Average Error: 23.8 → 12.7
Time: 51.0s
Precision: 64
Internal Precision: 1344
\[\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2.0} + 1.0}{2.0}\]
↓
\[\frac{\sqrt[3]{(\left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*}\right) + 1.0)_* \cdot \left((\left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*}\right) + 1.0)_* \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*} \cdot \left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) + 1.0\right)\right)}}{2.0}\]

Error

Bits error versus alpha

Bits error versus beta

Bits error versus i

Derivation

  1. Initial program 23.8

    \[\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2.0} + 1.0}{2.0}\]

  2. Initial simplification12.7

    \[\leadsto \frac{(\left(\frac{\beta + \alpha}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_*}{2.0}\]
  3. Using strategy rm

  4. Applied div-inv12.7

    \[\leadsto \frac{(\color{blue}{\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right)} \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_*}{2.0}\]
  5. Using strategy rm

  6. Applied add-cbrt-cube12.7

    \[\leadsto \frac{\color{blue}{\sqrt[3]{\left((\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_* \cdot (\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_*\right) \cdot (\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_*}}}{2.0}\]
  7. Using strategy rm

  8. Applied fma-udef12.7

    \[\leadsto \frac{\sqrt[3]{\left((\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_* \cdot \color{blue}{\left(\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta} + 1.0\right)}\right) \cdot (\left(\left(\beta + \alpha\right) \cdot \frac{1}{(2 \cdot i + \alpha)_* + \left(\beta + 2.0\right)}\right) \cdot \left(\frac{\beta - \alpha}{(2 \cdot i + \alpha)_* + \beta}\right) + 1.0)_*}}{2.0}\]

  9. Final simplification12.7

    \[\leadsto \frac{\sqrt[3]{(\left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*}\right) + 1.0)_* \cdot \left((\left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*}\right) + 1.0)_* \cdot \left(\frac{\beta - \alpha}{\beta + (2 \cdot i + \alpha)_*} \cdot \left(\left(\alpha + \beta\right) \cdot \frac{1}{\left(\beta + 2.0\right) + (2 \cdot i + \alpha)_*}\right) + 1.0\right)\right)}}{2.0}\]

Runtime

Time bar (total: 51.0s)Debug logProfile

herbie shell --seed 2018216 +o rules:numerics
(FPCore (alpha beta i)
  :name "Octave 3.8, jcobi/2"
  :pre (and (> alpha -1) (> beta -1) (> i 0))
  (/ (+ (/ (/ (* (+ alpha beta) (- beta alpha)) (+ (+ alpha beta) (* 2 i))) (+ (+ (+ alpha beta) (* 2 i)) 2.0)) 1.0) 2.0))