Average Error: 0.0 → 0.0
Time: 3.9s
Precision: 64
\[e^{-\left(1 - x \cdot x\right)}\]
\[\frac{1}{\frac{e^{1}}{e^{x \cdot x}}}\]
e^{-\left(1 - x \cdot x\right)}
\frac{1}{\frac{e^{1}}{e^{x \cdot x}}}
double f(double x) {
        double r32243 = 1.0;
        double r32244 = x;
        double r32245 = r32244 * r32244;
        double r32246 = r32243 - r32245;
        double r32247 = -r32246;
        double r32248 = exp(r32247);
        return r32248;
}

double f(double x) {
        double r32249 = 1.0;
        double r32250 = 1.0;
        double r32251 = exp(r32250);
        double r32252 = x;
        double r32253 = r32252 * r32252;
        double r32254 = exp(r32253);
        double r32255 = r32251 / r32254;
        double r32256 = r32249 / r32255;
        return r32256;
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[e^{-\left(1 - x \cdot x\right)}\]
  2. Using strategy rm
  3. Applied add-log-exp0.0

    \[\leadsto e^{-\left(1 - \color{blue}{\log \left(e^{x \cdot x}\right)}\right)}\]
  4. Applied add-log-exp0.0

    \[\leadsto e^{-\left(\color{blue}{\log \left(e^{1}\right)} - \log \left(e^{x \cdot x}\right)\right)}\]
  5. Applied diff-log0.0

    \[\leadsto e^{-\color{blue}{\log \left(\frac{e^{1}}{e^{x \cdot x}}\right)}}\]
  6. Applied neg-log0.0

    \[\leadsto e^{\color{blue}{\log \left(\frac{1}{\frac{e^{1}}{e^{x \cdot x}}}\right)}}\]
  7. Applied rem-exp-log0.0

    \[\leadsto \color{blue}{\frac{1}{\frac{e^{1}}{e^{x \cdot x}}}}\]
  8. Final simplification0.0

    \[\leadsto \frac{1}{\frac{e^{1}}{e^{x \cdot x}}}\]

Reproduce

herbie shell --seed 2020049 +o rules:numerics
(FPCore (x)
  :name "exp neg sub"
  :precision binary64
  (exp (- (- 1 (* x x)))))