Beckmann Distribution sample, tan2theta, alphax == alphay

Percentage Accurate: 55.9% → 96.6%
Time: 7.3s
Alternatives: 10
Speedup: 10.5×

Specification

?
\[\left(0.0001 \leq \alpha \land \alpha \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u0 \land u0 \leq 1\right)\]
\[\begin{array}{l} \\ \left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \end{array} \]
(FPCore (alpha u0)
 :precision binary32
 (* (* (- alpha) alpha) (log (- 1.0 u0))))
float code(float alpha, float u0) {
	return (-alpha * alpha) * logf((1.0f - u0));
}
real(4) function code(alpha, u0)
    real(4), intent (in) :: alpha
    real(4), intent (in) :: u0
    code = (-alpha * alpha) * log((1.0e0 - u0))
end function
function code(alpha, u0)
	return Float32(Float32(Float32(-alpha) * alpha) * log(Float32(Float32(1.0) - u0)))
end
function tmp = code(alpha, u0)
	tmp = (-alpha * alpha) * log((single(1.0) - u0));
end
\begin{array}{l}

\\
\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right)
\end{array}

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 10 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 55.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \end{array} \]
(FPCore (alpha u0)
 :precision binary32
 (* (* (- alpha) alpha) (log (- 1.0 u0))))
float code(float alpha, float u0) {
	return (-alpha * alpha) * logf((1.0f - u0));
}
real(4) function code(alpha, u0)
    real(4), intent (in) :: alpha
    real(4), intent (in) :: u0
    code = (-alpha * alpha) * log((1.0e0 - u0))
end function
function code(alpha, u0)
	return Float32(Float32(Float32(-alpha) * alpha) * log(Float32(Float32(1.0) - u0)))
end
function tmp = code(alpha, u0)
	tmp = (-alpha * alpha) * log((single(1.0) - u0));
end
\begin{array}{l}

\\
\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right)
\end{array}

Alternative 1: 96.6% accurate, 0.4× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\log \left(1 - u0\right) \cdot \left({\alpha}^{-2} \cdot \left(-{\alpha}^{4}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
(FPCore (alpha u0)
 :precision binary32
 (let* ((t_0 (* (* alpha alpha) u0)))
   (if (<= (- 1.0 u0) 0.9972000122070313)
     (* (log (- 1.0 u0)) (* (pow alpha -2.0) (- (pow alpha 4.0))))
     (+ (* (* 0.5 u0) t_0) t_0))))
float code(float alpha, float u0) {
	float t_0 = (alpha * alpha) * u0;
	float tmp;
	if ((1.0f - u0) <= 0.9972000122070313f) {
		tmp = logf((1.0f - u0)) * (powf(alpha, -2.0f) * -powf(alpha, 4.0f));
	} else {
		tmp = ((0.5f * u0) * t_0) + t_0;
	}
	return tmp;
}
real(4) function code(alpha, u0)
    real(4), intent (in) :: alpha
    real(4), intent (in) :: u0
    real(4) :: t_0
    real(4) :: tmp
    t_0 = (alpha * alpha) * u0
    if ((1.0e0 - u0) <= 0.9972000122070313e0) then
        tmp = log((1.0e0 - u0)) * ((alpha ** (-2.0e0)) * -(alpha ** 4.0e0))
    else
        tmp = ((0.5e0 * u0) * t_0) + t_0
    end if
    code = tmp
end function
function code(alpha, u0)
	t_0 = Float32(Float32(alpha * alpha) * u0)
	tmp = Float32(0.0)
	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
		tmp = Float32(log(Float32(Float32(1.0) - u0)) * Float32((alpha ^ Float32(-2.0)) * Float32(-(alpha ^ Float32(4.0)))));
	else
		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
	end
	return tmp
end
function tmp_2 = code(alpha, u0)
	t_0 = (alpha * alpha) * u0;
	tmp = single(0.0);
	if ((single(1.0) - u0) <= single(0.9972000122070313))
		tmp = log((single(1.0) - u0)) * ((alpha ^ single(-2.0)) * -(alpha ^ single(4.0)));
	else
		tmp = ((single(0.5) * u0) * t_0) + t_0;
	end
	tmp_2 = tmp;
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
\mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
\;\;\;\;\log \left(1 - u0\right) \cdot \left({\alpha}^{-2} \cdot \left(-{\alpha}^{4}\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

    1. Initial program 93.5%

      \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
      2. lift-neg.f32N/A

        \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      3. distribute-lft-neg-outN/A

        \[\leadsto \color{blue}{\left(\mathsf{neg}\left(\alpha \cdot \alpha\right)\right)} \cdot \log \left(1 - u0\right) \]
      4. neg-sub0N/A

        \[\leadsto \color{blue}{\left(0 - \alpha \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
      5. flip--N/A

        \[\leadsto \color{blue}{\frac{0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)}{0 + \alpha \cdot \alpha}} \cdot \log \left(1 - u0\right) \]
      6. +-lft-identityN/A

        \[\leadsto \frac{0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)}{\color{blue}{\alpha \cdot \alpha}} \cdot \log \left(1 - u0\right) \]
      7. div-invN/A

        \[\leadsto \color{blue}{\left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{\alpha \cdot \alpha}\right)} \cdot \log \left(1 - u0\right) \]
      8. +-rgt-identityN/A

        \[\leadsto \left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{\color{blue}{\alpha \cdot \alpha + 0}}\right) \cdot \log \left(1 - u0\right) \]
      9. mul0-lftN/A

        \[\leadsto \left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{\alpha \cdot \alpha + \color{blue}{0 \cdot \alpha}}\right) \cdot \log \left(1 - u0\right) \]
      10. +-lft-identityN/A

        \[\leadsto \left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{\color{blue}{0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}}\right) \cdot \log \left(1 - u0\right) \]
      11. metadata-evalN/A

        \[\leadsto \left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{\color{blue}{0 \cdot 0} + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      12. lower-*.f32N/A

        \[\leadsto \color{blue}{\left(\left(0 \cdot 0 - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right)} \cdot \log \left(1 - u0\right) \]
      13. metadata-evalN/A

        \[\leadsto \left(\left(\color{blue}{0} - \left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      14. sub0-negN/A

        \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)\right)} \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      15. lower-neg.f32N/A

        \[\leadsto \left(\color{blue}{\left(-\left(\alpha \cdot \alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      16. pow2N/A

        \[\leadsto \left(\left(-\color{blue}{{\alpha}^{2}} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      17. pow2N/A

        \[\leadsto \left(\left(-{\alpha}^{2} \cdot \color{blue}{{\alpha}^{2}}\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      18. pow-prod-upN/A

        \[\leadsto \left(\left(-\color{blue}{{\alpha}^{\left(2 + 2\right)}}\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      19. lower-pow.f32N/A

        \[\leadsto \left(\left(-\color{blue}{{\alpha}^{\left(2 + 2\right)}}\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      20. metadata-evalN/A

        \[\leadsto \left(\left(-{\alpha}^{\color{blue}{4}}\right) \cdot \frac{1}{0 \cdot 0 + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
      21. metadata-evalN/A

        \[\leadsto \left(\left(-{\alpha}^{4}\right) \cdot \frac{1}{\color{blue}{0} + \left(\alpha \cdot \alpha + 0 \cdot \alpha\right)}\right) \cdot \log \left(1 - u0\right) \]
    4. Applied rewrites93.8%

      \[\leadsto \color{blue}{\left(\left(-{\alpha}^{4}\right) \cdot {\alpha}^{-2}\right)} \cdot \log \left(1 - u0\right) \]

    if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

    1. Initial program 39.8%

      \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
      2. lift-neg.f32N/A

        \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      3. neg-sub0N/A

        \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      4. flip--N/A

        \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      5. metadata-evalN/A

        \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      6. neg-sub0N/A

        \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      7. distribute-lft-neg-outN/A

        \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      8. lift-neg.f32N/A

        \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      9. lift-*.f32N/A

        \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      10. +-lft-identityN/A

        \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      11. associate-*l/N/A

        \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
      12. div-invN/A

        \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
      13. +-lft-identityN/A

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
      14. lower-*.f32N/A

        \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
      15. lower-*.f32N/A

        \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
      16. +-lft-identityN/A

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
      17. lower-/.f3239.8

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
    4. Applied rewrites39.8%

      \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
    5. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      2. /-rgt-identityN/A

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      3. div-invN/A

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      4. metadata-evalN/A

        \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      5. associate-*l*N/A

        \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      6. lift-*.f32N/A

        \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      7. rgt-mult-inverseN/A

        \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      8. lift-/.f32N/A

        \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      9. associate-*l*N/A

        \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      10. lift-*.f32N/A

        \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      11. *-commutativeN/A

        \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      12. lift-*.f32N/A

        \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      13. lift-*.f32N/A

        \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      14. associate-*l*N/A

        \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      15. lift-*.f32N/A

        \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      16. associate-*r*N/A

        \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      17. lower-*.f32N/A

        \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      18. lower-*.f3239.8

        \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
    6. Applied rewrites39.8%

      \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
    7. Taylor expanded in u0 around 0

      \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
    8. Step-by-step derivation
      1. distribute-lft-inN/A

        \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
      2. associate-*r*N/A

        \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
      3. *-commutativeN/A

        \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
      4. distribute-lft1-inN/A

        \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
      5. lower-*.f32N/A

        \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
      6. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
      7. lower-fma.f32N/A

        \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
      8. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
      9. unpow2N/A

        \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
      10. lower-*.f3282.3

        \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
    9. Applied rewrites86.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
    10. Step-by-step derivation
      1. Applied rewrites98.1%

        \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
    11. Recombined 2 regimes into one program.
    12. Final simplification97.0%

      \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\log \left(1 - u0\right) \cdot \left({\alpha}^{-2} \cdot \left(-{\alpha}^{4}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
    13. Add Preprocessing

    Alternative 2: 96.6% accurate, 0.5× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\frac{{\left(-\alpha\right)}^{3}}{\alpha} \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
    (FPCore (alpha u0)
     :precision binary32
     (let* ((t_0 (* (* alpha alpha) u0)))
       (if (<= (- 1.0 u0) 0.9972000122070313)
         (* (/ (pow (- alpha) 3.0) alpha) (log (- 1.0 u0)))
         (+ (* (* 0.5 u0) t_0) t_0))))
    float code(float alpha, float u0) {
    	float t_0 = (alpha * alpha) * u0;
    	float tmp;
    	if ((1.0f - u0) <= 0.9972000122070313f) {
    		tmp = (powf(-alpha, 3.0f) / alpha) * logf((1.0f - u0));
    	} else {
    		tmp = ((0.5f * u0) * t_0) + t_0;
    	}
    	return tmp;
    }
    
    real(4) function code(alpha, u0)
        real(4), intent (in) :: alpha
        real(4), intent (in) :: u0
        real(4) :: t_0
        real(4) :: tmp
        t_0 = (alpha * alpha) * u0
        if ((1.0e0 - u0) <= 0.9972000122070313e0) then
            tmp = ((-alpha ** 3.0e0) / alpha) * log((1.0e0 - u0))
        else
            tmp = ((0.5e0 * u0) * t_0) + t_0
        end if
        code = tmp
    end function
    
    function code(alpha, u0)
    	t_0 = Float32(Float32(alpha * alpha) * u0)
    	tmp = Float32(0.0)
    	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
    		tmp = Float32(Float32((Float32(-alpha) ^ Float32(3.0)) / alpha) * log(Float32(Float32(1.0) - u0)));
    	else
    		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
    	end
    	return tmp
    end
    
    function tmp_2 = code(alpha, u0)
    	t_0 = (alpha * alpha) * u0;
    	tmp = single(0.0);
    	if ((single(1.0) - u0) <= single(0.9972000122070313))
    		tmp = ((-alpha ^ single(3.0)) / alpha) * log((single(1.0) - u0));
    	else
    		tmp = ((single(0.5) * u0) * t_0) + t_0;
    	end
    	tmp_2 = tmp;
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
    \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
    \;\;\;\;\frac{{\left(-\alpha\right)}^{3}}{\alpha} \cdot \log \left(1 - u0\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

      1. Initial program 93.5%

        \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-*.f32N/A

          \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
        2. lift-neg.f32N/A

          \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        3. neg-sub0N/A

          \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        4. flip--N/A

          \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        5. metadata-evalN/A

          \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        6. neg-sub0N/A

          \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        7. distribute-lft-neg-outN/A

          \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        8. lift-neg.f32N/A

          \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        9. lift-*.f32N/A

          \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        10. +-lft-identityN/A

          \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        11. associate-*l/N/A

          \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
        12. div-invN/A

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
        13. +-lft-identityN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
        14. lower-*.f32N/A

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
        15. lower-*.f32N/A

          \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
        16. +-lft-identityN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
        17. lower-/.f3293.5

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
      4. Applied rewrites93.5%

        \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
      5. Step-by-step derivation
        1. lift-*.f32N/A

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
        2. lift-/.f32N/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
        3. un-div-invN/A

          \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
        4. lift-*.f32N/A

          \[\leadsto \frac{\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}}{\alpha} \cdot \log \left(1 - u0\right) \]
        5. lift-*.f32N/A

          \[\leadsto \frac{\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha}{\alpha} \cdot \log \left(1 - u0\right) \]
        6. associate-*l*N/A

          \[\leadsto \frac{\color{blue}{\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)}}{\alpha} \cdot \log \left(1 - u0\right) \]
        7. sqr-negN/A

          \[\leadsto \frac{\left(-\alpha\right) \cdot \color{blue}{\left(\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \left(\mathsf{neg}\left(\alpha\right)\right)\right)}}{\alpha} \cdot \log \left(1 - u0\right) \]
        8. lift-neg.f32N/A

          \[\leadsto \frac{\left(-\alpha\right) \cdot \left(\color{blue}{\left(-\alpha\right)} \cdot \left(\mathsf{neg}\left(\alpha\right)\right)\right)}{\alpha} \cdot \log \left(1 - u0\right) \]
        9. lift-neg.f32N/A

          \[\leadsto \frac{\left(-\alpha\right) \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(-\alpha\right)}\right)}{\alpha} \cdot \log \left(1 - u0\right) \]
        10. cube-multN/A

          \[\leadsto \frac{\color{blue}{{\left(-\alpha\right)}^{3}}}{\alpha} \cdot \log \left(1 - u0\right) \]
        11. lift-pow.f32N/A

          \[\leadsto \frac{\color{blue}{{\left(-\alpha\right)}^{3}}}{\alpha} \cdot \log \left(1 - u0\right) \]
        12. lift-/.f3293.7

          \[\leadsto \color{blue}{\frac{{\left(-\alpha\right)}^{3}}{\alpha}} \cdot \log \left(1 - u0\right) \]
      6. Applied rewrites93.7%

        \[\leadsto \color{blue}{\frac{{\left(-\alpha\right)}^{3}}{\alpha}} \cdot \log \left(1 - u0\right) \]

      if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

      1. Initial program 39.8%

        \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-*.f32N/A

          \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
        2. lift-neg.f32N/A

          \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        3. neg-sub0N/A

          \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        4. flip--N/A

          \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        5. metadata-evalN/A

          \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        6. neg-sub0N/A

          \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        7. distribute-lft-neg-outN/A

          \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        8. lift-neg.f32N/A

          \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        9. lift-*.f32N/A

          \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        10. +-lft-identityN/A

          \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        11. associate-*l/N/A

          \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
        12. div-invN/A

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
        13. +-lft-identityN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
        14. lower-*.f32N/A

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
        15. lower-*.f32N/A

          \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
        16. +-lft-identityN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
        17. lower-/.f3239.8

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
      4. Applied rewrites39.8%

        \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
      5. Step-by-step derivation
        1. lift-*.f32N/A

          \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        2. /-rgt-identityN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        3. div-invN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        4. metadata-evalN/A

          \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        5. associate-*l*N/A

          \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        6. lift-*.f32N/A

          \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        7. rgt-mult-inverseN/A

          \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        8. lift-/.f32N/A

          \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        9. associate-*l*N/A

          \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        10. lift-*.f32N/A

          \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        11. *-commutativeN/A

          \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        12. lift-*.f32N/A

          \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        13. lift-*.f32N/A

          \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        14. associate-*l*N/A

          \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        15. lift-*.f32N/A

          \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        16. associate-*r*N/A

          \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        17. lower-*.f32N/A

          \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        18. lower-*.f3239.8

          \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      6. Applied rewrites39.8%

        \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
      7. Taylor expanded in u0 around 0

        \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
      8. Step-by-step derivation
        1. distribute-lft-inN/A

          \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
        2. associate-*r*N/A

          \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
        3. *-commutativeN/A

          \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
        4. distribute-lft1-inN/A

          \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
        5. lower-*.f32N/A

          \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
        6. *-commutativeN/A

          \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
        7. lower-fma.f32N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
        8. lower-*.f32N/A

          \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
        9. unpow2N/A

          \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
        10. lower-*.f3286.5

          \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
      9. Applied rewrites86.5%

        \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
      10. Step-by-step derivation
        1. Applied rewrites98.1%

          \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
      11. Recombined 2 regimes into one program.
      12. Final simplification97.0%

        \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\frac{{\left(-\alpha\right)}^{3}}{\alpha} \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
      13. Add Preprocessing

      Alternative 3: 96.6% accurate, 0.8× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\frac{1}{\frac{-1}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
      (FPCore (alpha u0)
       :precision binary32
       (let* ((t_0 (* (* alpha alpha) u0)))
         (if (<= (- 1.0 u0) 0.9972000122070313)
           (* (* (/ 1.0 (/ -1.0 alpha)) alpha) (log (- 1.0 u0)))
           (+ (* (* 0.5 u0) t_0) t_0))))
      float code(float alpha, float u0) {
      	float t_0 = (alpha * alpha) * u0;
      	float tmp;
      	if ((1.0f - u0) <= 0.9972000122070313f) {
      		tmp = ((1.0f / (-1.0f / alpha)) * alpha) * logf((1.0f - u0));
      	} else {
      		tmp = ((0.5f * u0) * t_0) + t_0;
      	}
      	return tmp;
      }
      
      real(4) function code(alpha, u0)
          real(4), intent (in) :: alpha
          real(4), intent (in) :: u0
          real(4) :: t_0
          real(4) :: tmp
          t_0 = (alpha * alpha) * u0
          if ((1.0e0 - u0) <= 0.9972000122070313e0) then
              tmp = ((1.0e0 / ((-1.0e0) / alpha)) * alpha) * log((1.0e0 - u0))
          else
              tmp = ((0.5e0 * u0) * t_0) + t_0
          end if
          code = tmp
      end function
      
      function code(alpha, u0)
      	t_0 = Float32(Float32(alpha * alpha) * u0)
      	tmp = Float32(0.0)
      	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
      		tmp = Float32(Float32(Float32(Float32(1.0) / Float32(Float32(-1.0) / alpha)) * alpha) * log(Float32(Float32(1.0) - u0)));
      	else
      		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
      	end
      	return tmp
      end
      
      function tmp_2 = code(alpha, u0)
      	t_0 = (alpha * alpha) * u0;
      	tmp = single(0.0);
      	if ((single(1.0) - u0) <= single(0.9972000122070313))
      		tmp = ((single(1.0) / (single(-1.0) / alpha)) * alpha) * log((single(1.0) - u0));
      	else
      		tmp = ((single(0.5) * u0) * t_0) + t_0;
      	end
      	tmp_2 = tmp;
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
      \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
      \;\;\;\;\left(\frac{1}{\frac{-1}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

        1. Initial program 93.5%

          \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
          2. lift-neg.f32N/A

            \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          3. neg-sub0N/A

            \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          4. flip--N/A

            \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          5. metadata-evalN/A

            \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          6. neg-sub0N/A

            \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          7. distribute-lft-neg-outN/A

            \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          8. lift-neg.f32N/A

            \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          9. lift-*.f32N/A

            \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          10. +-lft-identityN/A

            \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          11. associate-*l/N/A

            \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
          12. div-invN/A

            \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
          13. +-lft-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
          14. lower-*.f32N/A

            \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
          15. lower-*.f32N/A

            \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
          16. +-lft-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
          17. lower-/.f3293.5

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
        4. Applied rewrites93.5%

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
        5. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          2. /-rgt-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          3. div-invN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          4. metadata-evalN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          5. associate-*l*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          6. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          7. rgt-mult-inverseN/A

            \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          8. lift-/.f32N/A

            \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          9. associate-*l*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          10. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          11. *-commutativeN/A

            \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          12. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          13. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          14. associate-*l*N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          15. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          16. associate-*r*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          17. lower-*.f32N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          18. lower-*.f3293.4

            \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        6. Applied rewrites93.4%

          \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        7. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \color{blue}{\left(\left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
          2. lift-*.f32N/A

            \[\leadsto \left(\color{blue}{\left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          3. associate-*l*N/A

            \[\leadsto \color{blue}{\left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \left(\alpha \cdot \frac{1}{\alpha}\right)\right)} \cdot \log \left(1 - u0\right) \]
          4. lift-/.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \log \left(1 - u0\right) \]
          5. rgt-mult-inverseN/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \color{blue}{1}\right) \cdot \log \left(1 - u0\right) \]
          6. lift-*.f32N/A

            \[\leadsto \left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot 1\right) \cdot \log \left(1 - u0\right) \]
          7. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right) \cdot 1\right) \cdot \log \left(1 - u0\right) \]
          8. associate-*r*N/A

            \[\leadsto \left(\color{blue}{\left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \log \left(1 - u0\right) \]
          9. associate-*l*N/A

            \[\leadsto \color{blue}{\left(\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right)} \cdot \log \left(1 - u0\right) \]
          10. lift-*.f32N/A

            \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          11. *-commutativeN/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          12. lift-neg.f32N/A

            \[\leadsto \left(\left(\left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          13. distribute-lft-neg-outN/A

            \[\leadsto \left(\left(\color{blue}{\left(\mathsf{neg}\left(\alpha \cdot \frac{1}{\alpha}\right)\right)} \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          14. lift-/.f32N/A

            \[\leadsto \left(\left(\left(\mathsf{neg}\left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          15. rgt-mult-inverseN/A

            \[\leadsto \left(\left(\left(\mathsf{neg}\left(\color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          16. metadata-evalN/A

            \[\leadsto \left(\left(\color{blue}{-1} \cdot \alpha\right) \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          17. neg-mul-1N/A

            \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          18. lift-neg.f32N/A

            \[\leadsto \left(\color{blue}{\left(-\alpha\right)} \cdot \left(\alpha \cdot 1\right)\right) \cdot \log \left(1 - u0\right) \]
          19. metadata-evalN/A

            \[\leadsto \left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{1}}\right)\right) \cdot \log \left(1 - u0\right) \]
          20. div-invN/A

            \[\leadsto \left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \log \left(1 - u0\right) \]
          21. /-rgt-identityN/A

            \[\leadsto \left(\left(-\alpha\right) \cdot \color{blue}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        8. Applied rewrites93.6%

          \[\leadsto \color{blue}{\left(\frac{1}{\frac{-1}{\alpha}} \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]

        if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

        1. Initial program 39.8%

          \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
          2. lift-neg.f32N/A

            \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          3. neg-sub0N/A

            \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          4. flip--N/A

            \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          5. metadata-evalN/A

            \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          6. neg-sub0N/A

            \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          7. distribute-lft-neg-outN/A

            \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          8. lift-neg.f32N/A

            \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          9. lift-*.f32N/A

            \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          10. +-lft-identityN/A

            \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          11. associate-*l/N/A

            \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
          12. div-invN/A

            \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
          13. +-lft-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
          14. lower-*.f32N/A

            \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
          15. lower-*.f32N/A

            \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
          16. +-lft-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
          17. lower-/.f3239.8

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
        4. Applied rewrites39.8%

          \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
        5. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          2. /-rgt-identityN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          3. div-invN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          4. metadata-evalN/A

            \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          5. associate-*l*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          6. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          7. rgt-mult-inverseN/A

            \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          8. lift-/.f32N/A

            \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          9. associate-*l*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          10. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          11. *-commutativeN/A

            \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          12. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          13. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          14. associate-*l*N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          15. lift-*.f32N/A

            \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          16. associate-*r*N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          17. lower-*.f32N/A

            \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          18. lower-*.f3239.8

            \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        6. Applied rewrites39.8%

          \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
        7. Taylor expanded in u0 around 0

          \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
        8. Step-by-step derivation
          1. distribute-lft-inN/A

            \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
          2. associate-*r*N/A

            \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
          3. *-commutativeN/A

            \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
          4. distribute-lft1-inN/A

            \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
          5. lower-*.f32N/A

            \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
          6. *-commutativeN/A

            \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
          7. lower-fma.f32N/A

            \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
          8. lower-*.f32N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
          9. unpow2N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
          10. lower-*.f3251.6

            \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
        9. Applied rewrites86.2%

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
        10. Step-by-step derivation
          1. Applied rewrites98.1%

            \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
        11. Recombined 2 regimes into one program.
        12. Final simplification96.9%

          \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\frac{1}{\frac{-1}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
        13. Add Preprocessing

        Alternative 4: 96.6% accurate, 0.8× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha} \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
        (FPCore (alpha u0)
         :precision binary32
         (let* ((t_0 (* (* alpha alpha) u0)))
           (if (<= (- 1.0 u0) 0.9972000122070313)
             (* (/ (* (* (- alpha) alpha) alpha) alpha) (log (- 1.0 u0)))
             (+ (* (* 0.5 u0) t_0) t_0))))
        float code(float alpha, float u0) {
        	float t_0 = (alpha * alpha) * u0;
        	float tmp;
        	if ((1.0f - u0) <= 0.9972000122070313f) {
        		tmp = (((-alpha * alpha) * alpha) / alpha) * logf((1.0f - u0));
        	} else {
        		tmp = ((0.5f * u0) * t_0) + t_0;
        	}
        	return tmp;
        }
        
        real(4) function code(alpha, u0)
            real(4), intent (in) :: alpha
            real(4), intent (in) :: u0
            real(4) :: t_0
            real(4) :: tmp
            t_0 = (alpha * alpha) * u0
            if ((1.0e0 - u0) <= 0.9972000122070313e0) then
                tmp = (((-alpha * alpha) * alpha) / alpha) * log((1.0e0 - u0))
            else
                tmp = ((0.5e0 * u0) * t_0) + t_0
            end if
            code = tmp
        end function
        
        function code(alpha, u0)
        	t_0 = Float32(Float32(alpha * alpha) * u0)
        	tmp = Float32(0.0)
        	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
        		tmp = Float32(Float32(Float32(Float32(Float32(-alpha) * alpha) * alpha) / alpha) * log(Float32(Float32(1.0) - u0)));
        	else
        		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
        	end
        	return tmp
        end
        
        function tmp_2 = code(alpha, u0)
        	t_0 = (alpha * alpha) * u0;
        	tmp = single(0.0);
        	if ((single(1.0) - u0) <= single(0.9972000122070313))
        		tmp = (((-alpha * alpha) * alpha) / alpha) * log((single(1.0) - u0));
        	else
        		tmp = ((single(0.5) * u0) * t_0) + t_0;
        	end
        	tmp_2 = tmp;
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
        \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
        \;\;\;\;\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha} \cdot \log \left(1 - u0\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

          1. Initial program 93.5%

            \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f32N/A

              \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
            2. lift-neg.f32N/A

              \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            3. neg-sub0N/A

              \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            4. flip--N/A

              \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            5. metadata-evalN/A

              \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            6. neg-sub0N/A

              \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            7. distribute-lft-neg-outN/A

              \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            8. lift-neg.f32N/A

              \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            9. lift-*.f32N/A

              \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            10. +-lft-identityN/A

              \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            11. associate-*l/N/A

              \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
            12. lower-/.f32N/A

              \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
            13. lower-*.f3293.6

              \[\leadsto \frac{\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}}{\alpha} \cdot \log \left(1 - u0\right) \]
          4. Applied rewrites93.6%

            \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]

          if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

          1. Initial program 39.8%

            \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f32N/A

              \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
            2. lift-neg.f32N/A

              \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            3. neg-sub0N/A

              \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            4. flip--N/A

              \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            5. metadata-evalN/A

              \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            6. neg-sub0N/A

              \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            7. distribute-lft-neg-outN/A

              \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            8. lift-neg.f32N/A

              \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            9. lift-*.f32N/A

              \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            10. +-lft-identityN/A

              \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            11. associate-*l/N/A

              \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
            12. div-invN/A

              \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
            13. +-lft-identityN/A

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
            14. lower-*.f32N/A

              \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
            15. lower-*.f32N/A

              \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
            16. +-lft-identityN/A

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
            17. lower-/.f3239.8

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
          4. Applied rewrites39.8%

            \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
          5. Step-by-step derivation
            1. lift-*.f32N/A

              \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            2. /-rgt-identityN/A

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            3. div-invN/A

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            4. metadata-evalN/A

              \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            5. associate-*l*N/A

              \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            6. lift-*.f32N/A

              \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            7. rgt-mult-inverseN/A

              \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            8. lift-/.f32N/A

              \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            9. associate-*l*N/A

              \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            10. lift-*.f32N/A

              \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            11. *-commutativeN/A

              \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            12. lift-*.f32N/A

              \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            13. lift-*.f32N/A

              \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            14. associate-*l*N/A

              \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            15. lift-*.f32N/A

              \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            16. associate-*r*N/A

              \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            17. lower-*.f32N/A

              \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            18. lower-*.f3239.8

              \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          6. Applied rewrites39.8%

            \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
          7. Taylor expanded in u0 around 0

            \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
          8. Step-by-step derivation
            1. distribute-lft-inN/A

              \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
            2. associate-*r*N/A

              \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
            3. *-commutativeN/A

              \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
            4. distribute-lft1-inN/A

              \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
            5. lower-*.f32N/A

              \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
            6. *-commutativeN/A

              \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
            7. lower-fma.f32N/A

              \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
            8. lower-*.f32N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
            9. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
            10. lower-*.f3256.2

              \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
          9. Applied rewrites86.2%

            \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
          10. Step-by-step derivation
            1. Applied rewrites98.1%

              \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
          11. Recombined 2 regimes into one program.
          12. Final simplification96.9%

            \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha} \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
          13. Add Preprocessing

          Alternative 5: 96.6% accurate, 0.9× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
          (FPCore (alpha u0)
           :precision binary32
           (let* ((t_0 (* (* alpha alpha) u0)))
             (if (<= (- 1.0 u0) 0.9972000122070313)
               (* (* (- alpha) alpha) (log (- 1.0 u0)))
               (+ (* (* 0.5 u0) t_0) t_0))))
          float code(float alpha, float u0) {
          	float t_0 = (alpha * alpha) * u0;
          	float tmp;
          	if ((1.0f - u0) <= 0.9972000122070313f) {
          		tmp = (-alpha * alpha) * logf((1.0f - u0));
          	} else {
          		tmp = ((0.5f * u0) * t_0) + t_0;
          	}
          	return tmp;
          }
          
          real(4) function code(alpha, u0)
              real(4), intent (in) :: alpha
              real(4), intent (in) :: u0
              real(4) :: t_0
              real(4) :: tmp
              t_0 = (alpha * alpha) * u0
              if ((1.0e0 - u0) <= 0.9972000122070313e0) then
                  tmp = (-alpha * alpha) * log((1.0e0 - u0))
              else
                  tmp = ((0.5e0 * u0) * t_0) + t_0
              end if
              code = tmp
          end function
          
          function code(alpha, u0)
          	t_0 = Float32(Float32(alpha * alpha) * u0)
          	tmp = Float32(0.0)
          	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
          		tmp = Float32(Float32(Float32(-alpha) * alpha) * log(Float32(Float32(1.0) - u0)));
          	else
          		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
          	end
          	return tmp
          end
          
          function tmp_2 = code(alpha, u0)
          	t_0 = (alpha * alpha) * u0;
          	tmp = single(0.0);
          	if ((single(1.0) - u0) <= single(0.9972000122070313))
          		tmp = (-alpha * alpha) * log((single(1.0) - u0));
          	else
          		tmp = ((single(0.5) * u0) * t_0) + t_0;
          	end
          	tmp_2 = tmp;
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
          \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
          \;\;\;\;\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

            1. Initial program 93.5%

              \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            2. Add Preprocessing

            if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

            1. Initial program 39.8%

              \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-*.f32N/A

                \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
              2. lift-neg.f32N/A

                \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              3. neg-sub0N/A

                \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              4. flip--N/A

                \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              5. metadata-evalN/A

                \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              6. neg-sub0N/A

                \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              7. distribute-lft-neg-outN/A

                \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              8. lift-neg.f32N/A

                \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              9. lift-*.f32N/A

                \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              10. +-lft-identityN/A

                \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              11. associate-*l/N/A

                \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
              12. div-invN/A

                \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
              13. +-lft-identityN/A

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
              14. lower-*.f32N/A

                \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
              15. lower-*.f32N/A

                \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
              16. +-lft-identityN/A

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
              17. lower-/.f3239.8

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
            4. Applied rewrites39.8%

              \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
            5. Step-by-step derivation
              1. lift-*.f32N/A

                \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              2. /-rgt-identityN/A

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              3. div-invN/A

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              4. metadata-evalN/A

                \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              5. associate-*l*N/A

                \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              6. lift-*.f32N/A

                \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              7. rgt-mult-inverseN/A

                \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              8. lift-/.f32N/A

                \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              9. associate-*l*N/A

                \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              10. lift-*.f32N/A

                \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              11. *-commutativeN/A

                \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              12. lift-*.f32N/A

                \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              13. lift-*.f32N/A

                \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              14. associate-*l*N/A

                \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              15. lift-*.f32N/A

                \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              16. associate-*r*N/A

                \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              17. lower-*.f32N/A

                \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
              18. lower-*.f3239.8

                \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            6. Applied rewrites39.8%

              \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
            7. Taylor expanded in u0 around 0

              \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
            8. Step-by-step derivation
              1. distribute-lft-inN/A

                \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
              2. associate-*r*N/A

                \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
              3. *-commutativeN/A

                \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
              4. distribute-lft1-inN/A

                \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
              5. lower-*.f32N/A

                \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
              6. *-commutativeN/A

                \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
              7. lower-fma.f32N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
              8. lower-*.f32N/A

                \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
              9. unpow2N/A

                \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
              10. lower-*.f3286.5

                \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
            9. Applied rewrites86.2%

              \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
            10. Step-by-step derivation
              1. Applied rewrites98.1%

                \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
            11. Recombined 2 regimes into one program.
            12. Final simplification96.9%

              \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
            13. Add Preprocessing

            Alternative 6: 96.6% accurate, 0.9× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\left(-\alpha\right) \cdot \log \left(1 - u0\right)\right) \cdot \alpha\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\ \end{array} \end{array} \]
            (FPCore (alpha u0)
             :precision binary32
             (let* ((t_0 (* (* alpha alpha) u0)))
               (if (<= (- 1.0 u0) 0.9972000122070313)
                 (* (* (- alpha) (log (- 1.0 u0))) alpha)
                 (+ (* (* 0.5 u0) t_0) t_0))))
            float code(float alpha, float u0) {
            	float t_0 = (alpha * alpha) * u0;
            	float tmp;
            	if ((1.0f - u0) <= 0.9972000122070313f) {
            		tmp = (-alpha * logf((1.0f - u0))) * alpha;
            	} else {
            		tmp = ((0.5f * u0) * t_0) + t_0;
            	}
            	return tmp;
            }
            
            real(4) function code(alpha, u0)
                real(4), intent (in) :: alpha
                real(4), intent (in) :: u0
                real(4) :: t_0
                real(4) :: tmp
                t_0 = (alpha * alpha) * u0
                if ((1.0e0 - u0) <= 0.9972000122070313e0) then
                    tmp = (-alpha * log((1.0e0 - u0))) * alpha
                else
                    tmp = ((0.5e0 * u0) * t_0) + t_0
                end if
                code = tmp
            end function
            
            function code(alpha, u0)
            	t_0 = Float32(Float32(alpha * alpha) * u0)
            	tmp = Float32(0.0)
            	if (Float32(Float32(1.0) - u0) <= Float32(0.9972000122070313))
            		tmp = Float32(Float32(Float32(-alpha) * log(Float32(Float32(1.0) - u0))) * alpha);
            	else
            		tmp = Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0);
            	end
            	return tmp
            end
            
            function tmp_2 = code(alpha, u0)
            	t_0 = (alpha * alpha) * u0;
            	tmp = single(0.0);
            	if ((single(1.0) - u0) <= single(0.9972000122070313))
            		tmp = (-alpha * log((single(1.0) - u0))) * alpha;
            	else
            		tmp = ((single(0.5) * u0) * t_0) + t_0;
            	end
            	tmp_2 = tmp;
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
            \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\
            \;\;\;\;\left(\left(-\alpha\right) \cdot \log \left(1 - u0\right)\right) \cdot \alpha\\
            
            \mathbf{else}:\\
            \;\;\;\;\left(0.5 \cdot u0\right) \cdot t\_0 + t\_0\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (-.f32 #s(literal 1 binary32) u0) < 0.99720001

              1. Initial program 93.5%

                \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
              2. Add Preprocessing
              3. Taylor expanded in alpha around 0

                \[\leadsto \color{blue}{-1 \cdot \left({\alpha}^{2} \cdot \log \left(1 - u0\right)\right)} \]
              4. Step-by-step derivation
                1. mul-1-negN/A

                  \[\leadsto \color{blue}{\mathsf{neg}\left({\alpha}^{2} \cdot \log \left(1 - u0\right)\right)} \]
                2. unpow2N/A

                  \[\leadsto \mathsf{neg}\left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot \log \left(1 - u0\right)\right) \]
                3. associate-*l*N/A

                  \[\leadsto \mathsf{neg}\left(\color{blue}{\alpha \cdot \left(\alpha \cdot \log \left(1 - u0\right)\right)}\right) \]
                4. distribute-rgt-neg-inN/A

                  \[\leadsto \color{blue}{\alpha \cdot \left(\mathsf{neg}\left(\alpha \cdot \log \left(1 - u0\right)\right)\right)} \]
                5. *-commutativeN/A

                  \[\leadsto \color{blue}{\left(\mathsf{neg}\left(\alpha \cdot \log \left(1 - u0\right)\right)\right) \cdot \alpha} \]
                6. lower-*.f32N/A

                  \[\leadsto \color{blue}{\left(\mathsf{neg}\left(\alpha \cdot \log \left(1 - u0\right)\right)\right) \cdot \alpha} \]
                7. distribute-lft-neg-inN/A

                  \[\leadsto \color{blue}{\left(\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \log \left(1 - u0\right)\right)} \cdot \alpha \]
                8. mul-1-negN/A

                  \[\leadsto \left(\color{blue}{\left(-1 \cdot \alpha\right)} \cdot \log \left(1 - u0\right)\right) \cdot \alpha \]
                9. lower-*.f32N/A

                  \[\leadsto \color{blue}{\left(\left(-1 \cdot \alpha\right) \cdot \log \left(1 - u0\right)\right)} \cdot \alpha \]
                10. mul-1-negN/A

                  \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \log \left(1 - u0\right)\right) \cdot \alpha \]
                11. lower-neg.f32N/A

                  \[\leadsto \left(\color{blue}{\left(-\alpha\right)} \cdot \log \left(1 - u0\right)\right) \cdot \alpha \]
                12. sub-negN/A

                  \[\leadsto \left(\left(-\alpha\right) \cdot \log \color{blue}{\left(1 + \left(\mathsf{neg}\left(u0\right)\right)\right)}\right) \cdot \alpha \]
                13. lower-log1p.f32N/A

                  \[\leadsto \left(\left(-\alpha\right) \cdot \color{blue}{\mathsf{log1p}\left(\mathsf{neg}\left(u0\right)\right)}\right) \cdot \alpha \]
                14. lower-neg.f3241.2

                  \[\leadsto \left(\left(-\alpha\right) \cdot \mathsf{log1p}\left(\color{blue}{-u0}\right)\right) \cdot \alpha \]
              5. Applied rewrites41.2%

                \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \mathsf{log1p}\left(-u0\right)\right) \cdot \alpha} \]
              6. Step-by-step derivation
                1. Applied rewrites93.3%

                  \[\leadsto \left(\left(-\alpha\right) \cdot \log \left(1 - u0\right)\right) \cdot \alpha \]

                if 0.99720001 < (-.f32 #s(literal 1 binary32) u0)

                1. Initial program 39.8%

                  \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                2. Add Preprocessing
                3. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
                  2. lift-neg.f32N/A

                    \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  3. neg-sub0N/A

                    \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  4. flip--N/A

                    \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  5. metadata-evalN/A

                    \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  6. neg-sub0N/A

                    \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  7. distribute-lft-neg-outN/A

                    \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  8. lift-neg.f32N/A

                    \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  9. lift-*.f32N/A

                    \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  10. +-lft-identityN/A

                    \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  11. associate-*l/N/A

                    \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
                  12. div-invN/A

                    \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                  13. +-lft-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
                  14. lower-*.f32N/A

                    \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
                  15. lower-*.f32N/A

                    \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
                  16. +-lft-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                  17. lower-/.f3239.8

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                4. Applied rewrites39.8%

                  \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                5. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  2. /-rgt-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  3. div-invN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  4. metadata-evalN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  5. associate-*l*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  6. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  7. rgt-mult-inverseN/A

                    \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  8. lift-/.f32N/A

                    \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  9. associate-*l*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  10. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  11. *-commutativeN/A

                    \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  12. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  13. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  14. associate-*l*N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  15. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  16. associate-*r*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  17. lower-*.f32N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  18. lower-*.f3239.8

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                6. Applied rewrites39.8%

                  \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                7. Taylor expanded in u0 around 0

                  \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
                8. Step-by-step derivation
                  1. distribute-lft-inN/A

                    \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
                  2. associate-*r*N/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
                  3. *-commutativeN/A

                    \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
                  4. distribute-lft1-inN/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                  5. lower-*.f32N/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                  6. *-commutativeN/A

                    \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
                  7. lower-fma.f32N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
                  8. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
                  9. unpow2N/A

                    \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                  10. lower-*.f3284.0

                    \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                9. Applied rewrites86.2%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
                10. Step-by-step derivation
                  1. Applied rewrites98.1%

                    \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
                11. Recombined 2 regimes into one program.
                12. Final simplification96.9%

                  \[\leadsto \begin{array}{l} \mathbf{if}\;1 - u0 \leq 0.9972000122070313:\\ \;\;\;\;\left(\left(-\alpha\right) \cdot \log \left(1 - u0\right)\right) \cdot \alpha\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0\\ \end{array} \]
                13. Add Preprocessing

                Alternative 7: 87.3% accurate, 3.4× speedup?

                \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\ \left(0.5 \cdot u0\right) \cdot t\_0 + t\_0 \end{array} \end{array} \]
                (FPCore (alpha u0)
                 :precision binary32
                 (let* ((t_0 (* (* alpha alpha) u0))) (+ (* (* 0.5 u0) t_0) t_0)))
                float code(float alpha, float u0) {
                	float t_0 = (alpha * alpha) * u0;
                	return ((0.5f * u0) * t_0) + t_0;
                }
                
                real(4) function code(alpha, u0)
                    real(4), intent (in) :: alpha
                    real(4), intent (in) :: u0
                    real(4) :: t_0
                    t_0 = (alpha * alpha) * u0
                    code = ((0.5e0 * u0) * t_0) + t_0
                end function
                
                function code(alpha, u0)
                	t_0 = Float32(Float32(alpha * alpha) * u0)
                	return Float32(Float32(Float32(Float32(0.5) * u0) * t_0) + t_0)
                end
                
                function tmp = code(alpha, u0)
                	t_0 = (alpha * alpha) * u0;
                	tmp = ((single(0.5) * u0) * t_0) + t_0;
                end
                
                \begin{array}{l}
                
                \\
                \begin{array}{l}
                t_0 := \left(\alpha \cdot \alpha\right) \cdot u0\\
                \left(0.5 \cdot u0\right) \cdot t\_0 + t\_0
                \end{array}
                \end{array}
                
                Derivation
                1. Initial program 53.4%

                  \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                2. Add Preprocessing
                3. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
                  2. lift-neg.f32N/A

                    \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  3. neg-sub0N/A

                    \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  4. flip--N/A

                    \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  5. metadata-evalN/A

                    \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  6. neg-sub0N/A

                    \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  7. distribute-lft-neg-outN/A

                    \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  8. lift-neg.f32N/A

                    \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  9. lift-*.f32N/A

                    \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  10. +-lft-identityN/A

                    \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  11. associate-*l/N/A

                    \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
                  12. div-invN/A

                    \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                  13. +-lft-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
                  14. lower-*.f32N/A

                    \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
                  15. lower-*.f32N/A

                    \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
                  16. +-lft-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                  17. lower-/.f3253.4

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                4. Applied rewrites53.4%

                  \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                5. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  2. /-rgt-identityN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  3. div-invN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  4. metadata-evalN/A

                    \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  5. associate-*l*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  6. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  7. rgt-mult-inverseN/A

                    \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  8. lift-/.f32N/A

                    \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  9. associate-*l*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  10. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  11. *-commutativeN/A

                    \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  12. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  13. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  14. associate-*l*N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  15. lift-*.f32N/A

                    \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  16. associate-*r*N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  17. lower-*.f32N/A

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  18. lower-*.f3253.4

                    \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                6. Applied rewrites53.4%

                  \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                7. Taylor expanded in u0 around 0

                  \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
                8. Step-by-step derivation
                  1. distribute-lft-inN/A

                    \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
                  2. associate-*r*N/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
                  3. *-commutativeN/A

                    \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
                  4. distribute-lft1-inN/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                  5. lower-*.f32N/A

                    \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                  6. *-commutativeN/A

                    \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
                  7. lower-fma.f32N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
                  8. lower-*.f32N/A

                    \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
                  9. unpow2N/A

                    \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                  10. lower-*.f3243.4

                    \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                9. Applied rewrites74.8%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
                10. Step-by-step derivation
                  1. Applied rewrites87.2%

                    \[\leadsto \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot \left(0.5 \cdot u0\right) + \color{blue}{\left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \cdot 1} \]
                  2. Final simplification87.2%

                    \[\leadsto \left(0.5 \cdot u0\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) + \left(\alpha \cdot \alpha\right) \cdot u0 \]
                  3. Add Preprocessing

                  Alternative 8: 87.1% accurate, 4.8× speedup?

                  \[\begin{array}{l} \\ \left(0.5 \cdot u0 + 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right) \end{array} \]
                  (FPCore (alpha u0)
                   :precision binary32
                   (* (+ (* 0.5 u0) 1.0) (* (* alpha alpha) u0)))
                  float code(float alpha, float u0) {
                  	return ((0.5f * u0) + 1.0f) * ((alpha * alpha) * u0);
                  }
                  
                  real(4) function code(alpha, u0)
                      real(4), intent (in) :: alpha
                      real(4), intent (in) :: u0
                      code = ((0.5e0 * u0) + 1.0e0) * ((alpha * alpha) * u0)
                  end function
                  
                  function code(alpha, u0)
                  	return Float32(Float32(Float32(Float32(0.5) * u0) + Float32(1.0)) * Float32(Float32(alpha * alpha) * u0))
                  end
                  
                  function tmp = code(alpha, u0)
                  	tmp = ((single(0.5) * u0) + single(1.0)) * ((alpha * alpha) * u0);
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  \left(0.5 \cdot u0 + 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)
                  \end{array}
                  
                  Derivation
                  1. Initial program 53.4%

                    \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                  2. Add Preprocessing
                  3. Step-by-step derivation
                    1. lift-*.f32N/A

                      \[\leadsto \color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \log \left(1 - u0\right) \]
                    2. lift-neg.f32N/A

                      \[\leadsto \left(\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    3. neg-sub0N/A

                      \[\leadsto \left(\color{blue}{\left(0 - \alpha\right)} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    4. flip--N/A

                      \[\leadsto \left(\color{blue}{\frac{0 \cdot 0 - \alpha \cdot \alpha}{0 + \alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    5. metadata-evalN/A

                      \[\leadsto \left(\frac{\color{blue}{0} - \alpha \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    6. neg-sub0N/A

                      \[\leadsto \left(\frac{\color{blue}{\mathsf{neg}\left(\alpha \cdot \alpha\right)}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    7. distribute-lft-neg-outN/A

                      \[\leadsto \left(\frac{\color{blue}{\left(\mathsf{neg}\left(\alpha\right)\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    8. lift-neg.f32N/A

                      \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right)} \cdot \alpha}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    9. lift-*.f32N/A

                      \[\leadsto \left(\frac{\color{blue}{\left(-\alpha\right) \cdot \alpha}}{0 + \alpha} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    10. +-lft-identityN/A

                      \[\leadsto \left(\frac{\left(-\alpha\right) \cdot \alpha}{\color{blue}{\alpha}} \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    11. associate-*l/N/A

                      \[\leadsto \color{blue}{\frac{\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha}{\alpha}} \cdot \log \left(1 - u0\right) \]
                    12. div-invN/A

                      \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                    13. +-lft-identityN/A

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{0 + \alpha}}\right) \cdot \log \left(1 - u0\right) \]
                    14. lower-*.f32N/A

                      \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{0 + \alpha}\right)} \cdot \log \left(1 - u0\right) \]
                    15. lower-*.f32N/A

                      \[\leadsto \left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{0 + \alpha}\right) \cdot \log \left(1 - u0\right) \]
                    16. +-lft-identityN/A

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\color{blue}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                    17. lower-/.f3253.4

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \color{blue}{\frac{1}{\alpha}}\right) \cdot \log \left(1 - u0\right) \]
                  4. Applied rewrites53.4%

                    \[\leadsto \color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \log \left(1 - u0\right) \]
                  5. Step-by-step derivation
                    1. lift-*.f32N/A

                      \[\leadsto \left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    2. /-rgt-identityN/A

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\frac{\alpha}{1}}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    3. div-invN/A

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{1}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    4. metadata-evalN/A

                      \[\leadsto \left(\left(\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \color{blue}{1}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    5. associate-*l*N/A

                      \[\leadsto \left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot 1\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    6. lift-*.f32N/A

                      \[\leadsto \left(\left(\left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot 1\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    7. rgt-mult-inverseN/A

                      \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \color{blue}{\left(\alpha \cdot \frac{1}{\alpha}\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    8. lift-/.f32N/A

                      \[\leadsto \left(\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \left(\alpha \cdot \color{blue}{\frac{1}{\alpha}}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    9. associate-*l*N/A

                      \[\leadsto \left(\left(\color{blue}{\left(\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    10. lift-*.f32N/A

                      \[\leadsto \left(\left(\left(\color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)} \cdot \frac{1}{\alpha}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    11. *-commutativeN/A

                      \[\leadsto \left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    12. lift-*.f32N/A

                      \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \alpha\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    13. lift-*.f32N/A

                      \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\color{blue}{\left(\left(-\alpha\right) \cdot \alpha\right)} \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    14. associate-*l*N/A

                      \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \color{blue}{\left(\left(-\alpha\right) \cdot \left(\alpha \cdot \alpha\right)\right)}\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    15. lift-*.f32N/A

                      \[\leadsto \left(\left(\left(\frac{1}{\alpha} \cdot \left(\left(-\alpha\right) \cdot \color{blue}{\left(\alpha \cdot \alpha\right)}\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    16. associate-*r*N/A

                      \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    17. lower-*.f32N/A

                      \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                    18. lower-*.f3253.4

                      \[\leadsto \left(\left(\left(\color{blue}{\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right)} \cdot \left(\alpha \cdot \alpha\right)\right) \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  6. Applied rewrites53.4%

                    \[\leadsto \left(\left(\color{blue}{\left(\left(\frac{1}{\alpha} \cdot \left(-\alpha\right)\right) \cdot \left(\alpha \cdot \alpha\right)\right)} \cdot \alpha\right) \cdot \frac{1}{\alpha}\right) \cdot \log \left(1 - u0\right) \]
                  7. Taylor expanded in u0 around 0

                    \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right) + {\alpha}^{2}\right)} \]
                  8. Step-by-step derivation
                    1. distribute-lft-inN/A

                      \[\leadsto \color{blue}{u0 \cdot \left(\frac{1}{2} \cdot \left({\alpha}^{2} \cdot u0\right)\right) + u0 \cdot {\alpha}^{2}} \]
                    2. associate-*r*N/A

                      \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right)} + u0 \cdot {\alpha}^{2} \]
                    3. *-commutativeN/A

                      \[\leadsto \left(u0 \cdot \frac{1}{2}\right) \cdot \left({\alpha}^{2} \cdot u0\right) + \color{blue}{{\alpha}^{2} \cdot u0} \]
                    4. distribute-lft1-inN/A

                      \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                    5. lower-*.f32N/A

                      \[\leadsto \color{blue}{\left(u0 \cdot \frac{1}{2} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right)} \]
                    6. *-commutativeN/A

                      \[\leadsto \left(\color{blue}{\frac{1}{2} \cdot u0} + 1\right) \cdot \left({\alpha}^{2} \cdot u0\right) \]
                    7. lower-fma.f32N/A

                      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{2}, u0, 1\right)} \cdot \left({\alpha}^{2} \cdot u0\right) \]
                    8. lower-*.f32N/A

                      \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \color{blue}{\left({\alpha}^{2} \cdot u0\right)} \]
                    9. unpow2N/A

                      \[\leadsto \mathsf{fma}\left(\frac{1}{2}, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                    10. lower-*.f3275.0

                      \[\leadsto \mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                  9. Applied rewrites74.8%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(0.5, u0, 1\right) \cdot \left(\left(\alpha \cdot \alpha\right) \cdot u0\right)} \]
                  10. Step-by-step derivation
                    1. Applied rewrites87.0%

                      \[\leadsto \left(0.5 \cdot u0 + 1\right) \cdot \left(\color{blue}{\left(\alpha \cdot \alpha\right)} \cdot u0\right) \]
                    2. Add Preprocessing

                    Alternative 9: 74.5% accurate, 10.5× speedup?

                    \[\begin{array}{l} \\ \left(\alpha \cdot u0\right) \cdot \alpha \end{array} \]
                    (FPCore (alpha u0) :precision binary32 (* (* alpha u0) alpha))
                    float code(float alpha, float u0) {
                    	return (alpha * u0) * alpha;
                    }
                    
                    real(4) function code(alpha, u0)
                        real(4), intent (in) :: alpha
                        real(4), intent (in) :: u0
                        code = (alpha * u0) * alpha
                    end function
                    
                    function code(alpha, u0)
                    	return Float32(Float32(alpha * u0) * alpha)
                    end
                    
                    function tmp = code(alpha, u0)
                    	tmp = (alpha * u0) * alpha;
                    end
                    
                    \begin{array}{l}
                    
                    \\
                    \left(\alpha \cdot u0\right) \cdot \alpha
                    \end{array}
                    
                    Derivation
                    1. Initial program 53.4%

                      \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                    2. Add Preprocessing
                    3. Taylor expanded in u0 around 0

                      \[\leadsto \color{blue}{{\alpha}^{2} \cdot u0} \]
                    4. Step-by-step derivation
                      1. *-commutativeN/A

                        \[\leadsto \color{blue}{u0 \cdot {\alpha}^{2}} \]
                      2. lower-*.f32N/A

                        \[\leadsto \color{blue}{u0 \cdot {\alpha}^{2}} \]
                      3. unpow2N/A

                        \[\leadsto u0 \cdot \color{blue}{\left(\alpha \cdot \alpha\right)} \]
                      4. lower-*.f3275.0

                        \[\leadsto u0 \cdot \color{blue}{\left(\alpha \cdot \alpha\right)} \]
                    5. Applied rewrites75.0%

                      \[\leadsto \color{blue}{u0 \cdot \left(\alpha \cdot \alpha\right)} \]
                    6. Step-by-step derivation
                      1. Applied rewrites75.0%

                        \[\leadsto \left(u0 \cdot \alpha\right) \cdot \color{blue}{\alpha} \]
                      2. Final simplification75.0%

                        \[\leadsto \left(\alpha \cdot u0\right) \cdot \alpha \]
                      3. Add Preprocessing

                      Alternative 10: 74.5% accurate, 10.5× speedup?

                      \[\begin{array}{l} \\ \left(\alpha \cdot \alpha\right) \cdot u0 \end{array} \]
                      (FPCore (alpha u0) :precision binary32 (* (* alpha alpha) u0))
                      float code(float alpha, float u0) {
                      	return (alpha * alpha) * u0;
                      }
                      
                      real(4) function code(alpha, u0)
                          real(4), intent (in) :: alpha
                          real(4), intent (in) :: u0
                          code = (alpha * alpha) * u0
                      end function
                      
                      function code(alpha, u0)
                      	return Float32(Float32(alpha * alpha) * u0)
                      end
                      
                      function tmp = code(alpha, u0)
                      	tmp = (alpha * alpha) * u0;
                      end
                      
                      \begin{array}{l}
                      
                      \\
                      \left(\alpha \cdot \alpha\right) \cdot u0
                      \end{array}
                      
                      Derivation
                      1. Initial program 53.4%

                        \[\left(\left(-\alpha\right) \cdot \alpha\right) \cdot \log \left(1 - u0\right) \]
                      2. Add Preprocessing
                      3. Taylor expanded in u0 around 0

                        \[\leadsto \color{blue}{{\alpha}^{2} \cdot u0} \]
                      4. Step-by-step derivation
                        1. *-commutativeN/A

                          \[\leadsto \color{blue}{u0 \cdot {\alpha}^{2}} \]
                        2. lower-*.f32N/A

                          \[\leadsto \color{blue}{u0 \cdot {\alpha}^{2}} \]
                        3. unpow2N/A

                          \[\leadsto u0 \cdot \color{blue}{\left(\alpha \cdot \alpha\right)} \]
                        4. lower-*.f3275.0

                          \[\leadsto u0 \cdot \color{blue}{\left(\alpha \cdot \alpha\right)} \]
                      5. Applied rewrites75.0%

                        \[\leadsto \color{blue}{u0 \cdot \left(\alpha \cdot \alpha\right)} \]
                      6. Final simplification75.0%

                        \[\leadsto \left(\alpha \cdot \alpha\right) \cdot u0 \]
                      7. Add Preprocessing

                      Reproduce

                      ?
                      herbie shell --seed 2024264 
                      (FPCore (alpha u0)
                        :name "Beckmann Distribution sample, tan2theta, alphax == alphay"
                        :precision binary32
                        :pre (and (and (<= 0.0001 alpha) (<= alpha 1.0)) (and (<= 2.328306437e-10 u0) (<= u0 1.0)))
                        (* (* (- alpha) alpha) (log (- 1.0 u0))))