Average Error: 60.4 → 0.1
Time: 11.9s
Precision: binary64
\[-1 < \varepsilon \land \varepsilon < 1\]
\[[a, b]=\mathsf{sort}([a, b])\]
\[\frac{\varepsilon \cdot \left(e^{\left(a + b\right) \cdot \varepsilon} - 1\right)}{\left(e^{a \cdot \varepsilon} - 1\right) \cdot \left(e^{b \cdot \varepsilon} - 1\right)} \]
\[\begin{array}{l} t_0 := \varepsilon \cdot \left(a + b\right)\\ t_1 := \frac{\varepsilon \cdot \left(e^{t_0} - 1\right)}{\left(e^{\varepsilon \cdot a} - 1\right) \cdot \left(e^{\varepsilon \cdot b} - 1\right)}\\ \mathbf{if}\;t_1 \leq -\infty:\\ \;\;\;\;\mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \frac{1}{a}\right)\\ \mathbf{elif}\;t_1 \leq 0.0017847522660158154:\\ \;\;\;\;\frac{\frac{\varepsilon}{\mathsf{expm1}\left(\varepsilon \cdot a\right)} \cdot \mathsf{expm1}\left(t_0\right)}{\mathsf{expm1}\left(\varepsilon \cdot b\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{b} + \mathsf{fma}\left(b \cdot \left(\varepsilon \cdot \varepsilon\right), 0.08333333333333333, \frac{1}{a}\right)\\ \end{array} \]
\frac{\varepsilon \cdot \left(e^{\left(a + b\right) \cdot \varepsilon} - 1\right)}{\left(e^{a \cdot \varepsilon} - 1\right) \cdot \left(e^{b \cdot \varepsilon} - 1\right)}
\begin{array}{l}
t_0 := \varepsilon \cdot \left(a + b\right)\\
t_1 := \frac{\varepsilon \cdot \left(e^{t_0} - 1\right)}{\left(e^{\varepsilon \cdot a} - 1\right) \cdot \left(e^{\varepsilon \cdot b} - 1\right)}\\
\mathbf{if}\;t_1 \leq -\infty:\\
\;\;\;\;\mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \frac{1}{a}\right)\\

\mathbf{elif}\;t_1 \leq 0.0017847522660158154:\\
\;\;\;\;\frac{\frac{\varepsilon}{\mathsf{expm1}\left(\varepsilon \cdot a\right)} \cdot \mathsf{expm1}\left(t_0\right)}{\mathsf{expm1}\left(\varepsilon \cdot b\right)}\\

\mathbf{else}:\\
\;\;\;\;\frac{1}{b} + \mathsf{fma}\left(b \cdot \left(\varepsilon \cdot \varepsilon\right), 0.08333333333333333, \frac{1}{a}\right)\\


\end{array}
(FPCore (a b eps)
 :precision binary64
 (/
  (* eps (- (exp (* (+ a b) eps)) 1.0))
  (* (- (exp (* a eps)) 1.0) (- (exp (* b eps)) 1.0))))
(FPCore (a b eps)
 :precision binary64
 (let* ((t_0 (* eps (+ a b)))
        (t_1
         (/
          (* eps (- (exp t_0) 1.0))
          (* (- (exp (* eps a)) 1.0) (- (exp (* eps b)) 1.0)))))
   (if (<= t_1 (- INFINITY))
     (fma 0.08333333333333333 (* a (* eps eps)) (+ (/ 1.0 b) (/ 1.0 a)))
     (if (<= t_1 0.0017847522660158154)
       (/ (* (/ eps (expm1 (* eps a))) (expm1 t_0)) (expm1 (* eps b)))
       (+ (/ 1.0 b) (fma (* b (* eps eps)) 0.08333333333333333 (/ 1.0 a)))))))
double code(double a, double b, double eps) {
	return (eps * (exp((a + b) * eps) - 1.0)) / ((exp(a * eps) - 1.0) * (exp(b * eps) - 1.0));
}
double code(double a, double b, double eps) {
	double t_0 = eps * (a + b);
	double t_1 = (eps * (exp(t_0) - 1.0)) / ((exp(eps * a) - 1.0) * (exp(eps * b) - 1.0));
	double tmp;
	if (t_1 <= -((double) INFINITY)) {
		tmp = fma(0.08333333333333333, (a * (eps * eps)), ((1.0 / b) + (1.0 / a)));
	} else if (t_1 <= 0.0017847522660158154) {
		tmp = ((eps / expm1(eps * a)) * expm1(t_0)) / expm1(eps * b);
	} else {
		tmp = (1.0 / b) + fma((b * (eps * eps)), 0.08333333333333333, (1.0 / a));
	}
	return tmp;
}

Error

Bits error versus a

Bits error versus b

Bits error versus eps

Target

Original60.4
Target14.7
Herbie0.1
\[\frac{a + b}{a \cdot b} \]

Derivation

  1. Split input into 3 regimes
  2. if (/.f64 (*.f64 eps (-.f64 (exp.f64 (*.f64 (+.f64 a b) eps)) 1)) (*.f64 (-.f64 (exp.f64 (*.f64 a eps)) 1) (-.f64 (exp.f64 (*.f64 b eps)) 1))) < -inf.0

    1. Initial program 64.0

      \[\frac{\varepsilon \cdot \left(e^{\left(a + b\right) \cdot \varepsilon} - 1\right)}{\left(e^{a \cdot \varepsilon} - 1\right) \cdot \left(e^{b \cdot \varepsilon} - 1\right)} \]
    2. Simplified16.4

      \[\leadsto \color{blue}{\frac{\varepsilon \cdot \mathsf{expm1}\left(\varepsilon \cdot \left(a + b\right)\right)}{\mathsf{expm1}\left(\varepsilon \cdot a\right) \cdot \mathsf{expm1}\left(\varepsilon \cdot b\right)}} \]
    3. Taylor expanded in eps around 0 10.6

      \[\leadsto \color{blue}{0.08333333333333333 \cdot \left({\varepsilon}^{2} \cdot a\right) + \left(\frac{1}{b} + \left(\frac{1}{a} + 0.08333333333333333 \cdot \left({\varepsilon}^{2} \cdot b\right)\right)\right)} \]
    4. Simplified10.6

      \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \mathsf{fma}\left(0.08333333333333333, b \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{a}\right)\right)} \]
    5. Taylor expanded in b around 0 0.0

      \[\leadsto \mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \color{blue}{\frac{1}{a}}\right) \]

    if -inf.0 < (/.f64 (*.f64 eps (-.f64 (exp.f64 (*.f64 (+.f64 a b) eps)) 1)) (*.f64 (-.f64 (exp.f64 (*.f64 a eps)) 1) (-.f64 (exp.f64 (*.f64 b eps)) 1))) < 0.0017847522660158154

    1. Initial program 3.8

      \[\frac{\varepsilon \cdot \left(e^{\left(a + b\right) \cdot \varepsilon} - 1\right)}{\left(e^{a \cdot \varepsilon} - 1\right) \cdot \left(e^{b \cdot \varepsilon} - 1\right)} \]
    2. Simplified0.1

      \[\leadsto \color{blue}{\frac{\varepsilon \cdot \mathsf{expm1}\left(\varepsilon \cdot \left(a + b\right)\right)}{\mathsf{expm1}\left(\varepsilon \cdot a\right) \cdot \mathsf{expm1}\left(\varepsilon \cdot b\right)}} \]
    3. Applied associate-/r*_binary640.1

      \[\leadsto \color{blue}{\frac{\frac{\varepsilon \cdot \mathsf{expm1}\left(\varepsilon \cdot \left(a + b\right)\right)}{\mathsf{expm1}\left(\varepsilon \cdot a\right)}}{\mathsf{expm1}\left(\varepsilon \cdot b\right)}} \]
    4. Simplified0.1

      \[\leadsto \frac{\color{blue}{\frac{\varepsilon}{\mathsf{expm1}\left(a \cdot \varepsilon\right)} \cdot \mathsf{expm1}\left(\left(a + b\right) \cdot \varepsilon\right)}}{\mathsf{expm1}\left(\varepsilon \cdot b\right)} \]

    if 0.0017847522660158154 < (/.f64 (*.f64 eps (-.f64 (exp.f64 (*.f64 (+.f64 a b) eps)) 1)) (*.f64 (-.f64 (exp.f64 (*.f64 a eps)) 1) (-.f64 (exp.f64 (*.f64 b eps)) 1)))

    1. Initial program 64.0

      \[\frac{\varepsilon \cdot \left(e^{\left(a + b\right) \cdot \varepsilon} - 1\right)}{\left(e^{a \cdot \varepsilon} - 1\right) \cdot \left(e^{b \cdot \varepsilon} - 1\right)} \]
    2. Simplified48.2

      \[\leadsto \color{blue}{\frac{\varepsilon \cdot \mathsf{expm1}\left(\varepsilon \cdot \left(a + b\right)\right)}{\mathsf{expm1}\left(\varepsilon \cdot a\right) \cdot \mathsf{expm1}\left(\varepsilon \cdot b\right)}} \]
    3. Taylor expanded in eps around 0 1.8

      \[\leadsto \color{blue}{0.08333333333333333 \cdot \left({\varepsilon}^{2} \cdot a\right) + \left(\frac{1}{b} + \left(\frac{1}{a} + 0.08333333333333333 \cdot \left({\varepsilon}^{2} \cdot b\right)\right)\right)} \]
    4. Simplified1.8

      \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \mathsf{fma}\left(0.08333333333333333, b \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{a}\right)\right)} \]
    5. Taylor expanded in a around 0 0.1

      \[\leadsto \color{blue}{\frac{1}{b} + \left(\frac{1}{a} + 0.08333333333333333 \cdot \left({\varepsilon}^{2} \cdot b\right)\right)} \]
    6. Simplified0.1

      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\varepsilon \cdot \varepsilon\right) \cdot b, 0.08333333333333333, \frac{1}{a}\right) + \frac{1}{b}} \]
  3. Recombined 3 regimes into one program.
  4. Final simplification0.1

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{\varepsilon \cdot \left(e^{\varepsilon \cdot \left(a + b\right)} - 1\right)}{\left(e^{\varepsilon \cdot a} - 1\right) \cdot \left(e^{\varepsilon \cdot b} - 1\right)} \leq -\infty:\\ \;\;\;\;\mathsf{fma}\left(0.08333333333333333, a \cdot \left(\varepsilon \cdot \varepsilon\right), \frac{1}{b} + \frac{1}{a}\right)\\ \mathbf{elif}\;\frac{\varepsilon \cdot \left(e^{\varepsilon \cdot \left(a + b\right)} - 1\right)}{\left(e^{\varepsilon \cdot a} - 1\right) \cdot \left(e^{\varepsilon \cdot b} - 1\right)} \leq 0.0017847522660158154:\\ \;\;\;\;\frac{\frac{\varepsilon}{\mathsf{expm1}\left(\varepsilon \cdot a\right)} \cdot \mathsf{expm1}\left(\varepsilon \cdot \left(a + b\right)\right)}{\mathsf{expm1}\left(\varepsilon \cdot b\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{b} + \mathsf{fma}\left(b \cdot \left(\varepsilon \cdot \varepsilon\right), 0.08333333333333333, \frac{1}{a}\right)\\ \end{array} \]

Reproduce

herbie shell --seed 2021215 
(FPCore (a b eps)
  :name "expq3 (problem 3.4.2)"
  :precision binary64
  :pre (and (< -1.0 eps) (< eps 1.0))

  :herbie-target
  (/ (+ a b) (* a b))

  (/ (* eps (- (exp (* (+ a b) eps)) 1.0)) (* (- (exp (* a eps)) 1.0) (- (exp (* b eps)) 1.0))))