Average Error: 53.2 → 0.1
Time: 4.5s
Precision: binary64
\[\log \left(x + \sqrt{x \cdot x + 1}\right) \]
\[\begin{array}{l} \mathbf{if}\;x \leq -1.1:\\ \;\;\;\;\log \left(\mathsf{fma}\left(0.125, {x}^{-3}, \frac{-0.5}{x}\right)\right)\\ \mathbf{elif}\;x \leq 0.0075:\\ \;\;\;\;\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, \mathsf{fma}\left(0.075, {x}^{5}, x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(x + \mathsf{hypot}\left(1, x\right)\right)\\ \end{array} \]
(FPCore (x) :precision binary64 (log (+ x (sqrt (+ (* x x) 1.0)))))
(FPCore (x)
 :precision binary64
 (if (<= x -1.1)
   (log (fma 0.125 (pow x -3.0) (/ -0.5 x)))
   (if (<= x 0.0075)
     (fma -0.16666666666666666 (pow x 3.0) (fma 0.075 (pow x 5.0) x))
     (log (+ x (hypot 1.0 x))))))
double code(double x) {
	return log((x + sqrt(((x * x) + 1.0))));
}
double code(double x) {
	double tmp;
	if (x <= -1.1) {
		tmp = log(fma(0.125, pow(x, -3.0), (-0.5 / x)));
	} else if (x <= 0.0075) {
		tmp = fma(-0.16666666666666666, pow(x, 3.0), fma(0.075, pow(x, 5.0), x));
	} else {
		tmp = log((x + hypot(1.0, x)));
	}
	return tmp;
}
function code(x)
	return log(Float64(x + sqrt(Float64(Float64(x * x) + 1.0))))
end
function code(x)
	tmp = 0.0
	if (x <= -1.1)
		tmp = log(fma(0.125, (x ^ -3.0), Float64(-0.5 / x)));
	elseif (x <= 0.0075)
		tmp = fma(-0.16666666666666666, (x ^ 3.0), fma(0.075, (x ^ 5.0), x));
	else
		tmp = log(Float64(x + hypot(1.0, x)));
	end
	return tmp
end
code[x_] := N[Log[N[(x + N[Sqrt[N[(N[(x * x), $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
code[x_] := If[LessEqual[x, -1.1], N[Log[N[(0.125 * N[Power[x, -3.0], $MachinePrecision] + N[(-0.5 / x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], If[LessEqual[x, 0.0075], N[(-0.16666666666666666 * N[Power[x, 3.0], $MachinePrecision] + N[(0.075 * N[Power[x, 5.0], $MachinePrecision] + x), $MachinePrecision]), $MachinePrecision], N[Log[N[(x + N[Sqrt[1.0 ^ 2 + x ^ 2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]
\log \left(x + \sqrt{x \cdot x + 1}\right)
\begin{array}{l}
\mathbf{if}\;x \leq -1.1:\\
\;\;\;\;\log \left(\mathsf{fma}\left(0.125, {x}^{-3}, \frac{-0.5}{x}\right)\right)\\

\mathbf{elif}\;x \leq 0.0075:\\
\;\;\;\;\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, \mathsf{fma}\left(0.075, {x}^{5}, x\right)\right)\\

\mathbf{else}:\\
\;\;\;\;\log \left(x + \mathsf{hypot}\left(1, x\right)\right)\\


\end{array}

Error

Target

Original53.2
Target45.3
Herbie0.1
\[\begin{array}{l} \mathbf{if}\;x < 0:\\ \;\;\;\;\log \left(\frac{-1}{x - \sqrt{x \cdot x + 1}}\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(x + \sqrt{x \cdot x + 1}\right)\\ \end{array} \]

Derivation

  1. Split input into 3 regimes
  2. if x < -1.1000000000000001

    1. Initial program 62.8

      \[\log \left(x + \sqrt{x \cdot x + 1}\right) \]
    2. Simplified62.8

      \[\leadsto \color{blue}{\log \left(x + \mathsf{hypot}\left(1, x\right)\right)} \]
    3. Taylor expanded in x around -inf 0.3

      \[\leadsto \log \color{blue}{\left(0.125 \cdot \frac{1}{{x}^{3}} - 0.5 \cdot \frac{1}{x}\right)} \]
    4. Simplified0.3

      \[\leadsto \log \color{blue}{\left(\frac{0.125}{{x}^{3}} + \frac{-0.5}{x}\right)} \]
    5. Applied egg-rr0.3

      \[\leadsto \log \color{blue}{\left(\mathsf{fma}\left(0.125, {x}^{-3}, \frac{-0.5}{x}\right)\right)} \]

    if -1.1000000000000001 < x < 0.0074999999999999997

    1. Initial program 59.1

      \[\log \left(x + \sqrt{x \cdot x + 1}\right) \]
    2. Simplified59.1

      \[\leadsto \color{blue}{\log \left(x + \mathsf{hypot}\left(1, x\right)\right)} \]
    3. Taylor expanded in x around 0 0.1

      \[\leadsto \color{blue}{-0.16666666666666666 \cdot {x}^{3} + \left(0.075 \cdot {x}^{5} + x\right)} \]
    4. Simplified0.1

      \[\leadsto \color{blue}{\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, \mathsf{fma}\left(0.075, {x}^{5}, x\right)\right)} \]

    if 0.0074999999999999997 < x

    1. Initial program 32.2

      \[\log \left(x + \sqrt{x \cdot x + 1}\right) \]
    2. Simplified0.1

      \[\leadsto \color{blue}{\log \left(x + \mathsf{hypot}\left(1, x\right)\right)} \]
  3. Recombined 3 regimes into one program.
  4. Final simplification0.1

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.1:\\ \;\;\;\;\log \left(\mathsf{fma}\left(0.125, {x}^{-3}, \frac{-0.5}{x}\right)\right)\\ \mathbf{elif}\;x \leq 0.0075:\\ \;\;\;\;\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, \mathsf{fma}\left(0.075, {x}^{5}, x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(x + \mathsf{hypot}\left(1, x\right)\right)\\ \end{array} \]

Reproduce

herbie shell --seed 2022181 
(FPCore (x)
  :name "Hyperbolic arcsine"
  :precision binary64

  :herbie-target
  (if (< x 0.0) (log (/ -1.0 (- x (sqrt (+ (* x x) 1.0))))) (log (+ x (sqrt (+ (* x x) 1.0)))))

  (log (+ x (sqrt (+ (* x x) 1.0)))))