999720603228))
        		tmp = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)));
        	else
        		tmp = Float32(sqrt(u1) * fma(Float32(Float32(Float32(64.93939402268539) * Float32(u2 * u2)) - Float32(19.739208802181317)), Float32(u2 * u2), Float32(1.0)));
        	end
        	return tmp
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;u2 \leq 0.0012499999720603228:\\
        \;\;\;\;\sqrt{\frac{u1}{1 - u1}}\\
        
        \mathbf{else}:\\
        \;\;\;\;\sqrt{u1} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, u2 \cdot u2, 1\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if u2 < 0.00124999997

          1. Initial program 99.5%

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

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

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

              \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
            3. lower--.f3297.4

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

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

          if 0.00124999997 < u2

          1. Initial program 97.6%

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

            \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          4. Step-by-step derivation
            1. lower-sqrt.f3280.4

              \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          5. Applied rewrites80.4%

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

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

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

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

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

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

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

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

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

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} \cdot \left(u2 \cdot u2\right) - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right) \]
            9. lower-*.f3264.4

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(64.93939402268539 \cdot \left(u2 \cdot u2\right) - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right) \]
          8. Applied rewrites64.4%

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

        Alternative 17: 88.5% accurate, 3.3× speedup?

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

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

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

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

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

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, \frac{-98696044010906577398881}{5000000000000000000000}, 1\right) \]
          5. lower-*.f3289.7

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(\color{blue}{u2 \cdot u2}, -19.739208802181317, 1\right) \]
        5. Applied rewrites89.7%

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

        Alternative 18: 80.3% accurate, 5.4× speedup?

        \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \end{array} \]
        (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (/ u1 (- 1.0 u1))))
        float code(float cosTheta_i, float u1, float u2) {
        	return sqrtf((u1 / (1.0f - u1)));
        }
        
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(4) function code(costheta_i, u1, u2)
        use fmin_fmax_functions
            real(4), intent (in) :: costheta_i
            real(4), intent (in) :: u1
            real(4), intent (in) :: u2
            code = sqrt((u1 / (1.0e0 - u1)))
        end function
        
        function code(cosTheta_i, u1, u2)
        	return sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
        end
        
        function tmp = code(cosTheta_i, u1, u2)
        	tmp = sqrt((u1 / (single(1.0) - u1)));
        end
        
        \begin{array}{l}
        
        \\
        \sqrt{\frac{u1}{1 - u1}}
        \end{array}
        
        Derivation
        1. Initial program 99.0%

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

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

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

            \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
          3. lower--.f3281.8

            \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
        5. Applied rewrites81.8%

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

        Alternative 19: 75.0% accurate, 5.9× speedup?

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

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

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

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

            \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
          3. lower--.f3281.8

            \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
        5. Applied rewrites81.8%

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

          \[\leadsto \sqrt{u1 \cdot \left(1 + u1 \cdot \left(1 + u1\right)\right)} \]
        7. Step-by-step derivation
          1. Applied rewrites75.4%

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

          Alternative 20: 72.3% accurate, 6.1× speedup?

          \[\begin{array}{l} \\ \sqrt{u1} \cdot \mathsf{fma}\left(0.5, u1, 1\right) \end{array} \]
          (FPCore (cosTheta_i u1 u2) :precision binary32 (* (sqrt u1) (fma 0.5 u1 1.0)))
          float code(float cosTheta_i, float u1, float u2) {
          	return sqrtf(u1) * fmaf(0.5f, u1, 1.0f);
          }
          
          function code(cosTheta_i, u1, u2)
          	return Float32(sqrt(u1) * fma(Float32(0.5), u1, Float32(1.0)))
          end
          
          \begin{array}{l}
          
          \\
          \sqrt{u1} \cdot \mathsf{fma}\left(0.5, u1, 1\right)
          \end{array}
          
          Derivation
          1. Initial program 99.0%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

              \[\leadsto \sqrt{u1} \cdot \frac{\cos \left(\color{blue}{\frac{-314159265359}{50000000000}} \cdot u2\right)}{\sqrt{1 - u1}} \]
            17. lower-sqrt.f3298.4

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

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

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

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

              \[\leadsto \sqrt{u1} \cdot \sqrt{\color{blue}{\frac{1}{1 - u1}}} \]
            3. lower--.f3281.5

              \[\leadsto \sqrt{u1} \cdot \sqrt{\frac{1}{\color{blue}{1 - u1}}} \]
          7. Applied rewrites81.5%

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

            \[\leadsto \sqrt{u1} \cdot \left(1 + \color{blue}{\frac{1}{2} \cdot u1}\right) \]
          9. Step-by-step derivation
            1. Applied rewrites73.2%

              \[\leadsto \sqrt{u1} \cdot \mathsf{fma}\left(0.5, \color{blue}{u1}, 1\right) \]
            2. Add Preprocessing

            Alternative 21: 72.2% accurate, 7.9× speedup?

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

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

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

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

                \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
              3. lower--.f3281.8

                \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
            5. Applied rewrites81.8%

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

              \[\leadsto \sqrt{u1 \cdot \left(1 + u1\right)} \]
            7. Step-by-step derivation
              1. Applied rewrites73.1%

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

              Alternative 22: 63.6% accurate, 12.3× speedup?

              \[\begin{array}{l} \\ \sqrt{u1} \end{array} \]
              (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt u1))
              float code(float cosTheta_i, float u1, float u2) {
              	return sqrtf(u1);
              }
              
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(4) function code(costheta_i, u1, u2)
              use fmin_fmax_functions
                  real(4), intent (in) :: costheta_i
                  real(4), intent (in) :: u1
                  real(4), intent (in) :: u2
                  code = sqrt(u1)
              end function
              
              function code(cosTheta_i, u1, u2)
              	return sqrt(u1)
              end
              
              function tmp = code(cosTheta_i, u1, u2)
              	tmp = sqrt(u1);
              end
              
              \begin{array}{l}
              
              \\
              \sqrt{u1}
              \end{array}
              
              Derivation
              1. Initial program 99.0%

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

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

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

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
                3. lower--.f3281.8

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
              5. Applied rewrites81.8%

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

                \[\leadsto \sqrt{u1} \]
              7. Step-by-step derivation
                1. Applied rewrites64.7%

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

                Reproduce

                ?
                herbie shell --seed 2024350 
                (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))))