math.sqrt on complex, imaginary part, im greater than 0 branch

Average Error: 39.2 → 6.7

Time: 10.3s

Precision: binary64

Cost: 27400

\[im > 0\]

Math

\[0.5 \cdot \sqrt{2 \cdot \left(\sqrt{re \cdot re + im \cdot im} - re\right)} \]

↓

\[\begin{array}{l} t_0 := \sqrt{re \cdot re + im \cdot im} - re\\ t_1 := 0.5 \cdot \sqrt{2 \cdot \left(\mathsf{hypot}\left(re, im\right) - re\right)}\\ \mathbf{if}\;t_0 \leq -1 \cdot 10^{-308}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_0 \leq 0:\\ \;\;\;\;{re}^{-0.5} \cdot \left(im \cdot 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

FPCore

(FPCore (re im)
 :precision binary64
 (* 0.5 (sqrt (* 2.0 (- (sqrt (+ (* re re) (* im im))) re)))))

↓

(FPCore (re im)
 :precision binary64
 (let* ((t_0 (- (sqrt (+ (* re re) (* im im))) re))
        (t_1 (* 0.5 (sqrt (* 2.0 (- (hypot re im) re))))))
   (if (<= t_0 -1e-308)
     t_1
     (if (<= t_0 0.0) (* (pow re -0.5) (* im 0.5)) t_1))))

C

double code(double re, double im) {
	return 0.5 * sqrt((2.0 * (sqrt(((re * re) + (im * im))) - re)));
}

↓

double code(double re, double im) {
	double t_0 = sqrt(((re * re) + (im * im))) - re;
	double t_1 = 0.5 * sqrt((2.0 * (hypot(re, im) - re)));
	double tmp;
	if (t_0 <= -1e-308) {
		tmp = t_1;
	} else if (t_0 <= 0.0) {
		tmp = pow(re, -0.5) * (im * 0.5);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Java

public static double code(double re, double im) {
	return 0.5 * Math.sqrt((2.0 * (Math.sqrt(((re * re) + (im * im))) - re)));
}

↓

public static double code(double re, double im) {
	double t_0 = Math.sqrt(((re * re) + (im * im))) - re;
	double t_1 = 0.5 * Math.sqrt((2.0 * (Math.hypot(re, im) - re)));
	double tmp;
	if (t_0 <= -1e-308) {
		tmp = t_1;
	} else if (t_0 <= 0.0) {
		tmp = Math.pow(re, -0.5) * (im * 0.5);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(re, im):
	return 0.5 * math.sqrt((2.0 * (math.sqrt(((re * re) + (im * im))) - re)))

↓

def code(re, im):
	t_0 = math.sqrt(((re * re) + (im * im))) - re
	t_1 = 0.5 * math.sqrt((2.0 * (math.hypot(re, im) - re)))
	tmp = 0
	if t_0 <= -1e-308:
		tmp = t_1
	elif t_0 <= 0.0:
		tmp = math.pow(re, -0.5) * (im * 0.5)
	else:
		tmp = t_1
	return tmp

Julia

function code(re, im)
	return Float64(0.5 * sqrt(Float64(2.0 * Float64(sqrt(Float64(Float64(re * re) + Float64(im * im))) - re))))
end

↓

function code(re, im)
	t_0 = Float64(sqrt(Float64(Float64(re * re) + Float64(im * im))) - re)
	t_1 = Float64(0.5 * sqrt(Float64(2.0 * Float64(hypot(re, im) - re))))
	tmp = 0.0
	if (t_0 <= -1e-308)
		tmp = t_1;
	elseif (t_0 <= 0.0)
		tmp = Float64((re ^ -0.5) * Float64(im * 0.5));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp = code(re, im)
	tmp = 0.5 * sqrt((2.0 * (sqrt(((re * re) + (im * im))) - re)));
end

↓

function tmp_2 = code(re, im)
	t_0 = sqrt(((re * re) + (im * im))) - re;
	t_1 = 0.5 * sqrt((2.0 * (hypot(re, im) - re)));
	tmp = 0.0;
	if (t_0 <= -1e-308)
		tmp = t_1;
	elseif (t_0 <= 0.0)
		tmp = (re ^ -0.5) * (im * 0.5);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[re_, im_] := N[(0.5 * N[Sqrt[N[(2.0 * N[(N[Sqrt[N[(N[(re * re), $MachinePrecision] + N[(im * im), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - re), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

↓

code[re_, im_] := Block[{t$95$0 = N[(N[Sqrt[N[(N[(re * re), $MachinePrecision] + N[(im * im), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - re), $MachinePrecision]}, Block[{t$95$1 = N[(0.5 * N[Sqrt[N[(2.0 * N[(N[Sqrt[re ^ 2 + im ^ 2], $MachinePrecision] - re), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -1e-308], t$95$1, If[LessEqual[t$95$0, 0.0], N[(N[Power[re, -0.5], $MachinePrecision] * N[(im * 0.5), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 2 regimes

2. if (-.f64 (sqrt.f64 (+.f64 (*.f64 re re) (*.f64 im im))) re) < -9.9999999999999991e-309 or 0.0 < (-.f64 (sqrt.f64 (+.f64 (*.f64 re re) (*.f64 im im))) re)

   1. Initial program 36.7

      \[0.5 \cdot \sqrt{2 \cdot \left(\sqrt{re \cdot re + im \cdot im} - re\right)} \]

   2. Simplified 7.6

      \[\leadsto \color{blue}{0.5 \cdot \sqrt{2 \cdot \left(\mathsf{hypot}\left(re, im\right) - re\right)}} \]
      Proof
      (*.f64 1/2 (sqrt.f64 (*.f64 2 (-.f64 (hypot.f64 re im) re)))): 0 points increase in error, 0 points decrease in error
      (*.f64 1/2 (sqrt.f64 (*.f64 2 (-.f64 (Rewrite<= hypot-def_binary64 (sqrt.f64 (+.f64 (*.f64 re re) (*.f64 im im)))) re)))): 125 points increase in error, 0 points decrease in error

   if -9.9999999999999991e-309 < (-.f64 (sqrt.f64 (+.f64 (*.f64 re re) (*.f64 im im))) re) < 0.0

   1. Initial program 56.7

      \[0.5 \cdot \sqrt{2 \cdot \left(\sqrt{re \cdot re + im \cdot im} - re\right)} \]

   2. Simplified 56.7

      \[\leadsto \color{blue}{0.5 \cdot \sqrt{2 \cdot \left(\mathsf{hypot}\left(re, im\right) - re\right)}} \]
      Proof
      (*.f64 1/2 (sqrt.f64 (*.f64 2 (-.f64 (hypot.f64 re im) re)))): 0 points increase in error, 0 points decrease in error
      (*.f64 1/2 (sqrt.f64 (*.f64 2 (-.f64 (Rewrite<= hypot-def_binary64 (sqrt.f64 (+.f64 (*.f64 re re) (*.f64 im im)))) re)))): 125 points increase in error, 0 points decrease in error

   3. Taylor expanded in re around inf 30.3

      \[\leadsto 0.5 \cdot \sqrt{2 \cdot \color{blue}{\left(0.5 \cdot \frac{{im}^{2}}{re}\right)}} \]

   4. Taylor expanded in im around 0 0.3

      \[\leadsto \color{blue}{0.5 \cdot \left(\sqrt{\frac{1}{re}} \cdot im\right)} \]

   5. Simplified 0.3

      \[\leadsto \color{blue}{\sqrt{\frac{1}{re}} \cdot \left(im \cdot 0.5\right)} \]
      Proof
      (*.f64 (sqrt.f64 (/.f64 1 re)) (*.f64 im 1/2)): 0 points increase in error, 0 points decrease in error
      (Rewrite<= associate-*l*_binary64 (*.f64 (*.f64 (sqrt.f64 (/.f64 1 re)) im) 1/2)): 1 points increase in error, 0 points decrease in error
      (Rewrite<= *-commutative_binary64 (*.f64 1/2 (*.f64 (sqrt.f64 (/.f64 1 re)) im))): 0 points increase in error, 0 points decrease in error

   6. Applied egg-rr 0.3

      \[\leadsto \color{blue}{{re}^{-0.5}} \cdot \left(im \cdot 0.5\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 6.7

   \[\leadsto \begin{array}{l} \mathbf{if}\;\sqrt{re \cdot re + im \cdot im} - re \leq -1 \cdot 10^{-308}:\\ \;\;\;\;0.5 \cdot \sqrt{2 \cdot \left(\mathsf{hypot}\left(re, im\right) - re\right)}\\ \mathbf{elif}\;\sqrt{re \cdot re + im \cdot im} - re \leq 0:\\ \;\;\;\;{re}^{-0.5} \cdot \left(im \cdot 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \sqrt{2 \cdot \left(\mathsf{hypot}\left(re, im\right) - re\right)}\\ \end{array} \]

Alternatives

Alternative 1
Error	15.5
Cost	7632

\[\begin{array}{l} t_0 := \sqrt{2 \cdot \left(im - re\right)}\\ \mathbf{if}\;re \leq -2.5243801377203508 \cdot 10^{+35}:\\ \;\;\;\;0.5 \cdot \sqrt{2 \cdot \left(re \cdot -2\right)}\\ \mathbf{elif}\;re \leq 2.672776537165513 \cdot 10^{-52}:\\ \;\;\;\;0.5 \cdot t_0\\ \mathbf{elif}\;re \leq 8.168045795003346 \cdot 10^{-29}:\\ \;\;\;\;\frac{0.5}{\frac{\sqrt{re}}{im}}\\ \mathbf{elif}\;re \leq 7.108154288195874 \cdot 10^{+53}:\\ \;\;\;\;0.5 \cdot \left(\left(t_0 + 1\right) + -1\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{im \cdot 0.5}{\sqrt{re}}\\ \end{array} \]

Alternative 2
Error	15.5
Cost	7376

\[\begin{array}{l} t_0 := 0.5 \cdot \sqrt{2 \cdot \left(im - re\right)}\\ \mathbf{if}\;re \leq -2.5243801377203508 \cdot 10^{+35}:\\ \;\;\;\;0.5 \cdot \sqrt{2 \cdot \left(re \cdot -2\right)}\\ \mathbf{elif}\;re \leq 2.672776537165513 \cdot 10^{-52}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;re \leq 8.168045795003346 \cdot 10^{-29}:\\ \;\;\;\;\frac{0.5}{\frac{\sqrt{re}}{im}}\\ \mathbf{elif}\;re \leq 7.108154288195874 \cdot 10^{+53}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;\frac{im \cdot 0.5}{\sqrt{re}}\\ \end{array} \]

Alternative 3
Error	15.7
Cost	6984

\[\begin{array}{l} \mathbf{if}\;re \leq -2.5243801377203508 \cdot 10^{+35}:\\ \;\;\;\;0.5 \cdot \sqrt{2 \cdot \left(re \cdot -2\right)}\\ \mathbf{elif}\;re \leq 7.108154288195874 \cdot 10^{+53}:\\ \;\;\;\;0.5 \cdot \sqrt{im \cdot 2}\\ \mathbf{else}:\\ \;\;\;\;\frac{im \cdot 0.5}{\sqrt{re}}\\ \end{array} \]

Alternative 4
Error	23.0
Cost	6852

\[\begin{array}{l} \mathbf{if}\;re \leq 7.108154288195874 \cdot 10^{+53}:\\ \;\;\;\;0.5 \cdot \sqrt{im \cdot 2}\\ \mathbf{else}:\\ \;\;\;\;\frac{im \cdot 0.5}{\sqrt{re}}\\ \end{array} \]

Alternative 5
Error	46.7
Cost	6720

\[im \cdot \frac{0.5}{\sqrt{re}} \]

Alternative 6
Error	46.6
Cost	6720

\[\frac{im \cdot 0.5}{\sqrt{re}} \]

Reproduce

herbie shell --seed 2022313 
(FPCore (re im)
  :name "math.sqrt on complex, imaginary part, im greater than 0 branch"
  :precision binary64
  :pre (> im 0.0)
  (* 0.5 (sqrt (* 2.0 (- (sqrt (+ (* re re) (* im im))) re)))))