?

Average Error: 15.8 → 0.6
Time: 8.9s
Precision: binary32
Cost: 6688

?

\[x \geq 1\]
\[\log \left(x + \sqrt{x \cdot x - 1}\right) \]
\[\log 2 + \left(\log x + \frac{-0.25}{x \cdot x}\right) \]
(FPCore (x) :precision binary32 (log (+ x (sqrt (- (* x x) 1.0)))))
(FPCore (x) :precision binary32 (+ (log 2.0) (+ (log x) (/ -0.25 (* x x)))))
float code(float x) {
	return logf((x + sqrtf(((x * x) - 1.0f))));
}
float code(float x) {
	return logf(2.0f) + (logf(x) + (-0.25f / (x * x)));
}
real(4) function code(x)
    real(4), intent (in) :: x
    code = log((x + sqrt(((x * x) - 1.0e0))))
end function
real(4) function code(x)
    real(4), intent (in) :: x
    code = log(2.0e0) + (log(x) + ((-0.25e0) / (x * x)))
end function
function code(x)
	return log(Float32(x + sqrt(Float32(Float32(x * x) - Float32(1.0)))))
end
function code(x)
	return Float32(log(Float32(2.0)) + Float32(log(x) + Float32(Float32(-0.25) / Float32(x * x))))
end
function tmp = code(x)
	tmp = log((x + sqrt(((x * x) - single(1.0)))));
end
function tmp = code(x)
	tmp = log(single(2.0)) + (log(x) + (single(-0.25) / (x * x)));
end
\log \left(x + \sqrt{x \cdot x - 1}\right)
\log 2 + \left(\log x + \frac{-0.25}{x \cdot x}\right)

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original15.8
Target0.2
Herbie0.6
\[\log \left(x + \sqrt{x - 1} \cdot \sqrt{x + 1}\right) \]

Derivation?

  1. Initial program 15.8

    \[\log \left(x + \sqrt{x \cdot x - 1}\right) \]
  2. Taylor expanded in x around inf 0.6

    \[\leadsto \color{blue}{\left(-1 \cdot \log \left(\frac{1}{x}\right) + \log 2\right) - 0.25 \cdot \frac{1}{{x}^{2}}} \]
  3. Simplified0.6

    \[\leadsto \color{blue}{\log 2 + \left(\log x + \frac{-0.25}{x \cdot x}\right)} \]
    Proof

    [Start]0.6

    \[ \left(-1 \cdot \log \left(\frac{1}{x}\right) + \log 2\right) - 0.25 \cdot \frac{1}{{x}^{2}} \]

    cancel-sign-sub-inv [=>]0.6

    \[ \color{blue}{\left(-1 \cdot \log \left(\frac{1}{x}\right) + \log 2\right) + \left(-0.25\right) \cdot \frac{1}{{x}^{2}}} \]

    +-commutative [=>]0.6

    \[ \color{blue}{\left(\log 2 + -1 \cdot \log \left(\frac{1}{x}\right)\right)} + \left(-0.25\right) \cdot \frac{1}{{x}^{2}} \]

    associate-+l+ [=>]0.6

    \[ \color{blue}{\log 2 + \left(-1 \cdot \log \left(\frac{1}{x}\right) + \left(-0.25\right) \cdot \frac{1}{{x}^{2}}\right)} \]

    mul-1-neg [=>]0.6

    \[ \log 2 + \left(\color{blue}{\left(-\log \left(\frac{1}{x}\right)\right)} + \left(-0.25\right) \cdot \frac{1}{{x}^{2}}\right) \]

    log-rec [=>]0.6

    \[ \log 2 + \left(\left(-\color{blue}{\left(-\log x\right)}\right) + \left(-0.25\right) \cdot \frac{1}{{x}^{2}}\right) \]

    remove-double-neg [=>]0.6

    \[ \log 2 + \left(\color{blue}{\log x} + \left(-0.25\right) \cdot \frac{1}{{x}^{2}}\right) \]

    unpow2 [=>]0.6

    \[ \log 2 + \left(\log x + \left(-0.25\right) \cdot \frac{1}{\color{blue}{x \cdot x}}\right) \]

    associate-*r/ [=>]0.6

    \[ \log 2 + \left(\log x + \color{blue}{\frac{\left(-0.25\right) \cdot 1}{x \cdot x}}\right) \]

    metadata-eval [=>]0.6

    \[ \log 2 + \left(\log x + \frac{\color{blue}{-0.25} \cdot 1}{x \cdot x}\right) \]

    metadata-eval [=>]0.6

    \[ \log 2 + \left(\log x + \frac{\color{blue}{-0.25}}{x \cdot x}\right) \]
  4. Final simplification0.6

    \[\leadsto \log 2 + \left(\log x + \frac{-0.25}{x \cdot x}\right) \]

Alternatives

Alternative 1
Error0.5
Cost3808
\[\log \left(\left(\frac{-0.5}{x} + \frac{-0.25}{\left(x \cdot x\right) \cdot \left(x + \frac{0.5}{x}\right)}\right) + 2 \cdot x\right) \]
Alternative 2
Error0.5
Cost3424
\[\log \left(x + \left(x + \frac{-0.5}{x}\right)\right) \]
Alternative 3
Error0.9
Cost3296
\[\log \left(x + x\right) \]
Alternative 4
Error24.2
Cost3232
\[\mathsf{expm1}\left(1.9453125\right) \]
Alternative 5
Error24.2
Cost3232
\[\mathsf{expm1}\left(1.9583333333333333\right) \]
Alternative 6
Error17.9
Cost3232
\[\log x \]
Alternative 7
Error30.0
Cost32
\[0 \]

Error

Reproduce?

herbie shell --seed 2023039 
(FPCore (x)
  :name "Rust f32::acosh"
  :precision binary32
  :pre (>= x 1.0)

  :herbie-target
  (log (+ x (* (sqrt (- x 1.0)) (sqrt (+ x 1.0)))))

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