Average Error: 63.0 → 0
Time: 17.3s
Precision: 64
\[n \gt 6.8 \cdot 10^{15}\]
\[\left(\left(n + 1\right) \cdot \log \left(n + 1\right) - n \cdot \log n\right) - 1\]
↓
\[\frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{\frac{0.1666666666666666851703837437526090070605}{n}}{n}\right)\]
\left(\left(n + 1\right) \cdot \log \left(n + 1\right) - n \cdot \log n\right) - 1
↓
\frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{\frac{0.1666666666666666851703837437526090070605}{n}}{n}\right)
double f(double n) {
        double r3379155 = n;
        double r3379156 = 1.0;
        double r3379157 = r3379155 + r3379156;
        double r3379158 = log(r3379157);
        double r3379159 = r3379157 * r3379158;
        double r3379160 = log(r3379155);
        double r3379161 = r3379155 * r3379160;
        double r3379162 = r3379159 - r3379161;
        double r3379163 = r3379162 - r3379156;
        return r3379163;
}
↓
double f(double n) {
        double r3379164 = 0.5;
        double r3379165 = n;
        double r3379166 = r3379164 / r3379165;
        double r3379167 = 1.0;
        double r3379168 = log(r3379165);
        double r3379169 = -r3379168;
        double r3379170 = 0.16666666666666669;
        double r3379171 = r3379170 / r3379165;
        double r3379172 = r3379171 / r3379165;
        double r3379173 = fma(r3379167, r3379169, r3379172);
        double r3379174 = r3379166 - r3379173;
        return r3379174;
}

Error

Bits error versus n

Target

Original63.0
Target0
Herbie0
\[\log \left(n + 1\right) - \left(\frac{1}{2 \cdot n} - \left(\frac{1}{3 \cdot \left(n \cdot n\right)} - \frac{4}{{n}^{3}}\right)\right)\]

Derivation

  1. Initial program 63.0

    \[\left(\left(n + 1\right) \cdot \log \left(n + 1\right) - n \cdot \log n\right) - 1\]

  2. Simplified62.0

    \[\leadsto \color{blue}{\log \left(1 + n\right) \cdot \left(1 + n\right) - \mathsf{fma}\left(n, \log n, 1\right)}\]

  3. Taylor expanded around inf 0.0

    \[\leadsto \color{blue}{0.5 \cdot \frac{1}{n} - \left(0.1666666666666666851703837437526090070605 \cdot \frac{1}{{n}^{2}} + 1 \cdot \log \left(\frac{1}{n}\right)\right)}\]

  4. Simplified0

    \[\leadsto \color{blue}{\frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{\frac{0.1666666666666666851703837437526090070605}{n}}{n}\right)}\]

  5. Final simplification0

    \[\leadsto \frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{\frac{0.1666666666666666851703837437526090070605}{n}}{n}\right)\]

Reproduce

herbie shell --seed 2019174 +o rules:numerics
(FPCore (n)
  :name "logs (example 3.8)"
  :pre (> n 6.8e+15)

  :herbie-target
  (- (log (+ n 1.0)) (- (/ 1.0 (* 2.0 n)) (- (/ 1.0 (* 3.0 (* n n))) (/ 4.0 (pow n 3.0)))))

  (- (- (* (+ n 1.0) (log (+ n 1.0))) (* n (log n))) 1.0))