UniformSampleCone, x

Percentage Accurate: 57.5% → 99.0%
Time: 8.4s
Alternatives: 13
Speedup: 5.8×

Specification

?
\[\left(\left(2.328306437 \cdot 10^{-10} \leq ux \land ux \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq uy \land uy \leq 1\right)\right) \land \left(0 \leq maxCos \land maxCos \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\end{array}
\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 13 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: 57.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\end{array}
\end{array}

Alternative 1: 99.0% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, ux, \left(-2 \cdot maxCos\right) \cdot ux\right)} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (cos (* (* uy 2.0) (PI)))
  (sqrt
   (fma (- 2.0 (* (pow (- maxCos 1.0) 2.0) ux)) ux (* (* -2.0 maxCos) ux)))))
\begin{array}{l}

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, ux, \left(-2 \cdot maxCos\right) \cdot ux\right)}
\end{array}
Derivation
  1. Initial program 54.0%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. fp-cancel-sub-sign-invN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
    4. metadata-evalN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
    5. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
    6. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
    7. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    8. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    9. fp-cancel-sub-signN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    12. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    13. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    14. lower--.f3299.1

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
  5. Applied rewrites99.1%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
  6. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot \color{blue}{ux}} \]
    2. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right)}} \]
    3. lift-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(-2 \cdot maxCos + \color{blue}{\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right)}\right)} \]
    4. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) + \color{blue}{-2 \cdot maxCos}\right)} \]
    5. distribute-rgt-inN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux + \color{blue}{\left(-2 \cdot maxCos\right) \cdot ux}} \]
    6. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, \color{blue}{ux}, \left(-2 \cdot maxCos\right) \cdot ux\right)} \]
    7. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, ux, \left(-2 \cdot maxCos\right) \cdot ux\right)} \]
    8. lower-*.f3299.1

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, ux, \left(-2 \cdot maxCos\right) \cdot ux\right)} \]
  7. Applied rewrites99.1%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - {\left(maxCos - 1\right)}^{2} \cdot ux, \color{blue}{ux}, \left(-2 \cdot maxCos\right) \cdot ux\right)} \]
  8. Add Preprocessing

Alternative 2: 99.0% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (cos (* (* uy 2.0) (PI)))
  (sqrt (* (fma -2.0 maxCos (- 2.0 (* (pow (- maxCos 1.0) 2.0) ux))) ux))))
\begin{array}{l}

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 54.0%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    2. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
    3. fp-cancel-sub-sign-invN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
    4. metadata-evalN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
    5. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
    6. lower-fma.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
    7. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    8. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    9. fp-cancel-sub-signN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    10. lower--.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
    11. *-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    12. lower-*.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    13. lower-pow.f32N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
    14. lower--.f3299.1

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
  5. Applied rewrites99.1%

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
  6. Add Preprocessing

Alternative 3: 83.9% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.004000000189989805:\\ \;\;\;\;\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\left(\left(\mathsf{fma}\left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right), ux, \left(-maxCos\right) - -1\right) - -1\right) - maxCos\right) \cdot ux}\\ \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (if (<=
        (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))
        0.004000000189989805)
     (*
      (fma (* -2.0 (* uy uy)) (* (PI) (PI)) 1.0)
      (sqrt (* (fma -2.0 maxCos 2.0) ux)))
     (*
      1.0
      (sqrt
       (*
        (-
         (-
          (fma (* (- 1.0 maxCos) (- maxCos 1.0)) ux (- (- maxCos) -1.0))
          -1.0)
         maxCos)
        ux))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.004000000189989805:\\
\;\;\;\;\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\

\mathbf{else}:\\
\;\;\;\;1 \cdot \sqrt{\left(\left(\mathsf{fma}\left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right), ux, \left(-maxCos\right) - -1\right) - -1\right) - maxCos\right) \cdot ux}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))))) < 0.00400000019

    1. Initial program 29.2%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Add Preprocessing
    3. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
    4. Step-by-step derivation
      1. metadata-evalN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
      2. fp-cancel-sign-sub-invN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
      3. *-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      4. lower-*.f32N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
      5. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + 2\right) \cdot ux} \]
      6. lower-fma.f3294.6

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
    5. Applied rewrites94.6%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]
    6. Taylor expanded in uy around 0

      \[\leadsto \color{blue}{\left(1 + -2 \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \left(-2 \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + \color{blue}{1}\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      2. associate-*r*N/A

        \[\leadsto \left(\left(-2 \cdot {uy}^{2}\right) \cdot {\mathsf{PI}\left(\right)}^{2} + 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      3. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot {uy}^{2}, \color{blue}{{\mathsf{PI}\left(\right)}^{2}}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      4. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot {uy}^{2}, {\color{blue}{\mathsf{PI}\left(\right)}}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      5. unpow2N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      6. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      7. unpow2N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      8. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      9. lower-PI.f32N/A

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      10. lower-PI.f3280.6

        \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
    8. Applied rewrites80.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]

    if 0.00400000019 < (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))))))

    1. Initial program 82.2%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Add Preprocessing
    3. Taylor expanded in uy around 0

      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    4. Step-by-step derivation
      1. Applied rewrites72.4%

        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      2. Taylor expanded in maxCos around inf

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

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

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
        3. associate--l+N/A

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
        4. div-subN/A

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

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

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
        7. lower--.f3271.3

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
      4. Applied rewrites71.3%

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

          \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
        2. lift-*.f32N/A

          \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
        3. fp-cancel-sub-sign-invN/A

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

          \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
        5. lower-fma.f32N/A

          \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
        6. lower-neg.f3271.3

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        7. lift-+.f32N/A

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        8. +-commutativeN/A

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        9. lift-*.f32N/A

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        10. lower-fma.f3271.3

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        11. lift-+.f32N/A

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
        12. +-commutativeN/A

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
        13. lower-+.f3271.3

          \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
      6. Applied rewrites71.3%

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

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

          \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + \left(-1 \cdot \left(maxCos - 1\right) + ux \cdot \left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right)\right)\right)\right) - maxCos\right)} \]
        2. +-commutativeN/A

          \[\leadsto 1 \cdot \sqrt{ux \cdot \left(\left(1 + \left(-1 \cdot \left(maxCos - 1\right) + ux \cdot \left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right)\right)\right)\right) - maxCos\right)} \]
        3. fp-cancel-sub-sign-invN/A

          \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + \left(-1 \cdot \left(maxCos - 1\right) + ux \cdot \left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right)\right)\right)\right) - maxCos\right)} \]
        4. *-commutativeN/A

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

          \[\leadsto 1 \cdot \sqrt{\left(\left(1 + \left(-1 \cdot \left(maxCos - 1\right) + ux \cdot \left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right)\right)\right)\right) - maxCos\right) \cdot \color{blue}{ux}} \]
      9. Applied rewrites84.7%

        \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\left(\mathsf{fma}\left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right), ux, -\left(maxCos - 1\right)\right) + 1\right) - maxCos\right) \cdot ux}} \]
    5. Recombined 2 regimes into one program.
    6. Final simplification82.5%

      \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \leq 0.004000000189989805:\\ \;\;\;\;\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\left(\left(\mathsf{fma}\left(\left(1 - maxCos\right) \cdot \left(maxCos - 1\right), ux, \left(-maxCos\right) - -1\right) - -1\right) - maxCos\right) \cdot ux}\\ \end{array} \]
    7. Add Preprocessing

    Alternative 4: 80.3% accurate, 0.7× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.02199999988079071:\\ \;\;\;\;\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}\\ \end{array} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
       (if (<=
            (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))
            0.02199999988079071)
         (*
          (fma (* -2.0 (* uy uy)) (* (PI) (PI)) 1.0)
          (sqrt (* (fma -2.0 maxCos 2.0) ux)))
         (sqrt (fma (- ux (fma maxCos ux 1.0)) (fma maxCos ux (- 1.0 ux)) 1.0)))))
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
    \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.02199999988079071:\\
    \;\;\;\;\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))))) < 0.0219999999

      1. Initial program 37.3%

        \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      2. Add Preprocessing
      3. Taylor expanded in ux around 0

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
      4. Step-by-step derivation
        1. metadata-evalN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
        2. fp-cancel-sign-sub-invN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
        3. *-commutativeN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
        4. lower-*.f32N/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
        5. +-commutativeN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + 2\right) \cdot ux} \]
        6. lower-fma.f3290.9

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      5. Applied rewrites90.9%

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]
      6. Taylor expanded in uy around 0

        \[\leadsto \color{blue}{\left(1 + -2 \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \left(-2 \cdot \left({uy}^{2} \cdot {\mathsf{PI}\left(\right)}^{2}\right) + \color{blue}{1}\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        2. associate-*r*N/A

          \[\leadsto \left(\left(-2 \cdot {uy}^{2}\right) \cdot {\mathsf{PI}\left(\right)}^{2} + 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        3. lower-fma.f32N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot {uy}^{2}, \color{blue}{{\mathsf{PI}\left(\right)}^{2}}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        4. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot {uy}^{2}, {\color{blue}{\mathsf{PI}\left(\right)}}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        5. unpow2N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        6. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), {\mathsf{PI}\left(\right)}^{2}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        7. unpow2N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        8. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}, 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        9. lower-PI.f32N/A

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
        10. lower-PI.f3278.6

          \[\leadsto \mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      8. Applied rewrites78.6%

        \[\leadsto \color{blue}{\mathsf{fma}\left(-2 \cdot \left(uy \cdot uy\right), \mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 1\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]

      if 0.0219999999 < (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))))))

      1. Initial program 89.0%

        \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      2. Add Preprocessing
      3. Taylor expanded in uy around 0

        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      4. Step-by-step derivation
        1. Applied rewrites77.6%

          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Taylor expanded in maxCos around inf

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

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

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
          3. associate--l+N/A

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
          4. div-subN/A

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

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

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
          7. lower--.f3277.2

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
        4. Applied rewrites77.2%

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

            \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
          2. lift-*.f32N/A

            \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
          3. fp-cancel-sub-sign-invN/A

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

            \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
          5. lower-fma.f32N/A

            \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
          6. lower-neg.f3277.2

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          7. lift-+.f32N/A

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          8. +-commutativeN/A

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          9. lift-*.f32N/A

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          10. lower-fma.f3277.2

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          11. lift-+.f32N/A

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
          12. +-commutativeN/A

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
          13. lower-+.f3277.2

            \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
        6. Applied rewrites77.2%

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

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

            \[\leadsto \sqrt{1 + \color{blue}{\left(ux - \left(1 + maxCos \cdot ux\right)\right)} \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
          2. +-commutativeN/A

            \[\leadsto \sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
          3. fp-cancel-sub-sign-invN/A

            \[\leadsto \sqrt{1 + \color{blue}{\left(ux - \left(1 + maxCos \cdot ux\right)\right)} \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
          4. lower-sqrt.f32N/A

            \[\leadsto \sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
          5. +-commutativeN/A

            \[\leadsto \sqrt{\left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right) + 1} \]
        9. Applied rewrites78.2%

          \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]
      5. Recombined 2 regimes into one program.
      6. Add Preprocessing

      Alternative 5: 74.2% accurate, 0.8× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.025200000032782555:\\ \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - ux, 1\right)}\\ \end{array} \end{array} \]
      (FPCore (ux uy maxCos)
       :precision binary32
       (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
         (if (<=
              (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))
              0.025200000032782555)
           (* 1.0 (sqrt (* (- (fma -1.0 (- maxCos 1.0) 1.0) maxCos) ux)))
           (* 1.0 (sqrt (fma (- ux 1.0) (- 1.0 ux) 1.0))))))
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
      \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.025200000032782555:\\
      \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux}\\
      
      \mathbf{else}:\\
      \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - ux, 1\right)}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))))) < 0.0252

        1. Initial program 37.7%

          \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Add Preprocessing
        3. Taylor expanded in uy around 0

          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        4. Step-by-step derivation
          1. Applied rewrites30.3%

            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          2. Taylor expanded in maxCos around inf

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

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

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
            3. associate--l+N/A

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
            4. div-subN/A

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

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

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
            7. lower--.f3230.9

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
          4. Applied rewrites30.9%

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

              \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
            2. lift-*.f32N/A

              \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
            3. fp-cancel-sub-sign-invN/A

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

              \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
            5. lower-fma.f32N/A

              \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
            6. lower-neg.f3230.9

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            7. lift-+.f32N/A

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            8. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            9. lift-*.f32N/A

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            10. lower-fma.f3230.9

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            11. lift-+.f32N/A

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
            12. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
            13. lower-+.f3230.9

              \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
          6. Applied rewrites30.9%

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

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

              \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
            2. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{ux \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
            3. fp-cancel-sub-sign-invN/A

              \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
            4. *-commutativeN/A

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

              \[\leadsto 1 \cdot \sqrt{\left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right) \cdot \color{blue}{ux}} \]
            6. lower--.f32N/A

              \[\leadsto 1 \cdot \sqrt{\left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right) \cdot ux} \]
            7. +-commutativeN/A

              \[\leadsto 1 \cdot \sqrt{\left(\left(-1 \cdot \left(maxCos - 1\right) + 1\right) - maxCos\right) \cdot ux} \]
            8. lower-fma.f32N/A

              \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux} \]
            9. lower--.f3269.6

              \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux} \]
          9. Applied rewrites69.6%

            \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux}} \]

          if 0.0252 < (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))))))

          1. Initial program 89.4%

            \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in uy around 0

            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          4. Step-by-step derivation
            1. Applied rewrites77.7%

              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            2. Taylor expanded in maxCos around inf

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

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

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
              3. associate--l+N/A

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
              4. div-subN/A

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

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

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
              7. lower--.f3277.3

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
            4. Applied rewrites77.3%

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

                \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
              2. lift-*.f32N/A

                \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
              3. fp-cancel-sub-sign-invN/A

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

                \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
              5. lower-fma.f32N/A

                \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
              6. lower-neg.f3277.4

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              7. lift-+.f32N/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              8. +-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              9. lift-*.f32N/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              10. lower-fma.f3277.4

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              11. lift-+.f32N/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
              12. +-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
              13. lower-+.f3277.4

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
            6. Applied rewrites77.4%

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

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

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

                \[\leadsto 1 \cdot \sqrt{1 + \left(1 - ux\right) \cdot \left(ux - 1\right)} \]
              3. fp-cancel-sub-sign-invN/A

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

                \[\leadsto 1 \cdot \sqrt{\left(1 - ux\right) \cdot \left(ux - 1\right) + \color{blue}{1}} \]
              5. *-commutativeN/A

                \[\leadsto 1 \cdot \sqrt{\left(ux - 1\right) \cdot \left(1 - ux\right) + 1} \]
              6. lower-fma.f32N/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, \color{blue}{1 - ux}, 1\right)} \]
              7. lower--.f32N/A

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, \color{blue}{1} - ux, 1\right)} \]
              8. lower--.f3275.2

                \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - \color{blue}{ux}, 1\right)} \]
            9. Applied rewrites75.2%

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

          Alternative 6: 74.2% accurate, 0.8× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.025200000032782555:\\ \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - ux, 1\right)}\\ \end{array} \end{array} \]
          (FPCore (ux uy maxCos)
           :precision binary32
           (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
             (if (<=
                  (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))
                  0.025200000032782555)
               (* 1.0 (sqrt (* (fma -2.0 maxCos 2.0) ux)))
               (* 1.0 (sqrt (fma (- ux 1.0) (- 1.0 ux) 1.0))))))
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
          \mathbf{if}\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \leq 0.025200000032782555:\\
          \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\
          
          \mathbf{else}:\\
          \;\;\;\;1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - ux, 1\right)}\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))))) < 0.0252

            1. Initial program 37.7%

              \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            2. Add Preprocessing
            3. Taylor expanded in uy around 0

              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            4. Step-by-step derivation
              1. Applied rewrites30.3%

                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Taylor expanded in ux around 0

                \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
              3. Step-by-step derivation
                1. metadata-evalN/A

                  \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
                2. fp-cancel-sign-sub-invN/A

                  \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
                3. *-commutativeN/A

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

                  \[\leadsto 1 \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                5. +-commutativeN/A

                  \[\leadsto 1 \cdot \sqrt{\left(-2 \cdot maxCos + 2\right) \cdot ux} \]
                6. lower-fma.f3269.6

                  \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
              4. Applied rewrites69.6%

                \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]

              if 0.0252 < (*.f32 (cos.f32 (*.f32 (*.f32 uy #s(literal 2 binary32)) (PI.f32))) (sqrt.f32 (-.f32 #s(literal 1 binary32) (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))))))

              1. Initial program 89.4%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Add Preprocessing
              3. Taylor expanded in uy around 0

                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              4. Step-by-step derivation
                1. Applied rewrites77.7%

                  \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Taylor expanded in maxCos around inf

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

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

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
                  3. associate--l+N/A

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
                  4. div-subN/A

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

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

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                  7. lower--.f3277.3

                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                4. Applied rewrites77.3%

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

                    \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                  2. lift-*.f32N/A

                    \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                  3. fp-cancel-sub-sign-invN/A

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

                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
                  5. lower-fma.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
                  6. lower-neg.f3277.4

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  7. lift-+.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  8. +-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  9. lift-*.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  10. lower-fma.f3277.4

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  11. lift-+.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                  12. +-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                  13. lower-+.f3277.4

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                6. Applied rewrites77.4%

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

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

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

                    \[\leadsto 1 \cdot \sqrt{1 + \left(1 - ux\right) \cdot \left(ux - 1\right)} \]
                  3. fp-cancel-sub-sign-invN/A

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

                    \[\leadsto 1 \cdot \sqrt{\left(1 - ux\right) \cdot \left(ux - 1\right) + \color{blue}{1}} \]
                  5. *-commutativeN/A

                    \[\leadsto 1 \cdot \sqrt{\left(ux - 1\right) \cdot \left(1 - ux\right) + 1} \]
                  6. lower-fma.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, \color{blue}{1 - ux}, 1\right)} \]
                  7. lower--.f32N/A

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, \color{blue}{1} - ux, 1\right)} \]
                  8. lower--.f3275.2

                    \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(ux - 1, 1 - \color{blue}{ux}, 1\right)} \]
                9. Applied rewrites75.2%

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

              Alternative 7: 99.0% accurate, 1.0× speedup?

              \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-maxCos, \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), ux, \left(maxCos \cdot ux\right) \cdot ux\right), \left(2 - ux\right) \cdot ux\right)} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (*
                (cos (* (* uy 2.0) (PI)))
                (sqrt
                 (fma
                  (- maxCos)
                  (fma (fma -2.0 ux 2.0) ux (* (* maxCos ux) ux))
                  (* (- 2.0 ux) ux)))))
              \begin{array}{l}
              
              \\
              \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-maxCos, \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), ux, \left(maxCos \cdot ux\right) \cdot ux\right), \left(2 - ux\right) \cdot ux\right)}
              \end{array}
              
              Derivation
              1. Initial program 54.0%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Add Preprocessing
              3. Taylor expanded in ux around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                2. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                3. fp-cancel-sub-sign-invN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
                4. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
                5. +-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
                6. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
                7. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                8. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                9. fp-cancel-sub-signN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                10. lower--.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                11. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                12. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                13. lower-pow.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                14. lower--.f3299.1

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              5. Applied rewrites99.1%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
              6. Taylor expanded in maxCos around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{maxCos \cdot \left(-1 \cdot \left(maxCos \cdot {ux}^{2}\right) + -1 \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right) + \color{blue}{ux \cdot \left(2 - ux\right)}} \]
              7. Step-by-step derivation
                1. distribute-lft-outN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{maxCos \cdot \left(-1 \cdot \left(maxCos \cdot {ux}^{2} + ux \cdot \left(2 + -2 \cdot ux\right)\right)\right) + ux \cdot \left(2 - ux\right)} \]
                2. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(maxCos \cdot -1\right) \cdot \left(maxCos \cdot {ux}^{2} + ux \cdot \left(2 + -2 \cdot ux\right)\right) + ux \cdot \left(\color{blue}{2} - ux\right)} \]
                3. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-1 \cdot maxCos\right) \cdot \left(maxCos \cdot {ux}^{2} + ux \cdot \left(2 + -2 \cdot ux\right)\right) + ux \cdot \left(2 - ux\right)} \]
                4. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{neg}\left(maxCos\right)\right) \cdot \left(maxCos \cdot {ux}^{2} + ux \cdot \left(2 + -2 \cdot ux\right)\right) + ux \cdot \left(2 - ux\right)} \]
                5. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{neg}\left(maxCos\right), maxCos \cdot {ux}^{2} + \color{blue}{ux \cdot \left(2 + -2 \cdot ux\right)}, ux \cdot \left(2 - ux\right)\right)} \]
              8. Applied rewrites99.1%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-maxCos, \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), ux, \left(maxCos \cdot ux\right) \cdot ux\right)}, \left(2 - ux\right) \cdot ux\right)} \]
              9. Add Preprocessing

              Alternative 8: 98.4% accurate, 1.0× speedup?

              \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, \left(\left(\left(1 - ux\right) \cdot ux\right) \cdot maxCos\right) \cdot -2\right)} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (*
                (cos (* (* uy 2.0) (PI)))
                (sqrt (fma (- 2.0 ux) ux (* (* (* (- 1.0 ux) ux) maxCos) -2.0)))))
              \begin{array}{l}
              
              \\
              \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, \left(\left(\left(1 - ux\right) \cdot ux\right) \cdot maxCos\right) \cdot -2\right)}
              \end{array}
              
              Derivation
              1. Initial program 54.0%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Add Preprocessing
              3. Taylor expanded in ux around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                2. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                3. fp-cancel-sub-sign-invN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
                4. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
                5. +-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
                6. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
                7. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                8. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                9. fp-cancel-sub-signN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                10. lower--.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                11. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                12. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                13. lower-pow.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                14. lower--.f3299.1

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              5. Applied rewrites99.1%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
              6. Taylor expanded in maxCos around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{-1 \cdot \left(maxCos \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right) + \color{blue}{ux \cdot \left(2 - ux\right)}} \]
              7. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \left(2 - ux\right) + -1 \cdot \color{blue}{\left(maxCos \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)}} \]
                2. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux + -1 \cdot \left(\color{blue}{maxCos} \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)} \]
                3. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, -1 \cdot \left(maxCos \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)\right)} \]
                4. lower--.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, -1 \cdot \left(maxCos \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)\right)} \]
                5. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, \mathsf{neg}\left(maxCos \cdot \left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)\right)} \]
                6. distribute-rgt-neg-inN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(ux \cdot \left(2 + -2 \cdot ux\right)\right)\right)\right)} \]
                7. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(\left(2 + -2 \cdot ux\right) \cdot ux\right)\right)\right)} \]
                8. fp-cancel-sign-sub-invN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(\left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot ux\right) \cdot ux\right)\right)\right)} \]
                9. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(\left(2 - 2 \cdot ux\right) \cdot ux\right)\right)\right)} \]
                10. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(\left(2 \cdot 1 - 2 \cdot ux\right) \cdot ux\right)\right)\right)} \]
                11. distribute-lft-out--N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(\left(2 \cdot \left(1 - ux\right)\right) \cdot ux\right)\right)\right)} \]
                12. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(2 \cdot \left(\left(1 - ux\right) \cdot ux\right)\right)\right)\right)} \]
                13. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\mathsf{neg}\left(2 \cdot \left(ux \cdot \left(1 - ux\right)\right)\right)\right)\right)} \]
                14. distribute-lft-neg-outN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\left(\mathsf{neg}\left(2\right)\right) \cdot \left(ux \cdot \left(1 - ux\right)\right)\right)\right)} \]
                15. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(-2 \cdot \left(ux \cdot \left(1 - ux\right)\right)\right)\right)} \]
                16. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, ux, maxCos \cdot \left(\left(ux \cdot \left(1 - ux\right)\right) \cdot -2\right)\right)} \]
              8. Applied rewrites98.3%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(2 - ux, \color{blue}{ux}, \left(\left(\left(1 - ux\right) \cdot ux\right) \cdot maxCos\right) \cdot -2\right)} \]
              9. Add Preprocessing

              Alternative 9: 93.1% accurate, 1.1× speedup?

              \[\begin{array}{l} \\ \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (* (sin (fma (- (PI)) (* 2.0 uy) (/ (PI) 2.0))) (sqrt (* (- 2.0 ux) ux))))
              \begin{array}{l}
              
              \\
              \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}
              \end{array}
              
              Derivation
              1. Initial program 54.0%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Add Preprocessing
              3. Taylor expanded in ux around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                2. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                3. fp-cancel-sub-sign-invN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
                4. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
                5. +-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
                6. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
                7. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                8. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                9. fp-cancel-sub-signN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                10. lower--.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                11. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                12. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                13. lower-pow.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                14. lower--.f3299.1

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              5. Applied rewrites99.1%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
              6. Step-by-step derivation
                1. lift-cos.f32N/A

                  \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                2. cos-neg-revN/A

                  \[\leadsto \color{blue}{\cos \left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                3. sin-+PI/2-revN/A

                  \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                4. lower-sin.f32N/A

                  \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                5. lift-*.f32N/A

                  \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                6. *-commutativeN/A

                  \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\mathsf{PI}\left(\right) \cdot \left(uy \cdot 2\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                7. distribute-lft-neg-inN/A

                  \[\leadsto \sin \left(\color{blue}{\left(\mathsf{neg}\left(\mathsf{PI}\left(\right)\right)\right) \cdot \left(uy \cdot 2\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                8. lower-fma.f32N/A

                  \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{neg}\left(\mathsf{PI}\left(\right)\right), uy \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                9. lower-neg.f32N/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{-\mathsf{PI}\left(\right)}, uy \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                10. lift-*.f32N/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), \color{blue}{uy \cdot 2}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                11. *-commutativeN/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), \color{blue}{2 \cdot uy}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                12. lower-*.f32N/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), \color{blue}{2 \cdot uy}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                13. lift-PI.f32N/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                14. lower-/.f3299.1

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              7. Applied rewrites99.1%

                \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              8. Taylor expanded in maxCos around 0

                \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{ux \cdot \color{blue}{\left(2 - ux\right)}} \]
              9. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                2. lower-*.f32N/A

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                3. lower--.f3293.5

                  \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
              10. Applied rewrites93.5%

                \[\leadsto \sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), 2 \cdot uy, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot \color{blue}{ux}} \]
              11. Add Preprocessing

              Alternative 10: 92.9% accurate, 1.2× speedup?

              \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (* (cos (* (* uy 2.0) (PI))) (sqrt (* (- 2.0 ux) ux))))
              \begin{array}{l}
              
              \\
              \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}
              \end{array}
              
              Derivation
              1. Initial program 54.0%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              2. Add Preprocessing
              3. Taylor expanded in ux around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
              4. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                2. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                3. fp-cancel-sub-sign-invN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + \left(\mathsf{neg}\left(2\right)\right) \cdot maxCos\right) \cdot ux} \]
                4. metadata-evalN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) + -2 \cdot maxCos\right) \cdot ux} \]
                5. +-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + \left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right)\right) \cdot ux} \]
                6. lower-fma.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) \cdot ux} \]
                7. associate-*r*N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                8. mul-1-negN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 + \left(\mathsf{neg}\left(ux\right)\right) \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                9. fp-cancel-sub-signN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                10. lower--.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - ux \cdot {\left(maxCos - 1\right)}^{2}\right) \cdot ux} \]
                11. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                12. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                13. lower-pow.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
                14. lower--.f3299.1

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux} \]
              5. Applied rewrites99.1%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2 - {\left(maxCos - 1\right)}^{2} \cdot ux\right) \cdot ux}} \]
              6. Taylor expanded in maxCos around 0

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{ux \cdot \color{blue}{\left(2 - ux\right)}} \]
              7. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                2. lower-*.f32N/A

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                3. lower--.f3293.4

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
              8. Applied rewrites93.4%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot \color{blue}{ux}} \]
              9. Add Preprocessing

              Alternative 11: 75.5% accurate, 2.3× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;t\_0 \cdot t\_0 \leq 0.9996600151062012:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux}\\ \end{array} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
                 (if (<= (* t_0 t_0) 0.9996600151062012)
                   (sqrt (fma (- ux (fma maxCos ux 1.0)) (fma maxCos ux (- 1.0 ux)) 1.0))
                   (* 1.0 (sqrt (* (- (fma -1.0 (- maxCos 1.0) 1.0) maxCos) ux))))))
              float code(float ux, float uy, float maxCos) {
              	float t_0 = (1.0f - ux) + (ux * maxCos);
              	float tmp;
              	if ((t_0 * t_0) <= 0.9996600151062012f) {
              		tmp = sqrtf(fmaf((ux - fmaf(maxCos, ux, 1.0f)), fmaf(maxCos, ux, (1.0f - ux)), 1.0f));
              	} else {
              		tmp = 1.0f * sqrtf(((fmaf(-1.0f, (maxCos - 1.0f), 1.0f) - maxCos) * ux));
              	}
              	return tmp;
              }
              
              function code(ux, uy, maxCos)
              	t_0 = Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))
              	tmp = Float32(0.0)
              	if (Float32(t_0 * t_0) <= Float32(0.9996600151062012))
              		tmp = sqrt(fma(Float32(ux - fma(maxCos, ux, Float32(1.0))), fma(maxCos, ux, Float32(Float32(1.0) - ux)), Float32(1.0)));
              	else
              		tmp = Float32(Float32(1.0) * sqrt(Float32(Float32(fma(Float32(-1.0), Float32(maxCos - Float32(1.0)), Float32(1.0)) - maxCos) * ux)));
              	end
              	return tmp
              end
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
              \mathbf{if}\;t\_0 \cdot t\_0 \leq 0.9996600151062012:\\
              \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}\\
              
              \mathbf{else}:\\
              \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux}\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))) < 0.999660015

                1. Initial program 87.8%

                  \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Add Preprocessing
                3. Taylor expanded in uy around 0

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

                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  2. Taylor expanded in maxCos around inf

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

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

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
                    3. associate--l+N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
                    4. div-subN/A

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

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

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                    7. lower--.f3271.0

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                  4. Applied rewrites71.0%

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

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                    2. lift-*.f32N/A

                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                    3. fp-cancel-sub-sign-invN/A

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

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
                    5. lower-fma.f32N/A

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
                    6. lower-neg.f3271.0

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    7. lift-+.f32N/A

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    8. +-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    9. lift-*.f32N/A

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    10. lower-fma.f3271.0

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    11. lift-+.f32N/A

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                    12. +-commutativeN/A

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                    13. lower-+.f3271.0

                      \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                  6. Applied rewrites71.0%

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

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

                      \[\leadsto \sqrt{1 + \color{blue}{\left(ux - \left(1 + maxCos \cdot ux\right)\right)} \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
                    2. +-commutativeN/A

                      \[\leadsto \sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
                    3. fp-cancel-sub-sign-invN/A

                      \[\leadsto \sqrt{1 + \color{blue}{\left(ux - \left(1 + maxCos \cdot ux\right)\right)} \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
                    4. lower-sqrt.f32N/A

                      \[\leadsto \sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)} \]
                    5. +-commutativeN/A

                      \[\leadsto \sqrt{\left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right) + 1} \]
                  9. Applied rewrites71.8%

                    \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]

                  if 0.999660015 < (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))

                  1. Initial program 33.5%

                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  2. Add Preprocessing
                  3. Taylor expanded in uy around 0

                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  4. Step-by-step derivation
                    1. Applied rewrites29.4%

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Taylor expanded in maxCos around inf

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

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

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(ux + \frac{1}{maxCos}\right) - \frac{ux}{maxCos}\right) \cdot \color{blue}{maxCos}\right)} \]
                      3. associate--l+N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
                      4. div-subN/A

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

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

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                      7. lower--.f3230.1

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
                    4. Applied rewrites30.1%

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

                        \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                      2. lift-*.f32N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
                      3. fp-cancel-sub-sign-invN/A

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

                        \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right) + 1}} \]
                      5. lower-fma.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)}} \]
                      6. lower-neg.f3230.1

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(\color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      7. lift-+.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      8. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      9. lift-*.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      10. lower-fma.f3230.1

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\color{blue}{\mathsf{fma}\left(ux, maxCos, 1 - ux\right)}, \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      11. lift-+.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos, 1\right)} \]
                      12. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                      13. lower-+.f3230.1

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-\mathsf{fma}\left(ux, maxCos, 1 - ux\right), \left(\frac{1 - ux}{maxCos} + ux\right) \cdot maxCos, 1\right)} \]
                    6. Applied rewrites30.1%

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

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

                        \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
                      2. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
                      3. fp-cancel-sub-sign-invN/A

                        \[\leadsto 1 \cdot \sqrt{\color{blue}{ux} \cdot \left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right)} \]
                      4. *-commutativeN/A

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

                        \[\leadsto 1 \cdot \sqrt{\left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right) \cdot \color{blue}{ux}} \]
                      6. lower--.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\left(\left(1 + -1 \cdot \left(maxCos - 1\right)\right) - maxCos\right) \cdot ux} \]
                      7. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{\left(\left(-1 \cdot \left(maxCos - 1\right) + 1\right) - maxCos\right) \cdot ux} \]
                      8. lower-fma.f32N/A

                        \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux} \]
                      9. lower--.f3272.8

                        \[\leadsto 1 \cdot \sqrt{\left(\mathsf{fma}\left(-1, maxCos - 1, 1\right) - maxCos\right) \cdot ux} \]
                    9. Applied rewrites72.8%

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

                  Alternative 12: 65.2% accurate, 5.8× speedup?

                  \[\begin{array}{l} \\ 1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \end{array} \]
                  (FPCore (ux uy maxCos)
                   :precision binary32
                   (* 1.0 (sqrt (* (fma -2.0 maxCos 2.0) ux))))
                  float code(float ux, float uy, float maxCos) {
                  	return 1.0f * sqrtf((fmaf(-2.0f, maxCos, 2.0f) * ux));
                  }
                  
                  function code(ux, uy, maxCos)
                  	return Float32(Float32(1.0) * sqrt(Float32(fma(Float32(-2.0), maxCos, Float32(2.0)) * ux)))
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}
                  \end{array}
                  
                  Derivation
                  1. Initial program 54.0%

                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  2. Add Preprocessing
                  3. Taylor expanded in uy around 0

                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  4. Step-by-step derivation
                    1. Applied rewrites45.3%

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Taylor expanded in ux around 0

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
                    3. Step-by-step derivation
                      1. metadata-evalN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 - \left(\mathsf{neg}\left(-2\right)\right) \cdot maxCos\right)} \]
                      2. fp-cancel-sign-sub-invN/A

                        \[\leadsto 1 \cdot \sqrt{ux \cdot \left(2 + \color{blue}{-2 \cdot maxCos}\right)} \]
                      3. *-commutativeN/A

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

                        \[\leadsto 1 \cdot \sqrt{\left(2 + -2 \cdot maxCos\right) \cdot \color{blue}{ux}} \]
                      5. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{\left(-2 \cdot maxCos + 2\right) \cdot ux} \]
                      6. lower-fma.f3263.4

                        \[\leadsto 1 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
                    4. Applied rewrites63.4%

                      \[\leadsto 1 \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]
                    5. Add Preprocessing

                    Alternative 13: 6.6% accurate, 8.2× speedup?

                    \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - 1} \end{array} \]
                    (FPCore (ux uy maxCos) :precision binary32 (* 1.0 (sqrt (- 1.0 1.0))))
                    float code(float ux, float uy, float maxCos) {
                    	return 1.0f * sqrtf((1.0f - 1.0f));
                    }
                    
                    module fmin_fmax_functions
                        implicit none
                        private
                        public fmax
                        public fmin
                    
                        interface fmax
                            module procedure fmax88
                            module procedure fmax44
                            module procedure fmax84
                            module procedure fmax48
                        end interface
                        interface fmin
                            module procedure fmin88
                            module procedure fmin44
                            module procedure fmin84
                            module procedure fmin48
                        end interface
                    contains
                        real(8) function fmax88(x, y) result (res)
                            real(8), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                        end function
                        real(4) function fmax44(x, y) result (res)
                            real(4), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                        end function
                        real(8) function fmax84(x, y) result(res)
                            real(8), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                        end function
                        real(8) function fmax48(x, y) result(res)
                            real(4), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                        end function
                        real(8) function fmin88(x, y) result (res)
                            real(8), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                        end function
                        real(4) function fmin44(x, y) result (res)
                            real(4), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                        end function
                        real(8) function fmin84(x, y) result(res)
                            real(8), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                        end function
                        real(8) function fmin48(x, y) result(res)
                            real(4), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                        end function
                    end module
                    
                    real(4) function code(ux, uy, maxcos)
                    use fmin_fmax_functions
                        real(4), intent (in) :: ux
                        real(4), intent (in) :: uy
                        real(4), intent (in) :: maxcos
                        code = 1.0e0 * sqrt((1.0e0 - 1.0e0))
                    end function
                    
                    function code(ux, uy, maxCos)
                    	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(1.0))))
                    end
                    
                    function tmp = code(ux, uy, maxCos)
                    	tmp = single(1.0) * sqrt((single(1.0) - single(1.0)));
                    end
                    
                    \begin{array}{l}
                    
                    \\
                    1 \cdot \sqrt{1 - 1}
                    \end{array}
                    
                    Derivation
                    1. Initial program 54.0%

                      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Add Preprocessing
                    3. Taylor expanded in uy around 0

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    4. Step-by-step derivation
                      1. Applied rewrites45.3%

                        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                      2. Taylor expanded in ux around 0

                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                      3. Step-by-step derivation
                        1. Applied rewrites6.6%

                          \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                        2. Add Preprocessing

                        Reproduce

                        ?
                        herbie shell --seed 2025026 
                        (FPCore (ux uy maxCos)
                          :name "UniformSampleCone, x"
                          :precision binary32
                          :pre (and (and (and (<= 2.328306437e-10 ux) (<= ux 1.0)) (and (<= 2.328306437e-10 uy) (<= uy 1.0))) (and (<= 0.0 maxCos) (<= maxCos 1.0)))
                          (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* (+ (- 1.0 ux) (* ux maxCos)) (+ (- 1.0 ux) (* ux maxCos)))))))