Average Error: 0.4 → 0.1
Time: 4.5s
Precision: binary64
\[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\pi \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]
↓
\[\begin{array}{l} t_1 := \sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}}\\ \frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)}}{t} \cdot \left(t_1 \cdot t_1\right) \end{array} \]
\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\pi \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)}
↓
\begin{array}{l}
t_1 := \sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}}\\
\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)}}{t} \cdot \left(t_1 \cdot t_1\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)))))
↓
(FPCore (v t)
 :precision binary64
 (let* ((t_1 (sqrt (pow (- 1.0 (* (* v v) 3.0)) -0.5))))
   (*
    (/ (/ (- 1.0 (* 5.0 (* v v))) (* (* PI (sqrt 2.0)) (- 1.0 (* v v)))) t)
    (* t_1 t_1))))
double code(double v, double t) {
	return (1.0 - (5.0 * (v * v))) / (((((double) M_PI) * t) * sqrt((2.0 * (1.0 - (3.0 * (v * v)))))) * (1.0 - (v * v)));
}
↓
double code(double v, double t) {
	double t_1 = sqrt(pow((1.0 - ((v * v) * 3.0)), -0.5));
	return (((1.0 - (5.0 * (v * v))) / ((((double) M_PI) * sqrt(2.0)) * (1.0 - (v * v)))) / t) * (t_1 * t_1);
}

Error

Bits error versus v

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.4

    \[\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\left(\pi \cdot t\right) \cdot \sqrt{2 \cdot \left(1 - 3 \cdot \left(v \cdot v\right)\right)}\right) \cdot \left(1 - v \cdot v\right)} \]

  2. Taylor expanded in t around 0 0.4

    \[\leadsto \color{blue}{\frac{1 - 5 \cdot {v}^{2}}{\left(\pi \cdot \sqrt{2} - {v}^{2} \cdot \left(\pi \cdot \sqrt{2}\right)\right) \cdot t} \cdot \sqrt{\frac{1}{1 - 3 \cdot {v}^{2}}}} \]

  3. Applied egg-rr0.3

    \[\leadsto \color{blue}{\left(\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)} \cdot \frac{1}{t}\right)} \cdot \sqrt{\frac{1}{1 - 3 \cdot {v}^{2}}} \]

  4. Applied egg-rr0.1

    \[\leadsto \color{blue}{\frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)}}{t}} \cdot \sqrt{\frac{1}{1 - 3 \cdot {v}^{2}}} \]

  5. Applied egg-rr0.1

    \[\leadsto \frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)}}{t} \cdot \color{blue}{\left(\sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}} \cdot \sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}}\right)} \]

  6. Final simplification0.1

    \[\leadsto \frac{\frac{1 - 5 \cdot \left(v \cdot v\right)}{\left(\pi \cdot \sqrt{2}\right) \cdot \left(1 - v \cdot v\right)}}{t} \cdot \left(\sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}} \cdot \sqrt{{\left(1 - \left(v \cdot v\right) \cdot 3\right)}^{-0.5}}\right) \]

Reproduce

herbie shell --seed 2022130 
(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)))))