Average Error: 15.4 → 14.9
Time: 4.2s
Precision: 64
\[1 - \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}\]
↓
\[\frac{e^{\log \left(\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]
1 - \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}
↓
\frac{e^{\log \left(\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}
double code(double x) {
	return (1.0 - sqrt((0.5 * (1.0 + (1.0 / hypot(1.0, x))))));
}
↓
double code(double x) {
	return (exp(log(((1.0 * ((((1.0 * 1.0) - (0.5 * 0.5)) * hypot(1.0, x)) - (0.5 * (0.5 + 1.0)))) / ((1.0 + 0.5) * hypot(1.0, x))))) / (1.0 + sqrt((0.5 * (1.0 + (1.0 / hypot(1.0, x)))))));
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 15.4

    \[1 - \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}\]
  2. Using strategy rm

  3. Applied flip--15.4

    \[\leadsto \color{blue}{\frac{1 \cdot 1 - \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)} \cdot \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}}\]

  4. Simplified14.9

    \[\leadsto \frac{\color{blue}{1 \cdot \left(1 - 0.5\right) - 0.5 \cdot \frac{1}{\mathsf{hypot}\left(1, x\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]
  5. Using strategy rm

  6. Applied associate-*r/14.9

    \[\leadsto \frac{1 \cdot \left(1 - 0.5\right) - \color{blue}{\frac{0.5 \cdot 1}{\mathsf{hypot}\left(1, x\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  7. Applied flip--14.9

    \[\leadsto \frac{1 \cdot \color{blue}{\frac{1 \cdot 1 - 0.5 \cdot 0.5}{1 + 0.5}} - \frac{0.5 \cdot 1}{\mathsf{hypot}\left(1, x\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  8. Applied associate-*r/14.9

    \[\leadsto \frac{\color{blue}{\frac{1 \cdot \left(1 \cdot 1 - 0.5 \cdot 0.5\right)}{1 + 0.5}} - \frac{0.5 \cdot 1}{\mathsf{hypot}\left(1, x\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  9. Applied frac-sub14.9

    \[\leadsto \frac{\color{blue}{\frac{\left(1 \cdot \left(1 \cdot 1 - 0.5 \cdot 0.5\right)\right) \cdot \mathsf{hypot}\left(1, x\right) - \left(1 + 0.5\right) \cdot \left(0.5 \cdot 1\right)}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  10. Simplified14.9

    \[\leadsto \frac{\frac{\color{blue}{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]
  11. Using strategy rm

  12. Applied add-exp-log17.7

    \[\leadsto \frac{\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\left(1 + 0.5\right) \cdot \color{blue}{e^{\log \left(\mathsf{hypot}\left(1, x\right)\right)}}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  13. Applied add-exp-log17.7

    \[\leadsto \frac{\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\color{blue}{e^{\log \left(1 + 0.5\right)}} \cdot e^{\log \left(\mathsf{hypot}\left(1, x\right)\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  14. Applied prod-exp17.7

    \[\leadsto \frac{\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\color{blue}{e^{\log \left(1 + 0.5\right) + \log \left(\mathsf{hypot}\left(1, x\right)\right)}}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  15. Applied add-exp-log17.5

    \[\leadsto \frac{\frac{1 \cdot \color{blue}{e^{\log \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}}}{e^{\log \left(1 + 0.5\right) + \log \left(\mathsf{hypot}\left(1, x\right)\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  16. Applied add-exp-log17.5

    \[\leadsto \frac{\frac{\color{blue}{e^{\log 1}} \cdot e^{\log \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}}{e^{\log \left(1 + 0.5\right) + \log \left(\mathsf{hypot}\left(1, x\right)\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  17. Applied prod-exp17.5

    \[\leadsto \frac{\frac{\color{blue}{e^{\log 1 + \log \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}}}{e^{\log \left(1 + 0.5\right) + \log \left(\mathsf{hypot}\left(1, x\right)\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  18. Applied div-exp17.5

    \[\leadsto \frac{\color{blue}{e^{\left(\log 1 + \log \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)\right) - \left(\log \left(1 + 0.5\right) + \log \left(\mathsf{hypot}\left(1, x\right)\right)\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  19. Simplified14.9

    \[\leadsto \frac{e^{\color{blue}{\log \left(\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}\right)}}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

  20. Final simplification14.9

    \[\leadsto \frac{e^{\log \left(\frac{1 \cdot \left(\left(1 \cdot 1 - 0.5 \cdot 0.5\right) \cdot \mathsf{hypot}\left(1, x\right) - 0.5 \cdot \left(0.5 + 1\right)\right)}{\left(1 + 0.5\right) \cdot \mathsf{hypot}\left(1, x\right)}\right)}}{1 + \sqrt{0.5 \cdot \left(1 + \frac{1}{\mathsf{hypot}\left(1, x\right)}\right)}}\]

Reproduce

herbie shell --seed 2020049 
(FPCore (x)
  :name "Given's Rotation SVD example, simplified"
  :precision binary64
  (- 1 (sqrt (* 0.5 (+ 1 (/ 1 (hypot 1 x)))))))