?

Average Accuracy: 49.4% → 99.6%
Time: 4.2s
Precision: binary64
Cost: 6848

?

\[\log \left(x + \sqrt{x \cdot x - 1}\right) \]
\[\log \left(x + \left(x - \frac{0.5}{x}\right)\right) \]
(FPCore (x) :precision binary64 (log (+ x (sqrt (- (* x x) 1.0)))))
(FPCore (x) :precision binary64 (log (+ x (- x (/ 0.5 x)))))
double code(double x) {
	return log((x + sqrt(((x * x) - 1.0))));
}
double code(double x) {
	return log((x + (x - (0.5 / x))));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = log((x + sqrt(((x * x) - 1.0d0))))
end function
real(8) function code(x)
    real(8), intent (in) :: x
    code = log((x + (x - (0.5d0 / x))))
end function
public static double code(double x) {
	return Math.log((x + Math.sqrt(((x * x) - 1.0))));
}
public static double code(double x) {
	return Math.log((x + (x - (0.5 / x))));
}
def code(x):
	return math.log((x + math.sqrt(((x * x) - 1.0))))
def code(x):
	return math.log((x + (x - (0.5 / x))))
function code(x)
	return log(Float64(x + sqrt(Float64(Float64(x * x) - 1.0))))
end
function code(x)
	return log(Float64(x + Float64(x - Float64(0.5 / x))))
end
function tmp = code(x)
	tmp = log((x + sqrt(((x * x) - 1.0))));
end
function tmp = code(x)
	tmp = log((x + (x - (0.5 / x))));
end
code[x_] := N[Log[N[(x + N[Sqrt[N[(N[(x * x), $MachinePrecision] - 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
code[x_] := N[Log[N[(x + N[(x - N[(0.5 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\log \left(x + \sqrt{x \cdot x - 1}\right)
\log \left(x + \left(x - \frac{0.5}{x}\right)\right)

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 49.4%

    \[\log \left(x + \sqrt{x \cdot x - 1}\right) \]
  2. Taylor expanded in x around inf 99.6%

    \[\leadsto \log \left(x + \color{blue}{\left(x - 0.5 \cdot \frac{1}{x}\right)}\right) \]
  3. Simplified99.6%

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

    [Start]99.6

    \[ \log \left(x + \left(x - 0.5 \cdot \frac{1}{x}\right)\right) \]

    associate-*r/ [=>]99.6

    \[ \log \left(x + \left(x - \color{blue}{\frac{0.5 \cdot 1}{x}}\right)\right) \]

    metadata-eval [=>]99.6

    \[ \log \left(x + \left(x - \frac{\color{blue}{0.5}}{x}\right)\right) \]
  4. Final simplification99.6%

    \[\leadsto \log \left(x + \left(x - \frac{0.5}{x}\right)\right) \]

Alternatives

Alternative 1
Accuracy99.1%
Cost6592
\[\log \left(x + x\right) \]
Alternative 2
Accuracy3.1%
Cost64
\[0 \]

Error

Reproduce?

herbie shell --seed 2023146 
(FPCore (x)
  :name "Hyperbolic arc-cosine"
  :precision binary64
  (log (+ x (sqrt (- (* x x) 1.0)))))