Hyperbolic arcsine

Average Error: 52.7 → 0.6

Time: 5.4s

Precision: binary64

Math

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

↓

\[\begin{array}{l} \mathbf{if}\;x \leq -6841338.693141433:\\ \;\;\;\;\log \left(\frac{0.125}{{x}^{3}} + \frac{-0.5}{x}\right)\\ \mathbf{elif}\;x \leq 2.7824422181283067 \cdot 10^{-14}:\\ \;\;\;\;\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, 0.075 \cdot {x}^{5}\right) + \mathsf{fma}\left(-0.044642857142857144, {x}^{7}, x\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(x + \mathsf{hypot}\left(1, x\right)\right)\\ \end{array} \]

FPCore

(FPCore (x) :precision binary64 (log (+ x (sqrt (+ (* x x) 1.0)))))

↓

(FPCore (x)
 :precision binary64
 (if (<= x -6841338.693141433)
   (log (+ (/ 0.125 (pow x 3.0)) (/ -0.5 x)))
   (if (<= x 2.7824422181283067e-14)
     (+
      (fma -0.16666666666666666 (pow x 3.0) (* 0.075 (pow x 5.0)))
      (fma -0.044642857142857144 (pow x 7.0) x))
     (log (+ x (hypot 1.0 x))))))

C

double code(double x) {
	return log((x + sqrt(((x * x) + 1.0))));
}

↓

double code(double x) {
	double tmp;
	if (x <= -6841338.693141433) {
		tmp = log(((0.125 / pow(x, 3.0)) + (-0.5 / x)));
	} else if (x <= 2.7824422181283067e-14) {
		tmp = fma(-0.16666666666666666, pow(x, 3.0), (0.075 * pow(x, 5.0))) + fma(-0.044642857142857144, pow(x, 7.0), x);
	} else {
		tmp = log((x + hypot(1.0, x)));
	}
	return tmp;
}

Julia

function code(x)
	return log(Float64(x + sqrt(Float64(Float64(x * x) + 1.0))))
end

↓

function code(x)
	tmp = 0.0
	if (x <= -6841338.693141433)
		tmp = log(Float64(Float64(0.125 / (x ^ 3.0)) + Float64(-0.5 / x)));
	elseif (x <= 2.7824422181283067e-14)
		tmp = Float64(fma(-0.16666666666666666, (x ^ 3.0), Float64(0.075 * (x ^ 5.0))) + fma(-0.044642857142857144, (x ^ 7.0), x));
	else
		tmp = log(Float64(x + hypot(1.0, x)));
	end
	return tmp
end

Wolfram

code[x_] := N[Log[N[(x + N[Sqrt[N[(N[(x * x), $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

↓

code[x_] := If[LessEqual[x, -6841338.693141433], N[Log[N[(N[(0.125 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[(-0.5 / x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], If[LessEqual[x, 2.7824422181283067e-14], N[(N[(-0.16666666666666666 * N[Power[x, 3.0], $MachinePrecision] + N[(0.075 * N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.044642857142857144 * N[Power[x, 7.0], $MachinePrecision] + x), $MachinePrecision]), $MachinePrecision], N[Log[N[(x + N[Sqrt[1.0 ^ 2 + x ^ 2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]]

Target

Original	52.7
Target	45.2
Herbie	0.6

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

Derivation

1. Split input into 3 regimes

2. if x < -6841338.69314143341

   1. Initial program 63.9

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

   2. Simplified 63.9

      \[\leadsto \color{blue}{\log \left(x + \mathsf{hypot}\left(1, x\right)\right)} \]

   3. Taylor expanded in x around -inf 0.0

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

   4. Simplified 0.0

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

   if -6841338.69314143341 < x < 2.78244221812830671e-14

   1. Initial program 58.9

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

   2. Simplified 58.9

      \[\leadsto \color{blue}{\log \left(x + \mathsf{hypot}\left(1, x\right)\right)} \]

   3. Taylor expanded in x around 0 0.8

      \[\leadsto \color{blue}{-0.16666666666666666 \cdot {x}^{3} + \left(0.075 \cdot {x}^{5} + \left(-0.044642857142857144 \cdot {x}^{7} + x\right)\right)} \]

   4. Simplified 0.8

      \[\leadsto \color{blue}{\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, \mathsf{fma}\left(0.075, {x}^{5}, \mathsf{fma}\left(-0.044642857142857144, {x}^{7}, x\right)\right)\right)} \]

   5. Applied egg-rr 0.8

      \[\leadsto \color{blue}{\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, 0.075 \cdot {x}^{5}\right) + \mathsf{fma}\left(-0.044642857142857144, {x}^{7}, x\right)} \]

   if 2.78244221812830671e-14 < x

   1. Initial program 30.4

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

   2. Simplified 0.8

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

4. Final simplification 0.6

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -6841338.693141433:\\ \;\;\;\;\log \left(\frac{0.125}{{x}^{3}} + \frac{-0.5}{x}\right)\\ \mathbf{elif}\;x \leq 2.7824422181283067 \cdot 10^{-14}:\\ \;\;\;\;\mathsf{fma}\left(-0.16666666666666666, {x}^{3}, 0.075 \cdot {x}^{5}\right) + \mathsf{fma}\left(-0.044642857142857144, {x}^{7}, x\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(x + \mathsf{hypot}\left(1, x\right)\right)\\ \end{array} \]

Reproduce

herbie shell --seed 2022210 
(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)))))