Average Error: 13.9 → 1.3
Time: 22.0s
Precision: 64
Internal Precision: 128
\[wj - \frac{wj \cdot e^{wj} - x}{e^{wj} + wj \cdot e^{wj}}\]
\[\frac{x}{e^{wj} + e^{wj} \cdot wj} + (wj \cdot \left(wj - wj \cdot wj\right) + \left({wj}^{4}\right))_*\]

Error

Bits error versus wj

Bits error versus x

Target

Original13.9
Target13.1
Herbie1.3
\[wj - \left(\frac{wj}{wj + 1} - \frac{x}{e^{wj} + wj \cdot e^{wj}}\right)\]

Derivation

  1. Initial program 13.9

    \[wj - \frac{wj \cdot e^{wj} - x}{e^{wj} + wj \cdot e^{wj}}\]
  2. Using strategy rm
  3. Applied div-sub13.9

    \[\leadsto wj - \color{blue}{\left(\frac{wj \cdot e^{wj}}{e^{wj} + wj \cdot e^{wj}} - \frac{x}{e^{wj} + wj \cdot e^{wj}}\right)}\]
  4. Applied associate--r-7.6

    \[\leadsto \color{blue}{\left(wj - \frac{wj \cdot e^{wj}}{e^{wj} + wj \cdot e^{wj}}\right) + \frac{x}{e^{wj} + wj \cdot e^{wj}}}\]
  5. Taylor expanded around 0 1.3

    \[\leadsto \color{blue}{\left(\left({wj}^{2} + {wj}^{4}\right) - {wj}^{3}\right)} + \frac{x}{e^{wj} + wj \cdot e^{wj}}\]
  6. Simplified1.3

    \[\leadsto \color{blue}{(wj \cdot \left(wj - wj \cdot wj\right) + \left({wj}^{4}\right))_*} + \frac{x}{e^{wj} + wj \cdot e^{wj}}\]
  7. Final simplification1.3

    \[\leadsto \frac{x}{e^{wj} + e^{wj} \cdot wj} + (wj \cdot \left(wj - wj \cdot wj\right) + \left({wj}^{4}\right))_*\]

Reproduce

herbie shell --seed 2019093 +o rules:numerics
(FPCore (wj x)
  :name "Jmat.Real.lambertw, newton loop step"

  :herbie-target
  (- wj (- (/ wj (+ wj 1)) (/ x (+ (exp wj) (* wj (exp wj))))))

  (- wj (/ (- (* wj (exp wj)) x) (+ (exp wj) (* wj (exp wj))))))