Rosa's Benchmark

1. Initial program 99.8%

   \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
2. Step-by-step derivation

   1. associate-*r*99.8%

      \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

   2. distribute-rgt-out--99.8%

      \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   3. sub-neg99.8%

      \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

   4. +-commutative99.8%

      \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

   5. *-commutative99.8%

      \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

   6. distribute-rgt-neg-in99.8%

      \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

   7. fma-def99.8%

      \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   8. metadata-eval99.8%

      \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

3. Simplified99.8%

   \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

4. Final simplification99.8%

   \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right) \]

1. Split input into 2 regimes

2. if x < -2.7999999999999998 or 2.7000000000000002 < x

   1. Initial program 99.8%

      \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
   2. Step-by-step derivation

      1. associate-*r*99.8%

         \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

      2. distribute-rgt-out--99.8%

         \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

      3. sub-neg99.8%

         \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

      4. +-commutative99.8%

         \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

      5. *-commutative99.8%

         \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

      6. distribute-rgt-neg-in99.8%

         \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

      7. fma-def99.9%

         \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

      8. metadata-eval99.9%

         \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

   3. Simplified99.9%

      \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   4. Taylor expanded in x around inf 99.3%

      \[\leadsto x \cdot \color{blue}{\left(-0.12900613773279798 \cdot {x}^{2}\right)} \]
   5. Step-by-step derivation

      1. unpow299.3%

         \[\leadsto x \cdot \left(-0.12900613773279798 \cdot \color{blue}{\left(x \cdot x\right)}\right) \]

   6. Simplified99.3%

      \[\leadsto x \cdot \color{blue}{\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   if -2.7999999999999998 < x < 2.7000000000000002

   1. Initial program 99.7%

      \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
   2. Step-by-step derivation

      1. associate-*r*99.7%

         \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

      2. distribute-rgt-out--99.7%

         \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

      3. sub-neg99.7%

         \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

      4. +-commutative99.7%

         \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

      5. *-commutative99.7%

         \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

      6. distribute-rgt-neg-in99.7%

         \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

      7. fma-def99.7%

         \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

      8. metadata-eval99.7%

         \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

   3. Simplified99.7%

      \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   4. Taylor expanded in x around 0 98.2%

      \[\leadsto x \cdot \color{blue}{0.954929658551372} \]
3. Recombined 2 regimes into one program.

4. Final simplification98.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.8 \lor \neg \left(x \leq 2.7\right):\\ \;\;\;\;x \cdot \left(\left(x \cdot x\right) \cdot -0.12900613773279798\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 0.954929658551372\\ \end{array} \]

1. Split input into 3 regimes

2. if x < -2.7999999999999998

   1. Initial program 99.8%

      \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
   2. Step-by-step derivation

      1. associate-*r*99.8%

         \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

      2. distribute-rgt-out--99.8%

         \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

      3. sub-neg99.8%

         \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

      4. +-commutative99.8%

         \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

      5. *-commutative99.8%

         \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

      6. distribute-rgt-neg-in99.8%

         \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

      7. fma-def99.8%

         \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

      8. metadata-eval99.8%

         \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

   3. Simplified99.8%

      \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   4. Taylor expanded in x around inf 99.8%

      \[\leadsto x \cdot \color{blue}{\left(-0.12900613773279798 \cdot {x}^{2}\right)} \]
   5. Step-by-step derivation

      1. unpow299.8%

         \[\leadsto x \cdot \left(-0.12900613773279798 \cdot \color{blue}{\left(x \cdot x\right)}\right) \]

   6. Simplified99.8%

      \[\leadsto x \cdot \color{blue}{\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   if -2.7999999999999998 < x < 2.7000000000000002

   1. Initial program 99.7%

      \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
   2. Step-by-step derivation

      1. associate-*r*99.7%

         \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

      2. distribute-rgt-out--99.7%

         \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

      3. sub-neg99.7%

         \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

      4. +-commutative99.7%

         \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

      5. *-commutative99.7%

         \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

      6. distribute-rgt-neg-in99.7%

         \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

      7. fma-def99.7%

         \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

      8. metadata-eval99.7%

         \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

   3. Simplified99.7%

      \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   4. Taylor expanded in x around 0 98.2%

      \[\leadsto x \cdot \color{blue}{0.954929658551372} \]

   if 2.7000000000000002 < x

   1. Initial program 99.8%

      \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
   2. Step-by-step derivation

      1. associate-*r*99.9%

         \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

      2. distribute-rgt-out--99.9%

         \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

      3. sub-neg99.9%

         \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

      4. +-commutative99.9%

         \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

      5. *-commutative99.9%

         \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

      6. distribute-rgt-neg-in99.9%

         \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

      7. fma-def99.9%

         \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

      8. metadata-eval99.9%

         \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

   3. Simplified99.9%

      \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   4. Taylor expanded in x around inf 98.8%

      \[\leadsto x \cdot \color{blue}{\left(-0.12900613773279798 \cdot {x}^{2}\right)} \]
   5. Step-by-step derivation

      1. unpow298.8%

         \[\leadsto x \cdot \left(-0.12900613773279798 \cdot \color{blue}{\left(x \cdot x\right)}\right) \]

      2. *-commutative98.8%

         \[\leadsto x \cdot \color{blue}{\left(\left(x \cdot x\right) \cdot -0.12900613773279798\right)} \]

      3. associate-*r*98.9%

         \[\leadsto x \cdot \color{blue}{\left(x \cdot \left(x \cdot -0.12900613773279798\right)\right)} \]

   6. Simplified98.9%

      \[\leadsto x \cdot \color{blue}{\left(x \cdot \left(x \cdot -0.12900613773279798\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification98.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.8:\\ \;\;\;\;x \cdot \left(\left(x \cdot x\right) \cdot -0.12900613773279798\right)\\ \mathbf{elif}\;x \leq 2.7:\\ \;\;\;\;x \cdot 0.954929658551372\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(x \cdot \left(x \cdot -0.12900613773279798\right)\right)\\ \end{array} \]

1. Initial program 99.8%

   \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
2. Step-by-step derivation

   1. associate-*r*99.8%

      \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

   2. distribute-rgt-out--99.8%

      \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   3. associate-*r*99.8%

      \[\leadsto x \cdot \left(0.954929658551372 - \color{blue}{\left(0.12900613773279798 \cdot x\right) \cdot x}\right) \]

3. Applied egg-rr99.8%

   \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - \left(0.12900613773279798 \cdot x\right) \cdot x\right)} \]

4. Taylor expanded in x around 0 99.8%

   \[\leadsto x \cdot \left(0.954929658551372 - \color{blue}{0.12900613773279798 \cdot {x}^{2}}\right) \]
5. Step-by-step derivation

   1. unpow299.8%

      \[\leadsto x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \color{blue}{\left(x \cdot x\right)}\right) \]

6. Simplified99.8%

   \[\leadsto x \cdot \left(0.954929658551372 - \color{blue}{0.12900613773279798 \cdot \left(x \cdot x\right)}\right) \]

7. Final simplification99.8%

   \[\leadsto x \cdot \left(0.954929658551372 - \left(x \cdot x\right) \cdot 0.12900613773279798\right) \]

1. Initial program 99.8%

   \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
2. Step-by-step derivation

   1. associate-*r*99.8%

      \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

   2. distribute-rgt-out--99.8%

      \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   3. associate-*r*99.8%

      \[\leadsto x \cdot \left(0.954929658551372 - \color{blue}{\left(0.12900613773279798 \cdot x\right) \cdot x}\right) \]

3. Applied egg-rr99.8%

   \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - \left(0.12900613773279798 \cdot x\right) \cdot x\right)} \]

4. Final simplification99.8%

   \[\leadsto x \cdot \left(0.954929658551372 - x \cdot \left(x \cdot 0.12900613773279798\right)\right) \]

1. Initial program 99.8%

   \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
2. Step-by-step derivation

   1. associate-*r*99.8%

      \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

   2. distribute-rgt-out--99.8%

      \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   3. sub-neg99.8%

      \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

   4. +-commutative99.8%

      \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

   5. *-commutative99.8%

      \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

   6. distribute-rgt-neg-in99.8%

      \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

   7. fma-def99.8%

      \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   8. metadata-eval99.8%

      \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

3. Simplified99.8%

   \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

4. Taylor expanded in x around 0 51.3%

   \[\leadsto x \cdot \color{blue}{0.954929658551372} \]
5. Step-by-step derivation

   1. add-sqr-sqrt23.0%

      \[\leadsto \color{blue}{\sqrt{x \cdot 0.954929658551372} \cdot \sqrt{x \cdot 0.954929658551372}} \]

   2. sqrt-unprod25.0%

      \[\leadsto \color{blue}{\sqrt{\left(x \cdot 0.954929658551372\right) \cdot \left(x \cdot 0.954929658551372\right)}} \]

   3. *-commutative25.0%

      \[\leadsto \sqrt{\color{blue}{\left(0.954929658551372 \cdot x\right)} \cdot \left(x \cdot 0.954929658551372\right)} \]

   4. *-commutative25.0%

      \[\leadsto \sqrt{\left(0.954929658551372 \cdot x\right) \cdot \color{blue}{\left(0.954929658551372 \cdot x\right)}} \]

   5. swap-sqr25.0%

      \[\leadsto \sqrt{\color{blue}{\left(0.954929658551372 \cdot 0.954929658551372\right) \cdot \left(x \cdot x\right)}} \]

   6. metadata-eval25.0%

      \[\leadsto \sqrt{\color{blue}{0.9118906527810399} \cdot \left(x \cdot x\right)} \]

6. Applied egg-rr25.0%

   \[\leadsto \color{blue}{\sqrt{0.9118906527810399 \cdot \left(x \cdot x\right)}} \]
7. Step-by-step derivation

   1. unpow225.0%

      \[\leadsto \sqrt{0.9118906527810399 \cdot \color{blue}{{x}^{2}}} \]

   2. *-commutative25.0%

      \[\leadsto \sqrt{\color{blue}{{x}^{2} \cdot 0.9118906527810399}} \]

   3. unpow225.0%

      \[\leadsto \sqrt{\color{blue}{\left(x \cdot x\right)} \cdot 0.9118906527810399} \]

8. Simplified25.0%

   \[\leadsto \color{blue}{\sqrt{\left(x \cdot x\right) \cdot 0.9118906527810399}} \]

9. Taylor expanded in x around -inf 4.9%

   \[\leadsto \color{blue}{-0.954929658551372 \cdot x} \]
10. Step-by-step derivation

    1. *-commutative4.9%

       \[\leadsto \color{blue}{x \cdot -0.954929658551372} \]

11. Simplified4.9%

    \[\leadsto \color{blue}{x \cdot -0.954929658551372} \]

12. Final simplification4.9%

    \[\leadsto x \cdot -0.954929658551372 \]

1. Initial program 99.8%

   \[0.954929658551372 \cdot x - 0.12900613773279798 \cdot \left(\left(x \cdot x\right) \cdot x\right) \]
2. Step-by-step derivation

   1. associate-*r*99.8%

      \[\leadsto 0.954929658551372 \cdot x - \color{blue}{\left(0.12900613773279798 \cdot \left(x \cdot x\right)\right) \cdot x} \]

   2. distribute-rgt-out--99.8%

      \[\leadsto \color{blue}{x \cdot \left(0.954929658551372 - 0.12900613773279798 \cdot \left(x \cdot x\right)\right)} \]

   3. sub-neg99.8%

      \[\leadsto x \cdot \color{blue}{\left(0.954929658551372 + \left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right)\right)} \]

   4. +-commutative99.8%

      \[\leadsto x \cdot \color{blue}{\left(\left(-0.12900613773279798 \cdot \left(x \cdot x\right)\right) + 0.954929658551372\right)} \]

   5. *-commutative99.8%

      \[\leadsto x \cdot \left(\left(-\color{blue}{\left(x \cdot x\right) \cdot 0.12900613773279798}\right) + 0.954929658551372\right) \]

   6. distribute-rgt-neg-in99.8%

      \[\leadsto x \cdot \left(\color{blue}{\left(x \cdot x\right) \cdot \left(-0.12900613773279798\right)} + 0.954929658551372\right) \]

   7. fma-def99.8%

      \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

   8. metadata-eval99.8%

      \[\leadsto x \cdot \mathsf{fma}\left(x \cdot x, \color{blue}{-0.12900613773279798}, 0.954929658551372\right) \]

3. Simplified99.8%

   \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(x \cdot x, -0.12900613773279798, 0.954929658551372\right)} \]

4. Taylor expanded in x around 0 51.3%

   \[\leadsto x \cdot \color{blue}{0.954929658551372} \]

5. Final simplification51.3%

   \[\leadsto x \cdot 0.954929658551372 \]

herbie shell --seed 2023167 
(FPCore (x)
  :name "Rosa's Benchmark"
  :precision binary64
  (- (* 0.954929658551372 x) (* 0.12900613773279798 (* (* x x) x))))