Falkner and Boettcher, Equation (20:1,3)

Percentage Accurate: 99.3% → 99.6%
Time: 8.6s
Alternatives: 10
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ \frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \end{array} \]
(FPCore (v t)
 :precision binary64
 (/
  (- 1.0 (* 5.0 (* v v)))
  (* (* (* (PI) t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))
\begin{array}{l}

\\
\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}
\end{array}

Sampling outcomes in binary64 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 10 alternatives:

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

Initial Program: 99.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \end{array} \]
(FPCore (v t)
 :precision binary64
 (/
  (- 1.0 (* 5.0 (* v v)))
  (* (* (* (PI) t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))
\begin{array}{l}

\\
\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}
\end{array}

Alternative 1: 99.6% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t} \cdot {\left(\left(\mathsf{PI}\left(\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right)}^{-1} \end{array} \]
(FPCore (v t)
 :precision binary64
 (*
  (/ (fma -5.0 (* v v) 1.0) t)
  (pow (* (* (PI) (- 1.0 (* v v))) (sqrt (fma -6.0 (* v v) 2.0))) -1.0)))
\begin{array}{l}

\\
\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t} \cdot {\left(\left(\mathsf{PI}\left(\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right)}^{-1}
\end{array}
Derivation
  1. Initial program 99.3%

    \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
    3. lift-*.f64N/A

      \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)} \cdot \left(1 - v \cdot v\right)} \]
    4. associate-*l*N/A

      \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
    5. *-rgt-identityN/A

      \[\leadsto \frac{\color{blue}{\left(1 - 5 \cdot \left(v \cdot v\right)\right) \cdot 1}}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)} \]
    6. lift-*.f64N/A

      \[\leadsto \frac{\left(1 - 5 \cdot \left(v \cdot v\right)\right) \cdot 1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right)} \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)} \]
    7. *-commutativeN/A

      \[\leadsto \frac{\left(1 - 5 \cdot \left(v \cdot v\right)\right) \cdot 1}{\color{blue}{\left(t \cdot \mathsf{PI}\left(\right)\right)} \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)} \]
    8. associate-*l*N/A

      \[\leadsto \frac{\left(1 - 5 \cdot \left(v \cdot v\right)\right) \cdot 1}{\color{blue}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)\right)}} \]
    9. times-fracN/A

      \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{t} \cdot \frac{1}{\mathsf{PI}\left(\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
  4. Applied rewrites99.6%

    \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t} \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
  5. Final simplification99.6%

    \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t} \cdot {\left(\left(\mathsf{PI}\left(\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right)}^{-1} \]
  6. Add Preprocessing

Alternative 2: 98.4% accurate, 0.6× speedup?

\[\begin{array}{l} \\ {\left(\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t\right)}^{-1} \end{array} \]
(FPCore (v t) :precision binary64 (pow (* (* (sqrt 2.0) (PI)) t) -1.0))
\begin{array}{l}

\\
{\left(\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t\right)}^{-1}
\end{array}
Derivation
  1. Initial program 99.3%

    \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in v around 0

    \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
  4. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
    3. lower-*.f64N/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
    5. lower-*.f64N/A

      \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
    6. lower-sqrt.f64N/A

      \[\leadsto \frac{1}{\left(\color{blue}{\sqrt{2}} \cdot \mathsf{PI}\left(\right)\right) \cdot t} \]
    7. lower-PI.f6497.9

      \[\leadsto \frac{1}{\left(\sqrt{2} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot t} \]
  5. Applied rewrites97.9%

    \[\leadsto \color{blue}{\frac{1}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t}} \]
  6. Final simplification97.9%

    \[\leadsto {\left(\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t\right)}^{-1} \]
  7. Add Preprocessing

Alternative 3: 98.2% accurate, 0.6× speedup?

\[\begin{array}{l} \\ {\left(\left(\sqrt{2} \cdot t\right) \cdot \mathsf{PI}\left(\right)\right)}^{-1} \end{array} \]
(FPCore (v t) :precision binary64 (pow (* (* (sqrt 2.0) t) (PI)) -1.0))
\begin{array}{l}

\\
{\left(\left(\sqrt{2} \cdot t\right) \cdot \mathsf{PI}\left(\right)\right)}^{-1}
\end{array}
Derivation
  1. Initial program 99.3%

    \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in v around 0

    \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
  4. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
    3. lower-*.f64N/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
    5. lower-*.f64N/A

      \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
    6. lower-sqrt.f64N/A

      \[\leadsto \frac{1}{\left(\color{blue}{\sqrt{2}} \cdot \mathsf{PI}\left(\right)\right) \cdot t} \]
    7. lower-PI.f6497.9

      \[\leadsto \frac{1}{\left(\sqrt{2} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot t} \]
  5. Applied rewrites97.9%

    \[\leadsto \color{blue}{\frac{1}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t}} \]
  6. Step-by-step derivation
    1. Applied rewrites97.8%

      \[\leadsto \frac{1}{\left(\sqrt{2} \cdot t\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}} \]
    2. Final simplification97.8%

      \[\leadsto {\left(\left(\sqrt{2} \cdot t\right) \cdot \mathsf{PI}\left(\right)\right)}^{-1} \]
    3. Add Preprocessing

    Alternative 4: 98.2% accurate, 0.6× speedup?

    \[\begin{array}{l} \\ {\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2}\right)}^{-1} \end{array} \]
    (FPCore (v t) :precision binary64 (pow (* (* (PI) t) (sqrt 2.0)) -1.0))
    \begin{array}{l}
    
    \\
    {\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2}\right)}^{-1}
    \end{array}
    
    Derivation
    1. Initial program 99.3%

      \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
    2. Add Preprocessing
    3. Taylor expanded in v around 0

      \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{1}{t \cdot \left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right)}} \]
      2. *-commutativeN/A

        \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
      3. lower-*.f64N/A

        \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \sqrt{2}\right) \cdot t}} \]
      4. *-commutativeN/A

        \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
      5. lower-*.f64N/A

        \[\leadsto \frac{1}{\color{blue}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot t} \]
      6. lower-sqrt.f64N/A

        \[\leadsto \frac{1}{\left(\color{blue}{\sqrt{2}} \cdot \mathsf{PI}\left(\right)\right) \cdot t} \]
      7. lower-PI.f6497.9

        \[\leadsto \frac{1}{\left(\sqrt{2} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot t} \]
    5. Applied rewrites97.9%

      \[\leadsto \color{blue}{\frac{1}{\left(\sqrt{2} \cdot \mathsf{PI}\left(\right)\right) \cdot t}} \]
    6. Step-by-step derivation
      1. Applied rewrites97.8%

        \[\leadsto \frac{1}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \color{blue}{\sqrt{2}}} \]
      2. Final simplification97.8%

        \[\leadsto {\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2}\right)}^{-1} \]
      3. Add Preprocessing

      Alternative 5: 99.3% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \end{array} \]
      (FPCore (v t)
       :precision binary64
       (/
        (/ (fma -5.0 (* v v) 1.0) (* t (PI)))
        (* (- 1.0 (* v v)) (sqrt (fma -6.0 (* v v) 2.0)))))
      \begin{array}{l}
      
      \\
      \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}
      \end{array}
      
      Derivation
      1. Initial program 99.3%

        \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        3. lift-*.f64N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)} \cdot \left(1 - v \cdot v\right)} \]
        4. associate-*l*N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
        5. associate-/r*N/A

          \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
        6. lower-/.f64N/A

          \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
      4. Applied rewrites99.4%

        \[\leadsto \color{blue}{\frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
      5. Add Preprocessing

      Alternative 6: 99.3% accurate, 1.1× speedup?

      \[\begin{array}{l} \\ \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot t\right) \cdot \mathsf{PI}\left(\right)} \end{array} \]
      (FPCore (v t)
       :precision binary64
       (/
        (fma -5.0 (* v v) 1.0)
        (* (* (* (sqrt (fma -6.0 (* v v) 2.0)) (- 1.0 (* v v))) t) (PI))))
      \begin{array}{l}
      
      \\
      \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot t\right) \cdot \mathsf{PI}\left(\right)}
      \end{array}
      
      Derivation
      1. Initial program 99.3%

        \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift--.f64N/A

          \[\leadsto \frac{\color{blue}{1 - 5 \cdot \left(v \cdot v\right)}}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        2. sub-negN/A

          \[\leadsto \frac{\color{blue}{1 + \left(\mathsf{neg}\left(5 \cdot \left(v \cdot v\right)\right)\right)}}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        3. +-commutativeN/A

          \[\leadsto \frac{\color{blue}{\left(\mathsf{neg}\left(5 \cdot \left(v \cdot v\right)\right)\right) + 1}}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        4. lift-*.f64N/A

          \[\leadsto \frac{\left(\mathsf{neg}\left(\color{blue}{5 \cdot \left(v \cdot v\right)}\right)\right) + 1}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        5. distribute-lft-neg-inN/A

          \[\leadsto \frac{\color{blue}{\left(\mathsf{neg}\left(5\right)\right) \cdot \left(v \cdot v\right)} + 1}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        6. lower-fma.f64N/A

          \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(\mathsf{neg}\left(5\right), v \cdot v, 1\right)}}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        7. metadata-eval99.3

          \[\leadsto \frac{\mathsf{fma}\left(\color{blue}{-5}, v \cdot v, 1\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        8. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        9. *-commutativeN/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(1 - v \cdot v\right) \cdot \left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)}} \]
        10. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(1 - v \cdot v\right) \cdot \color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)}} \]
        11. associate-*r*N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(1 - v \cdot v\right) \cdot \left(\mathsf{PI}\left(\right) \cdot t\right)\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}}} \]
        12. lower-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(1 - v \cdot v\right) \cdot \left(\mathsf{PI}\left(\right) \cdot t\right)\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}}} \]
      4. Applied rewrites99.3%

        \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(\left(1 - v \cdot v\right) \cdot \mathsf{PI}\left(\right)\right) \cdot t\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
      5. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\left(1 - v \cdot v\right) \cdot \mathsf{PI}\left(\right)\right) \cdot t\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\left(1 - v \cdot v\right) \cdot \mathsf{PI}\left(\right)\right) \cdot t\right)} \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        3. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\color{blue}{\left(\left(1 - v \cdot v\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot t\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        4. associate-*l*N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(1 - v \cdot v\right) \cdot \left(\mathsf{PI}\left(\right) \cdot t\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        5. *-commutativeN/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(1 - v \cdot v\right) \cdot \color{blue}{\left(t \cdot \mathsf{PI}\left(\right)\right)}\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        6. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(1 - v \cdot v\right) \cdot \color{blue}{\left(t \cdot \mathsf{PI}\left(\right)\right)}\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        7. *-commutativeN/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(t \cdot \mathsf{PI}\left(\right)\right) \cdot \left(1 - v \cdot v\right)\right)} \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}} \]
        8. associate-*l*N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(t \cdot \mathsf{PI}\left(\right)\right) \cdot \left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right)}} \]
        9. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(t \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{\left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right)}} \]
        10. *-commutativeN/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right) \cdot \left(t \cdot \mathsf{PI}\left(\right)\right)}} \]
        11. lift-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right) \cdot \color{blue}{\left(t \cdot \mathsf{PI}\left(\right)\right)}} \]
        12. associate-*r*N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right) \cdot t\right) \cdot \mathsf{PI}\left(\right)}} \]
        13. lower-*.f64N/A

          \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}\right) \cdot t\right) \cdot \mathsf{PI}\left(\right)}} \]
      6. Applied rewrites99.3%

        \[\leadsto \frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{\color{blue}{\left(\left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(1 - v \cdot v\right)\right) \cdot t\right) \cdot \mathsf{PI}\left(\right)}} \]
      7. Add Preprocessing

      Alternative 7: 98.7% accurate, 1.4× speedup?

      \[\begin{array}{l} \\ \frac{\mathsf{fma}\left(4, v \cdot v, -1\right)}{\mathsf{PI}\left(\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(-t\right)\right)} \end{array} \]
      (FPCore (v t)
       :precision binary64
       (/ (fma 4.0 (* v v) -1.0) (* (PI) (* (sqrt (fma -6.0 (* v v) 2.0)) (- t)))))
      \begin{array}{l}
      
      \\
      \frac{\mathsf{fma}\left(4, v \cdot v, -1\right)}{\mathsf{PI}\left(\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(-t\right)\right)}
      \end{array}
      
      Derivation
      1. Initial program 99.3%

        \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        3. *-commutativeN/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(1 - v \cdot v\right) \cdot \left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)}} \]
        4. associate-/r*N/A

          \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{1 - v \cdot v}}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}}} \]
        5. frac-2negN/A

          \[\leadsto \color{blue}{\frac{\mathsf{neg}\left(\frac{1 - 5 \cdot \left(v \cdot v\right)}{1 - v \cdot v}\right)}{\mathsf{neg}\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)}} \]
        6. lower-/.f64N/A

          \[\leadsto \color{blue}{\frac{\mathsf{neg}\left(\frac{1 - 5 \cdot \left(v \cdot v\right)}{1 - v \cdot v}\right)}{\mathsf{neg}\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)}} \]
      4. Applied rewrites99.3%

        \[\leadsto \color{blue}{\frac{-\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{1 - v \cdot v}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)}} \]
      5. Taylor expanded in v around 0

        \[\leadsto \frac{\color{blue}{4 \cdot {v}^{2} - 1}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
      6. Step-by-step derivation
        1. sub-negN/A

          \[\leadsto \frac{\color{blue}{4 \cdot {v}^{2} + \left(\mathsf{neg}\left(1\right)\right)}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
        2. metadata-evalN/A

          \[\leadsto \frac{4 \cdot {v}^{2} + \color{blue}{-1}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
        3. lower-fma.f64N/A

          \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(4, {v}^{2}, -1\right)}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
        4. unpow2N/A

          \[\leadsto \frac{\mathsf{fma}\left(4, \color{blue}{v \cdot v}, -1\right)}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
        5. lower-*.f6498.7

          \[\leadsto \frac{\mathsf{fma}\left(4, \color{blue}{v \cdot v}, -1\right)}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
      7. Applied rewrites98.7%

        \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(4, v \cdot v, -1\right)}}{\left(-\mathsf{PI}\left(\right)\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot t\right)} \]
      8. Final simplification98.7%

        \[\leadsto \frac{\mathsf{fma}\left(4, v \cdot v, -1\right)}{\mathsf{PI}\left(\right) \cdot \left(\sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)} \cdot \left(-t\right)\right)} \]
      9. Add Preprocessing

      Alternative 8: 98.5% accurate, 1.7× speedup?

      \[\begin{array}{l} \\ \frac{\frac{\frac{1}{\mathsf{PI}\left(\right)}}{t}}{\sqrt{2}} \end{array} \]
      (FPCore (v t) :precision binary64 (/ (/ (/ 1.0 (PI)) t) (sqrt 2.0)))
      \begin{array}{l}
      
      \\
      \frac{\frac{\frac{1}{\mathsf{PI}\left(\right)}}{t}}{\sqrt{2}}
      \end{array}
      
      Derivation
      1. Initial program 99.3%

        \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
        3. lift-*.f64N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)} \cdot \left(1 - v \cdot v\right)} \]
        4. associate-*l*N/A

          \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
        5. associate-/r*N/A

          \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
        6. lower-/.f64N/A

          \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
      4. Applied rewrites99.4%

        \[\leadsto \color{blue}{\frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
      5. Taylor expanded in v around 0

        \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
      6. Step-by-step derivation
        1. lower-sqrt.f6497.9

          \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
      7. Applied rewrites97.9%

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

        \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
      9. Step-by-step derivation
        1. Applied rewrites97.9%

          \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
        2. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \frac{\color{blue}{\frac{1}{t \cdot \mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{1}{\color{blue}{t \cdot \mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
          3. *-commutativeN/A

            \[\leadsto \frac{\frac{1}{\color{blue}{\mathsf{PI}\left(\right) \cdot t}}}{\sqrt{2}} \]
          4. associate-/r*N/A

            \[\leadsto \frac{\color{blue}{\frac{\frac{1}{\mathsf{PI}\left(\right)}}{t}}}{\sqrt{2}} \]
          5. lower-/.f64N/A

            \[\leadsto \frac{\color{blue}{\frac{\frac{1}{\mathsf{PI}\left(\right)}}{t}}}{\sqrt{2}} \]
          6. lower-/.f6498.1

            \[\leadsto \frac{\frac{\color{blue}{\frac{1}{\mathsf{PI}\left(\right)}}}{t}}{\sqrt{2}} \]
        3. Applied rewrites98.1%

          \[\leadsto \color{blue}{\frac{\frac{\frac{1}{\mathsf{PI}\left(\right)}}{t}}{\sqrt{2}}} \]
        4. Add Preprocessing

        Alternative 9: 98.3% accurate, 2.0× speedup?

        \[\begin{array}{l} \\ \frac{\frac{1}{\sqrt{2}}}{t \cdot \mathsf{PI}\left(\right)} \end{array} \]
        (FPCore (v t) :precision binary64 (/ (/ 1.0 (sqrt 2.0)) (* t (PI))))
        \begin{array}{l}
        
        \\
        \frac{\frac{1}{\sqrt{2}}}{t \cdot \mathsf{PI}\left(\right)}
        \end{array}
        
        Derivation
        1. Initial program 99.3%

          \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
          3. lift-*.f64N/A

            \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)} \cdot \left(1 - v \cdot v\right)} \]
          4. associate-*l*N/A

            \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
          5. associate-/r*N/A

            \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
          6. lower-/.f64N/A

            \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
        4. Applied rewrites99.4%

          \[\leadsto \color{blue}{\frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
        5. Taylor expanded in v around 0

          \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
        6. Step-by-step derivation
          1. lower-sqrt.f6497.9

            \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
        7. Applied rewrites97.9%

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

          \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
        9. Step-by-step derivation
          1. Applied rewrites97.9%

            \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
          2. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}}} \]
            2. lift-/.f64N/A

              \[\leadsto \frac{\color{blue}{\frac{1}{t \cdot \mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
            3. associate-/l/N/A

              \[\leadsto \color{blue}{\frac{1}{\sqrt{2} \cdot \left(t \cdot \mathsf{PI}\left(\right)\right)}} \]
            4. associate-/r*N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{\sqrt{2}}}{t \cdot \mathsf{PI}\left(\right)}} \]
            5. lower-/.f64N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{\sqrt{2}}}{t \cdot \mathsf{PI}\left(\right)}} \]
            6. lower-/.f6498.0

              \[\leadsto \frac{\color{blue}{\frac{1}{\sqrt{2}}}}{t \cdot \mathsf{PI}\left(\right)} \]
          3. Applied rewrites98.0%

            \[\leadsto \color{blue}{\frac{\frac{1}{\sqrt{2}}}{t \cdot \mathsf{PI}\left(\right)}} \]
          4. Add Preprocessing

          Alternative 10: 98.5% accurate, 2.0× speedup?

          \[\begin{array}{l} \\ \frac{\frac{1}{t}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)} \end{array} \]
          (FPCore (v t) :precision binary64 (/ (/ 1.0 t) (* (sqrt 2.0) (PI))))
          \begin{array}{l}
          
          \\
          \frac{\frac{1}{t}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)}
          \end{array}
          
          Derivation
          1. Initial program 99.3%

            \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto \color{blue}{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
            2. lift-*.f64N/A

              \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)}} \]
            3. lift-*.f64N/A

              \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right)} \cdot \left(1 - v \cdot v\right)} \]
            4. associate-*l*N/A

              \[\leadsto \frac{1 - 5 \cdot \left(v \cdot v\right)}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot t\right) \cdot \left(\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)\right)}} \]
            5. associate-/r*N/A

              \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
            6. lower-/.f64N/A

              \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\mathsf{PI}\left(\right) \cdot t}}{\sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)} \cdot \left(1 - v \cdot v\right)}} \]
          4. Applied rewrites99.4%

            \[\leadsto \color{blue}{\frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\left(1 - v \cdot v\right) \cdot \sqrt{\mathsf{fma}\left(-6, v \cdot v, 2\right)}}} \]
          5. Taylor expanded in v around 0

            \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
          6. Step-by-step derivation
            1. lower-sqrt.f6497.9

              \[\leadsto \frac{\frac{\mathsf{fma}\left(-5, v \cdot v, 1\right)}{t \cdot \mathsf{PI}\left(\right)}}{\color{blue}{\sqrt{2}}} \]
          7. Applied rewrites97.9%

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

            \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
          9. Step-by-step derivation
            1. Applied rewrites97.9%

              \[\leadsto \frac{\frac{\color{blue}{1}}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}} \]
            2. Step-by-step derivation
              1. lift-/.f64N/A

                \[\leadsto \color{blue}{\frac{\frac{1}{t \cdot \mathsf{PI}\left(\right)}}{\sqrt{2}}} \]
              2. lift-/.f64N/A

                \[\leadsto \frac{\color{blue}{\frac{1}{t \cdot \mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
              3. lift-*.f64N/A

                \[\leadsto \frac{\frac{1}{\color{blue}{t \cdot \mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
              4. associate-/r*N/A

                \[\leadsto \frac{\color{blue}{\frac{\frac{1}{t}}{\mathsf{PI}\left(\right)}}}{\sqrt{2}} \]
              5. associate-/l/N/A

                \[\leadsto \color{blue}{\frac{\frac{1}{t}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)}} \]
              6. lower-/.f64N/A

                \[\leadsto \color{blue}{\frac{\frac{1}{t}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)}} \]
              7. lower-/.f64N/A

                \[\leadsto \frac{\color{blue}{\frac{1}{t}}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)} \]
              8. lower-*.f6498.0

                \[\leadsto \frac{\frac{1}{t}}{\color{blue}{\sqrt{2} \cdot \mathsf{PI}\left(\right)}} \]
            3. Applied rewrites98.0%

              \[\leadsto \color{blue}{\frac{\frac{1}{t}}{\sqrt{2} \cdot \mathsf{PI}\left(\right)}} \]
            4. Add Preprocessing

            Reproduce

            ?
            herbie shell --seed 2024318 
            (FPCore (v t)
              :name "Falkner and Boettcher, Equation (20:1,3)"
              :precision binary64
              (/ (- 1.0 (* 5.0 (* v v))) (* (* (* (PI) t) (sqrt (* 2.0 (- 1.0 (* 3.0 (* v v)))))) (- 1.0 (* v v)))))