Average Error: 63.0 → 0
Time: 11.3s
Precision: 64
\[n \gt 6.8 \cdot 10^{15}\]
\[\left(\left(n + 1\right) \cdot \log \left(n + 1\right) - n \cdot \log n\right) - 1\]
↓
\[\frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{0.16666666666666669}{n \cdot n}\right)\]
\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{0.16666666666666669}{n \cdot n}\right)
double f(double n) {
        double r58534 = n;
        double r58535 = 1.0;
        double r58536 = r58534 + r58535;
        double r58537 = log(r58536);
        double r58538 = r58536 * r58537;
        double r58539 = log(r58534);
        double r58540 = r58534 * r58539;
        double r58541 = r58538 - r58540;
        double r58542 = r58541 - r58535;
        return r58542;
}
↓
double f(double n) {
        double r58543 = 0.5;
        double r58544 = n;
        double r58545 = r58543 / r58544;
        double r58546 = 1.0;
        double r58547 = log(r58544);
        double r58548 = -r58547;
        double r58549 = 0.16666666666666669;
        double r58550 = r58544 * r58544;
        double r58551 = r58549 / r58550;
        double r58552 = fma(r58546, r58548, r58551);
        double r58553 = r58545 - r58552;
        return r58553;
}

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

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

  3. Taylor expanded around inf 0.0

    \[\leadsto \color{blue}{0.5 \cdot \frac{1}{n} - \left(1 \cdot \log \left(\frac{1}{n}\right) + 0.16666666666666669 \cdot \frac{1}{{n}^{2}}\right)}\]

  4. Simplified0

    \[\leadsto \color{blue}{\frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{0.16666666666666669}{n \cdot n}\right)}\]

  5. Final simplification0

    \[\leadsto \frac{0.5}{n} - \mathsf{fma}\left(1, -\log n, \frac{0.16666666666666669}{n \cdot n}\right)\]

Reproduce

herbie shell --seed 2020046 +o rules:numerics
(FPCore (n)
  :name "logs (example 3.8)"
  :precision binary64
  :pre (> n 6.8e+15)

  :herbie-target
  (- (log (+ n 1)) (- (/ 1 (* 2 n)) (- (/ 1 (* 3 (* n n))) (/ 4 (pow n 3)))))

  (- (- (* (+ n 1) (log (+ n 1))) (* n (log n))) 1))