2log (problem 3.3.6)

Average Error: 29.1 → 0.1

Time: 2.7s

Precision: binary64

Math

\[\log \left(N + 1\right) - \log N\]

↓

\[\begin{array}{l} \mathbf{if}\;N \le 3051.5709578869396:\\ \;\;\;\;e^{\log \left(\log \left(N + 1\right)\right)} - \log N\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{N} + {N}^{-2} \cdot \left(\frac{0.333333333333333315}{N} - 0.5\right)\\ \end{array}\]

C

double code(double N) {
	return ((double) (((double) log(((double) (N + 1.0)))) - ((double) log(N))));
}

↓

double code(double N) {
	double VAR;
	if ((N <= 3051.5709578869396)) {
		VAR = ((double) (((double) exp(((double) log(((double) log(((double) (N + 1.0)))))))) - ((double) log(N))));
	} else {
		VAR = ((double) (((double) (1.0 / N)) + ((double) (((double) pow(N, -2.0)) * ((double) (((double) (0.3333333333333333 / N)) - 0.5))))));
	}
	return VAR;
}

Error

Bits error versus N

Derivation

1. Split input into 2 regimes

2. if N < 3051.5709578869396

   1. Initial program 0.1

      \[\log \left(N + 1\right) - \log N\]
   2. Using strategy rm

   3. Applied add-exp-log 0.1

      \[\leadsto \color{blue}{e^{\log \left(\log \left(N + 1\right)\right)}} - \log N\]

   if 3051.5709578869396 < N

   1. Initial program 59.4

      \[\log \left(N + 1\right) - \log N\]

   2. Taylor expanded around inf 0.1

      \[\leadsto \color{blue}{\left(0.333333333333333315 \cdot \frac{1}{{N}^{3}} + 1 \cdot \frac{1}{N}\right) - 0.5 \cdot \frac{1}{{N}^{2}}}\]

   3. Simplified 0.1

      \[\leadsto \color{blue}{\frac{1}{N} + {N}^{-2} \cdot \left(\frac{0.333333333333333315}{N} - 0.5\right)}\]
3. Recombined 2 regimes into one program.

4. Final simplification 0.1

   \[\leadsto \begin{array}{l} \mathbf{if}\;N \le 3051.5709578869396:\\ \;\;\;\;e^{\log \left(\log \left(N + 1\right)\right)} - \log N\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{N} + {N}^{-2} \cdot \left(\frac{0.333333333333333315}{N} - 0.5\right)\\ \end{array}\]

Reproduce

herbie shell --seed 2020184 
(FPCore (N)
  :name "2log (problem 3.3.6)"
  :precision binary64
  (- (log (+ N 1.0)) (log N)))