Average Error: 30.2 → 0.6
Time: 4.3s
Precision: 64
\[\left(e^{x} - 2\right) + e^{-x}\]
↓
\[\mathsf{fma}\left(x, x, \mathsf{fma}\left(\frac{1}{360}, {x}^{6}, \frac{1}{12} \cdot {x}^{4}\right)\right)\]
\left(e^{x} - 2\right) + e^{-x}
↓
\mathsf{fma}\left(x, x, \mathsf{fma}\left(\frac{1}{360}, {x}^{6}, \frac{1}{12} \cdot {x}^{4}\right)\right)
double f(double x) {
        double r102510 = x;
        double r102511 = exp(r102510);
        double r102512 = 2.0;
        double r102513 = r102511 - r102512;
        double r102514 = -r102510;
        double r102515 = exp(r102514);
        double r102516 = r102513 + r102515;
        return r102516;
}
↓
double f(double x) {
        double r102517 = x;
        double r102518 = 0.002777777777777778;
        double r102519 = 6.0;
        double r102520 = pow(r102517, r102519);
        double r102521 = 0.08333333333333333;
        double r102522 = 4.0;
        double r102523 = pow(r102517, r102522);
        double r102524 = r102521 * r102523;
        double r102525 = fma(r102518, r102520, r102524);
        double r102526 = fma(r102517, r102517, r102525);
        return r102526;
}

Error

Bits error versus x

Target

Original30.2
Target0.0
Herbie0.6
\[4 \cdot {\left(\sinh \left(\frac{x}{2}\right)\right)}^{2}\]

Derivation

  1. Initial program 30.2

    \[\left(e^{x} - 2\right) + e^{-x}\]

  2. Taylor expanded around 0 0.6

    \[\leadsto \color{blue}{{x}^{2} + \left(\frac{1}{360} \cdot {x}^{6} + \frac{1}{12} \cdot {x}^{4}\right)}\]

  3. Simplified0.6

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, x, \mathsf{fma}\left(\frac{1}{360}, {x}^{6}, \frac{1}{12} \cdot {x}^{4}\right)\right)}\]

  4. Final simplification0.6

    \[\leadsto \mathsf{fma}\left(x, x, \mathsf{fma}\left(\frac{1}{360}, {x}^{6}, \frac{1}{12} \cdot {x}^{4}\right)\right)\]

Reproduce

herbie shell --seed 2020001 +o rules:numerics
(FPCore (x)
  :name "exp2 (problem 3.3.7)"
  :precision binary64

  :herbie-target
  (* 4 (pow (sinh (/ x 2)) 2))

  (+ (- (exp x) 2) (exp (- x))))