Migdal et al, Equation (64)

Percentage Accurate: 99.5% → 99.6%

Time: 7.6s

Alternatives: 11

Speedup: 2.0×

• 44.4% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{\cos th}{\sqrt{2}}\\ t\_1 \cdot \left(a1 \cdot a1\right) + t\_1 \cdot \left(a2 \cdot a2\right) \end{array} \end{array} \]

FPCore

(FPCore (a1 a2 th)
 :precision binary64
 (let* ((t_1 (/ (cos th) (sqrt 2.0))))
   (+ (* t_1 (* a1 a1)) (* t_1 (* a2 a2)))))

C

double code(double a1, double a2, double th) {
	double t_1 = cos(th) / sqrt(2.0);
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
}

Fortran

real(8) function code(a1, a2, th)
    real(8), intent (in) :: a1
    real(8), intent (in) :: a2
    real(8), intent (in) :: th
    real(8) :: t_1
    t_1 = cos(th) / sqrt(2.0d0)
    code = (t_1 * (a1 * a1)) + (t_1 * (a2 * a2))
end function

Java

public static double code(double a1, double a2, double th) {
	double t_1 = Math.cos(th) / Math.sqrt(2.0);
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
}

Python

def code(a1, a2, th):
	t_1 = math.cos(th) / math.sqrt(2.0)
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2))

Julia

function code(a1, a2, th)
	t_1 = Float64(cos(th) / sqrt(2.0))
	return Float64(Float64(t_1 * Float64(a1 * a1)) + Float64(t_1 * Float64(a2 * a2)))
end

MATLAB

function tmp = code(a1, a2, th)
	t_1 = cos(th) / sqrt(2.0);
	tmp = (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
end

Wolfram

code[a1_, a2_, th_] := Block[{t$95$1 = N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[(t$95$1 * N[(a1 * a1), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(a2 * a2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Initial Program: 99.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{\cos th}{\sqrt{2}}\\ t\_1 \cdot \left(a1 \cdot a1\right) + t\_1 \cdot \left(a2 \cdot a2\right) \end{array} \end{array} \]

FPCore

(FPCore (a1 a2 th)
 :precision binary64
 (let* ((t_1 (/ (cos th) (sqrt 2.0))))
   (+ (* t_1 (* a1 a1)) (* t_1 (* a2 a2)))))

C

double code(double a1, double a2, double th) {
	double t_1 = cos(th) / sqrt(2.0);
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
}

Fortran

real(8) function code(a1, a2, th)
    real(8), intent (in) :: a1
    real(8), intent (in) :: a2
    real(8), intent (in) :: th
    real(8) :: t_1
    t_1 = cos(th) / sqrt(2.0d0)
    code = (t_1 * (a1 * a1)) + (t_1 * (a2 * a2))
end function

Java

public static double code(double a1, double a2, double th) {
	double t_1 = Math.cos(th) / Math.sqrt(2.0);
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
}

Python

def code(a1, a2, th):
	t_1 = math.cos(th) / math.sqrt(2.0)
	return (t_1 * (a1 * a1)) + (t_1 * (a2 * a2))

Julia

function code(a1, a2, th)
	t_1 = Float64(cos(th) / sqrt(2.0))
	return Float64(Float64(t_1 * Float64(a1 * a1)) + Float64(t_1 * Float64(a2 * a2)))
end

MATLAB

function tmp = code(a1, a2, th)
	t_1 = cos(th) / sqrt(2.0);
	tmp = (t_1 * (a1 * a1)) + (t_1 * (a2 * a2));
end

Wolfram

code[a1_, a2_, th_] := Block[{t$95$1 = N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[(t$95$1 * N[(a1 * a1), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(a2 * a2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Alternative 1: 99.6% accurate, 1.0× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1\_m \cdot a1\_m, \left(\frac{a2\_m}{\sqrt{2}} \cdot a2\_m\right) \cdot \cos th\right) \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (fma
  (/ (cos th) (sqrt 2.0))
  (* a1_m a1_m)
  (* (* (/ a2_m (sqrt 2.0)) a2_m) (cos th))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return fma((cos(th) / sqrt(2.0)), (a1_m * a1_m), (((a2_m / sqrt(2.0)) * a2_m) * cos(th)));
}

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return fma(Float64(cos(th) / sqrt(2.0)), Float64(a1_m * a1_m), Float64(Float64(Float64(a2_m / sqrt(2.0)) * a2_m) * cos(th)))
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * N[(a1$95$m * a1$95$m), $MachinePrecision] + N[(N[(N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * a2$95$m), $MachinePrecision] * N[Cos[th], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift-+.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

   3. lower-fma.f64 99.2

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)\right)} \]

   4. lift-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)}\right) \]

   5. lift-/.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a2 \cdot a2\right)\right) \]

   6. associate-*l/ N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\frac{\cos th \cdot \left(a2 \cdot a2\right)}{\sqrt{2}}}\right) \]

   7. associate-/l* N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\cos th \cdot \frac{a2 \cdot a2}{\sqrt{2}}}\right) \]

   8. *-commutative N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\frac{a2 \cdot a2}{\sqrt{2}} \cdot \cos th}\right) \]

   9. lower-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\frac{a2 \cdot a2}{\sqrt{2}} \cdot \cos th}\right) \]

   10. *-lft-identity N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \frac{\color{blue}{1 \cdot \left(a2 \cdot a2\right)}}{\sqrt{2}} \cdot \cos th\right) \]

   11. associate-*l/ N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)\right)} \cdot \cos th\right) \]

   12. lift-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \left(\frac{1}{\sqrt{2}} \cdot \color{blue}{\left(a2 \cdot a2\right)}\right) \cdot \cos th\right) \]

   13. associate-*r* N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\left(\left(\frac{1}{\sqrt{2}} \cdot a2\right) \cdot a2\right)} \cdot \cos th\right) \]

   14. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \color{blue}{\left(\left(\frac{1}{\sqrt{2}} \cdot a2\right) \cdot a2\right)} \cdot \cos th\right) \]

   15. associate-*l/ N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \left(\color{blue}{\frac{1 \cdot a2}{\sqrt{2}}} \cdot a2\right) \cdot \cos th\right) \]

   16. *-lft-identity N/A

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \left(\frac{\color{blue}{a2}}{\sqrt{2}} \cdot a2\right) \cdot \cos th\right) \]

   17. lower-/.f64 99.3

       \[\leadsto \mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \left(\color{blue}{\frac{a2}{\sqrt{2}}} \cdot a2\right) \cdot \cos th\right) \]

4. Applied rewrites 99.3%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\cos th}{\sqrt{2}}, a1 \cdot a1, \left(\frac{a2}{\sqrt{2}} \cdot a2\right) \cdot \cos th\right)} \]
5. Add Preprocessing

Alternative 2: 77.8% accurate, 0.6× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \begin{array}{l} t_1 := \frac{\cos th}{\sqrt{2}}\\ \mathbf{if}\;t\_1 \cdot \left(a1\_m \cdot a1\_m\right) + t\_1 \cdot \left(a2\_m \cdot a2\_m\right) \leq -5 \cdot 10^{-166}:\\ \;\;\;\;\left(\left(\left(\frac{a2\_m}{\sqrt{2}} \cdot a2\_m\right) \cdot -0.5\right) \cdot th\right) \cdot th\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left({\left(\frac{\sqrt{2}}{a2\_m}\right)}^{-1}, a2\_m, \frac{a1\_m}{\sqrt{2}} \cdot a1\_m\right)\\ \end{array} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (let* ((t_1 (/ (cos th) (sqrt 2.0))))
   (if (<= (+ (* t_1 (* a1_m a1_m)) (* t_1 (* a2_m a2_m))) -5e-166)
     (* (* (* (* (/ a2_m (sqrt 2.0)) a2_m) -0.5) th) th)
     (fma (pow (/ (sqrt 2.0) a2_m) -1.0) a2_m (* (/ a1_m (sqrt 2.0)) a1_m)))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	double t_1 = cos(th) / sqrt(2.0);
	double tmp;
	if (((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= -5e-166) {
		tmp = ((((a2_m / sqrt(2.0)) * a2_m) * -0.5) * th) * th;
	} else {
		tmp = fma(pow((sqrt(2.0) / a2_m), -1.0), a2_m, ((a1_m / sqrt(2.0)) * a1_m));
	}
	return tmp;
}

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	t_1 = Float64(cos(th) / sqrt(2.0))
	tmp = 0.0
	if (Float64(Float64(t_1 * Float64(a1_m * a1_m)) + Float64(t_1 * Float64(a2_m * a2_m))) <= -5e-166)
		tmp = Float64(Float64(Float64(Float64(Float64(a2_m / sqrt(2.0)) * a2_m) * -0.5) * th) * th);
	else
		tmp = fma((Float64(sqrt(2.0) / a2_m) ^ -1.0), a2_m, Float64(Float64(a1_m / sqrt(2.0)) * a1_m));
	end
	return tmp
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := Block[{t$95$1 = N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(t$95$1 * N[(a1$95$m * a1$95$m), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(a2$95$m * a2$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-166], N[(N[(N[(N[(N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * a2$95$m), $MachinePrecision] * -0.5), $MachinePrecision] * th), $MachinePrecision] * th), $MachinePrecision], N[(N[Power[N[(N[Sqrt[2.0], $MachinePrecision] / a2$95$m), $MachinePrecision], -1.0], $MachinePrecision] * a2$95$m + N[(N[(a1$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * a1$95$m), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2))) < -5e-166

   1. Initial program 99.5%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a1 around 0

      \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
   4. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

      2. unpow2 N/A

         \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

      3. associate-*r* N/A

         \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

      4. associate-/l* N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      5. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      6. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

      7. lower-cos.f64 N/A

         \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

      8. lower-/.f64 N/A

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

      9. lower-sqrt.f64 53.1

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

   5. Applied rewrites 53.1%

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. Taylor expanded in th around 0

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\sqrt{2}} + \color{blue}{\frac{{a2}^{2}}{\sqrt{2}}} \]
   7. Step-by-step derivation

   8. Applied rewrites 43.6%

      \[\leadsto \mathsf{fma}\left(th \cdot th, -0.5, 1\right) \cdot \color{blue}{\left(\frac{a2}{\sqrt{2}} \cdot a2\right)} \]

   9. Taylor expanded in th around inf

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\color{blue}{\sqrt{2}}} \]
   10. Step-by-step derivation

   11. Applied rewrites 40.8%

       \[\leadsto \left(\left(\left(\frac{a2}{\sqrt{2}} \cdot a2\right) \cdot -0.5\right) \cdot th\right) \cdot th \]

   if -5e-166 < (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2)))

   1. Initial program 99.2%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing

   3. Taylor expanded in th around 0

      \[\leadsto \color{blue}{\frac{{a1}^{2}}{\sqrt{2}} + \frac{{a2}^{2}}{\sqrt{2}}} \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \color{blue}{\frac{{a2}^{2}}{\sqrt{2}} + \frac{{a1}^{2}}{\sqrt{2}}} \]

      2. unpow2 N/A

         \[\leadsto \frac{\color{blue}{a2 \cdot a2}}{\sqrt{2}} + \frac{{a1}^{2}}{\sqrt{2}} \]

      3. associate-*l/ N/A

         \[\leadsto \color{blue}{\frac{a2}{\sqrt{2}} \cdot a2} + \frac{{a1}^{2}}{\sqrt{2}} \]

      4. lower-fma.f64 N/A

         \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right)} \]

      5. lower-/.f64 N/A

         \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{a2}{\sqrt{2}}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right) \]

      6. lower-sqrt.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\color{blue}{\sqrt{2}}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right) \]

      7. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{\color{blue}{a1 \cdot a1}}{\sqrt{2}}\right) \]

      8. associate-*l/ N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}} \cdot a1}\right) \]

      9. lower-*.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}} \cdot a1}\right) \]

      10. lower-/.f64 N/A

          \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}}} \cdot a1\right) \]

      11. lower-sqrt.f64 87.1

          \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{a1}{\color{blue}{\sqrt{2}}} \cdot a1\right) \]

   5. Applied rewrites 87.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{a1}{\sqrt{2}} \cdot a1\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.1%

      \[\leadsto \mathsf{fma}\left(\frac{1}{\frac{\sqrt{2}}{a2}}, a2, \frac{a1}{\sqrt{2}} \cdot a1\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 75.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \leq -5 \cdot 10^{-166}:\\ \;\;\;\;\left(\left(\left(\frac{a2}{\sqrt{2}} \cdot a2\right) \cdot -0.5\right) \cdot th\right) \cdot th\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left({\left(\frac{\sqrt{2}}{a2}\right)}^{-1}, a2, \frac{a1}{\sqrt{2}} \cdot a1\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 77.8% accurate, 0.8× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \begin{array}{l} t_1 := \frac{a2\_m}{\sqrt{2}}\\ t_2 := \frac{\cos th}{\sqrt{2}}\\ \mathbf{if}\;t\_2 \cdot \left(a1\_m \cdot a1\_m\right) + t\_2 \cdot \left(a2\_m \cdot a2\_m\right) \leq -5 \cdot 10^{-166}:\\ \;\;\;\;\left(\left(\left(t\_1 \cdot a2\_m\right) \cdot -0.5\right) \cdot th\right) \cdot th\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(t\_1, a2\_m, \frac{a1\_m}{\sqrt{2}} \cdot a1\_m\right)\\ \end{array} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (let* ((t_1 (/ a2_m (sqrt 2.0))) (t_2 (/ (cos th) (sqrt 2.0))))
   (if (<= (+ (* t_2 (* a1_m a1_m)) (* t_2 (* a2_m a2_m))) -5e-166)
     (* (* (* (* t_1 a2_m) -0.5) th) th)
     (fma t_1 a2_m (* (/ a1_m (sqrt 2.0)) a1_m)))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	double t_1 = a2_m / sqrt(2.0);
	double t_2 = cos(th) / sqrt(2.0);
	double tmp;
	if (((t_2 * (a1_m * a1_m)) + (t_2 * (a2_m * a2_m))) <= -5e-166) {
		tmp = (((t_1 * a2_m) * -0.5) * th) * th;
	} else {
		tmp = fma(t_1, a2_m, ((a1_m / sqrt(2.0)) * a1_m));
	}
	return tmp;
}

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	t_1 = Float64(a2_m / sqrt(2.0))
	t_2 = Float64(cos(th) / sqrt(2.0))
	tmp = 0.0
	if (Float64(Float64(t_2 * Float64(a1_m * a1_m)) + Float64(t_2 * Float64(a2_m * a2_m))) <= -5e-166)
		tmp = Float64(Float64(Float64(Float64(t_1 * a2_m) * -0.5) * th) * th);
	else
		tmp = fma(t_1, a2_m, Float64(Float64(a1_m / sqrt(2.0)) * a1_m));
	end
	return tmp
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := Block[{t$95$1 = N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(t$95$2 * N[(a1$95$m * a1$95$m), $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(a2$95$m * a2$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-166], N[(N[(N[(N[(t$95$1 * a2$95$m), $MachinePrecision] * -0.5), $MachinePrecision] * th), $MachinePrecision] * th), $MachinePrecision], N[(t$95$1 * a2$95$m + N[(N[(a1$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * a1$95$m), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2))) < -5e-166

   1. Initial program 99.5%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a1 around 0

      \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
   4. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

      2. unpow2 N/A

         \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

      3. associate-*r* N/A

         \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

      4. associate-/l* N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      5. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      6. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

      7. lower-cos.f64 N/A

         \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

      8. lower-/.f64 N/A

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

      9. lower-sqrt.f64 53.1

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

   5. Applied rewrites 53.1%

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. Taylor expanded in th around 0

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\sqrt{2}} + \color{blue}{\frac{{a2}^{2}}{\sqrt{2}}} \]
   7. Step-by-step derivation

   8. Applied rewrites 43.6%

      \[\leadsto \mathsf{fma}\left(th \cdot th, -0.5, 1\right) \cdot \color{blue}{\left(\frac{a2}{\sqrt{2}} \cdot a2\right)} \]

   9. Taylor expanded in th around inf

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\color{blue}{\sqrt{2}}} \]
   10. Step-by-step derivation

   11. Applied rewrites 40.8%

       \[\leadsto \left(\left(\left(\frac{a2}{\sqrt{2}} \cdot a2\right) \cdot -0.5\right) \cdot th\right) \cdot th \]

   if -5e-166 < (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2)))

   1. Initial program 99.2%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing

   3. Taylor expanded in th around 0

      \[\leadsto \color{blue}{\frac{{a1}^{2}}{\sqrt{2}} + \frac{{a2}^{2}}{\sqrt{2}}} \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \color{blue}{\frac{{a2}^{2}}{\sqrt{2}} + \frac{{a1}^{2}}{\sqrt{2}}} \]

      2. unpow2 N/A

         \[\leadsto \frac{\color{blue}{a2 \cdot a2}}{\sqrt{2}} + \frac{{a1}^{2}}{\sqrt{2}} \]

      3. associate-*l/ N/A

         \[\leadsto \color{blue}{\frac{a2}{\sqrt{2}} \cdot a2} + \frac{{a1}^{2}}{\sqrt{2}} \]

      4. lower-fma.f64 N/A

         \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right)} \]

      5. lower-/.f64 N/A

         \[\leadsto \mathsf{fma}\left(\color{blue}{\frac{a2}{\sqrt{2}}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right) \]

      6. lower-sqrt.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\color{blue}{\sqrt{2}}}, a2, \frac{{a1}^{2}}{\sqrt{2}}\right) \]

      7. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{\color{blue}{a1 \cdot a1}}{\sqrt{2}}\right) \]

      8. associate-*l/ N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}} \cdot a1}\right) \]

      9. lower-*.f64 N/A

         \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}} \cdot a1}\right) \]

      10. lower-/.f64 N/A

          \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \color{blue}{\frac{a1}{\sqrt{2}}} \cdot a1\right) \]

      11. lower-sqrt.f64 87.1

          \[\leadsto \mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{a1}{\color{blue}{\sqrt{2}}} \cdot a1\right) \]

   5. Applied rewrites 87.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{a2}{\sqrt{2}}, a2, \frac{a1}{\sqrt{2}} \cdot a1\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 4: 77.5% accurate, 0.8× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \begin{array}{l} t_1 := \frac{\cos th}{\sqrt{2}}\\ \mathbf{if}\;t\_1 \cdot \left(a1\_m \cdot a1\_m\right) + t\_1 \cdot \left(a2\_m \cdot a2\_m\right) \leq -5 \cdot 10^{-166}:\\ \;\;\;\;\left(\left(\left(\frac{a2\_m}{\sqrt{2}} \cdot a2\_m\right) \cdot -0.5\right) \cdot th\right) \cdot th\\ \mathbf{else}:\\ \;\;\;\;\left(\sqrt{0.5} \cdot a2\_m\right) \cdot a2\_m\\ \end{array} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (let* ((t_1 (/ (cos th) (sqrt 2.0))))
   (if (<= (+ (* t_1 (* a1_m a1_m)) (* t_1 (* a2_m a2_m))) -5e-166)
     (* (* (* (* (/ a2_m (sqrt 2.0)) a2_m) -0.5) th) th)
     (* (* (sqrt 0.5) a2_m) a2_m))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	double t_1 = cos(th) / sqrt(2.0);
	double tmp;
	if (((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= -5e-166) {
		tmp = ((((a2_m / sqrt(2.0)) * a2_m) * -0.5) * th) * th;
	} else {
		tmp = (sqrt(0.5) * a2_m) * a2_m;
	}
	return tmp;
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    real(8) :: t_1
    real(8) :: tmp
    t_1 = cos(th) / sqrt(2.0d0)
    if (((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= (-5d-166)) then
        tmp = ((((a2_m / sqrt(2.0d0)) * a2_m) * (-0.5d0)) * th) * th
    else
        tmp = (sqrt(0.5d0) * a2_m) * a2_m
    end if
    code = tmp
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	double t_1 = Math.cos(th) / Math.sqrt(2.0);
	double tmp;
	if (((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= -5e-166) {
		tmp = ((((a2_m / Math.sqrt(2.0)) * a2_m) * -0.5) * th) * th;
	} else {
		tmp = (Math.sqrt(0.5) * a2_m) * a2_m;
	}
	return tmp;
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	t_1 = math.cos(th) / math.sqrt(2.0)
	tmp = 0
	if ((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= -5e-166:
		tmp = ((((a2_m / math.sqrt(2.0)) * a2_m) * -0.5) * th) * th
	else:
		tmp = (math.sqrt(0.5) * a2_m) * a2_m
	return tmp

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	t_1 = Float64(cos(th) / sqrt(2.0))
	tmp = 0.0
	if (Float64(Float64(t_1 * Float64(a1_m * a1_m)) + Float64(t_1 * Float64(a2_m * a2_m))) <= -5e-166)
		tmp = Float64(Float64(Float64(Float64(Float64(a2_m / sqrt(2.0)) * a2_m) * -0.5) * th) * th);
	else
		tmp = Float64(Float64(sqrt(0.5) * a2_m) * a2_m);
	end
	return tmp
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp_2 = code(a1_m, a2_m, th)
	t_1 = cos(th) / sqrt(2.0);
	tmp = 0.0;
	if (((t_1 * (a1_m * a1_m)) + (t_1 * (a2_m * a2_m))) <= -5e-166)
		tmp = ((((a2_m / sqrt(2.0)) * a2_m) * -0.5) * th) * th;
	else
		tmp = (sqrt(0.5) * a2_m) * a2_m;
	end
	tmp_2 = tmp;
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := Block[{t$95$1 = N[(N[Cos[th], $MachinePrecision] / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(t$95$1 * N[(a1$95$m * a1$95$m), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(a2$95$m * a2$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], -5e-166], N[(N[(N[(N[(N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * a2$95$m), $MachinePrecision] * -0.5), $MachinePrecision] * th), $MachinePrecision] * th), $MachinePrecision], N[(N[(N[Sqrt[0.5], $MachinePrecision] * a2$95$m), $MachinePrecision] * a2$95$m), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2))) < -5e-166

   1. Initial program 99.5%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a1 around 0

      \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
   4. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

      2. unpow2 N/A

         \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

      3. associate-*r* N/A

         \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

      4. associate-/l* N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      5. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

      6. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

      7. lower-cos.f64 N/A

         \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

      8. lower-/.f64 N/A

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

      9. lower-sqrt.f64 53.1

         \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

   5. Applied rewrites 53.1%

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. Taylor expanded in th around 0

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\sqrt{2}} + \color{blue}{\frac{{a2}^{2}}{\sqrt{2}}} \]
   7. Step-by-step derivation

   8. Applied rewrites 43.6%

      \[\leadsto \mathsf{fma}\left(th \cdot th, -0.5, 1\right) \cdot \color{blue}{\left(\frac{a2}{\sqrt{2}} \cdot a2\right)} \]

   9. Taylor expanded in th around inf

      \[\leadsto \frac{-1}{2} \cdot \frac{{a2}^{2} \cdot {th}^{2}}{\color{blue}{\sqrt{2}}} \]
   10. Step-by-step derivation

   11. Applied rewrites 40.8%

       \[\leadsto \left(\left(\left(\frac{a2}{\sqrt{2}} \cdot a2\right) \cdot -0.5\right) \cdot th\right) \cdot th \]

   if -5e-166 < (+.f64 (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a1 a1)) (*.f64 (/.f64 (cos.f64 th) (sqrt.f64 #s(literal 2 binary64))) (*.f64 a2 a2)))

   1. Initial program 99.2%

      \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

      2. lift-*.f64 N/A

         \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

      3. lift-*.f64 N/A

         \[\leadsto \frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

      4. distribute-lft-out N/A

         \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)} \]

      5. lift-/.f64 N/A

         \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

      6. clear-num N/A

         \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{2}}{\cos th}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

      7. associate-/r/ N/A

         \[\leadsto \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \cos th\right)} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

      8. associate-*l* N/A

         \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

      9. lower-*.f64 N/A

         \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

      10. lift-sqrt.f64 N/A

          \[\leadsto \frac{1}{\color{blue}{\sqrt{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

      11. pow1/2 N/A

          \[\leadsto \frac{1}{\color{blue}{{2}^{\frac{1}{2}}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

      12. pow-flip N/A

          \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

      13. lower-pow.f64 N/A

          \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

      14. metadata-eval N/A

          \[\leadsto {2}^{\color{blue}{\frac{-1}{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

      15. *-commutative N/A

          \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

      16. lower-*.f64 N/A

          \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

      17. +-commutative N/A

          \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\color{blue}{\left(a2 \cdot a2 + a1 \cdot a1\right)} \cdot \cos th\right) \]

      18. lift-*.f64 N/A

          \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\left(\color{blue}{a2 \cdot a2} + a1 \cdot a1\right) \cdot \cos th\right) \]

      19. lower-fma.f64 99.3

          \[\leadsto {2}^{-0.5} \cdot \left(\color{blue}{\mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \cdot \cos th\right) \]

   4. Applied rewrites 99.3%

      \[\leadsto \color{blue}{{2}^{-0.5} \cdot \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right)} \]

   5. Taylor expanded in th around 0

      \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]

      2. lower-sqrt.f64 N/A

         \[\leadsto \color{blue}{\sqrt{\frac{1}{2}}} \cdot \left({a1}^{2} + {a2}^{2}\right) \]

      3. +-commutative N/A

         \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\left({a2}^{2} + {a1}^{2}\right)} \]

      4. unpow2 N/A

         \[\leadsto \sqrt{\frac{1}{2}} \cdot \left(\color{blue}{a2 \cdot a2} + {a1}^{2}\right) \]

      5. lower-fma.f64 N/A

         \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\mathsf{fma}\left(a2, a2, {a1}^{2}\right)} \]

      6. unpow2 N/A

         \[\leadsto \sqrt{\frac{1}{2}} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

      7. lower-*.f64 86.8

         \[\leadsto \sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

   7. Applied rewrites 86.8%

      \[\leadsto \color{blue}{\sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \]

   8. Taylor expanded in a1 around 0

      \[\leadsto {a2}^{2} \cdot \color{blue}{\sqrt{\frac{1}{2}}} \]
   9. Step-by-step derivation

   10. Applied rewrites 53.2%

       \[\leadsto \left(\sqrt{0.5} \cdot a2\right) \cdot \color{blue}{a2} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 5: 99.1% accurate, 1.2× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ a2\_m \cdot \left({4}^{-0.25} \cdot \left(a2\_m \cdot \cos th\right)\right) \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (* a2_m (* (pow 4.0 -0.25) (* a2_m (cos th)))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return a2_m * (pow(4.0, -0.25) * (a2_m * cos(th)));
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = a2_m * ((4.0d0 ** (-0.25d0)) * (a2_m * cos(th)))
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return a2_m * (Math.pow(4.0, -0.25) * (a2_m * Math.cos(th)));
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return a2_m * (math.pow(4.0, -0.25) * (a2_m * math.cos(th)))

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(a2_m * Float64((4.0 ^ -0.25) * Float64(a2_m * cos(th))))
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = a2_m * ((4.0 ^ -0.25) * (a2_m * cos(th)));
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(a2$95$m * N[(N[Power[4.0, -0.25], $MachinePrecision] * N[(a2$95$m * N[Cos[th], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing

3. Taylor expanded in a1 around 0

   \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
4. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

   2. unpow2 N/A

      \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

   3. associate-*r* N/A

      \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

   4. associate-/l* N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   5. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

   7. lower-cos.f64 N/A

      \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

   8. lower-/.f64 N/A

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

   9. lower-sqrt.f64 57.1

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

5. Applied rewrites 57.1%

   \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]
6. Step-by-step derivation

7. Applied rewrites 57.1%

   \[\leadsto a2 \cdot \color{blue}{\left({4}^{-0.25} \cdot \left(a2 \cdot \cos th\right)\right)} \]
8. Add Preprocessing

Alternative 6: 99.1% accurate, 2.0× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(\frac{a2\_m}{\sqrt{2}} \cdot \cos th\right) \cdot a2\_m \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (* (* (/ a2_m (sqrt 2.0)) (cos th)) a2_m))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return ((a2_m / sqrt(2.0)) * cos(th)) * a2_m;
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = ((a2_m / sqrt(2.0d0)) * cos(th)) * a2_m
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return ((a2_m / Math.sqrt(2.0)) * Math.cos(th)) * a2_m;
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return ((a2_m / math.sqrt(2.0)) * math.cos(th)) * a2_m

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(Float64(a2_m / sqrt(2.0)) * cos(th)) * a2_m)
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = ((a2_m / sqrt(2.0)) * cos(th)) * a2_m;
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision] * N[Cos[th], $MachinePrecision]), $MachinePrecision] * a2$95$m), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing

3. Taylor expanded in a1 around 0

   \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
4. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

   2. unpow2 N/A

      \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

   3. associate-*r* N/A

      \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

   4. associate-/l* N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   5. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

   7. lower-cos.f64 N/A

      \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

   8. lower-/.f64 N/A

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

   9. lower-sqrt.f64 57.1

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

5. Applied rewrites 57.1%

   \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]
6. Step-by-step derivation

7. Applied rewrites 57.1%

   \[\leadsto \left(\frac{a2}{\sqrt{2}} \cdot \cos th\right) \cdot \color{blue}{a2} \]
8. Add Preprocessing

Alternative 7: 99.1% accurate, 2.0× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(\cos th \cdot a2\_m\right) \cdot \frac{a2\_m}{\sqrt{2}} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (* (* (cos th) a2_m) (/ a2_m (sqrt 2.0))))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return (cos(th) * a2_m) * (a2_m / sqrt(2.0));
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = (cos(th) * a2_m) * (a2_m / sqrt(2.0d0))
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return (Math.cos(th) * a2_m) * (a2_m / Math.sqrt(2.0));
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return (math.cos(th) * a2_m) * (a2_m / math.sqrt(2.0))

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(cos(th) * a2_m) * Float64(a2_m / sqrt(2.0)))
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = (cos(th) * a2_m) * (a2_m / sqrt(2.0));
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[Cos[th], $MachinePrecision] * a2$95$m), $MachinePrecision] * N[(a2$95$m / N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing

3. Taylor expanded in a1 around 0

   \[\leadsto \color{blue}{\frac{{a2}^{2} \cdot \cos th}{\sqrt{2}}} \]
4. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \frac{\color{blue}{\cos th \cdot {a2}^{2}}}{\sqrt{2}} \]

   2. unpow2 N/A

      \[\leadsto \frac{\cos th \cdot \color{blue}{\left(a2 \cdot a2\right)}}{\sqrt{2}} \]

   3. associate-*r* N/A

      \[\leadsto \frac{\color{blue}{\left(\cos th \cdot a2\right) \cdot a2}}{\sqrt{2}} \]

   4. associate-/l* N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   5. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]

   6. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot a2\right)} \cdot \frac{a2}{\sqrt{2}} \]

   7. lower-cos.f64 N/A

      \[\leadsto \left(\color{blue}{\cos th} \cdot a2\right) \cdot \frac{a2}{\sqrt{2}} \]

   8. lower-/.f64 N/A

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \color{blue}{\frac{a2}{\sqrt{2}}} \]

   9. lower-sqrt.f64 57.1

      \[\leadsto \left(\cos th \cdot a2\right) \cdot \frac{a2}{\color{blue}{\sqrt{2}}} \]

5. Applied rewrites 57.1%

   \[\leadsto \color{blue}{\left(\cos th \cdot a2\right) \cdot \frac{a2}{\sqrt{2}}} \]
6. Add Preprocessing

Alternative 8: 99.6% accurate, 2.0× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(\mathsf{fma}\left(a2\_m, a2\_m, a1\_m \cdot a1\_m\right) \cdot \cos th\right) \cdot \sqrt{0.5} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (* (* (fma a2_m a2_m (* a1_m a1_m)) (cos th)) (sqrt 0.5)))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return (fma(a2_m, a2_m, (a1_m * a1_m)) * cos(th)) * sqrt(0.5);
}

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(fma(a2_m, a2_m, Float64(a1_m * a1_m)) * cos(th)) * sqrt(0.5))
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[(a2$95$m * a2$95$m + N[(a1$95$m * a1$95$m), $MachinePrecision]), $MachinePrecision] * N[Cos[th], $MachinePrecision]), $MachinePrecision] * N[Sqrt[0.5], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift-+.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

   3. lift-*.f64 N/A

      \[\leadsto \frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   4. distribute-lft-out N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)} \]

   5. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   6. clear-num N/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{2}}{\cos th}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   7. associate-/r/ N/A

      \[\leadsto \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \cos th\right)} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   8. associate-*l* N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   9. lower-*.f64 N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   10. lift-sqrt.f64 N/A

       \[\leadsto \frac{1}{\color{blue}{\sqrt{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   11. pow1/2 N/A

       \[\leadsto \frac{1}{\color{blue}{{2}^{\frac{1}{2}}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   12. pow-flip N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   13. lower-pow.f64 N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   14. metadata-eval N/A

       \[\leadsto {2}^{\color{blue}{\frac{-1}{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   15. *-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   16. lower-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   17. +-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\color{blue}{\left(a2 \cdot a2 + a1 \cdot a1\right)} \cdot \cos th\right) \]

   18. lift-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\left(\color{blue}{a2 \cdot a2} + a1 \cdot a1\right) \cdot \cos th\right) \]

   19. lower-fma.f64 99.4

       \[\leadsto {2}^{-0.5} \cdot \left(\color{blue}{\mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \cdot \cos th\right) \]

4. Applied rewrites 99.4%

   \[\leadsto \color{blue}{{2}^{-0.5} \cdot \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right)} \]

5. Taylor expanded in a1 around 0

   \[\leadsto \color{blue}{{a1}^{2} \cdot \left(\cos th \cdot \sqrt{\frac{1}{2}}\right) + {a2}^{2} \cdot \left(\cos th \cdot \sqrt{\frac{1}{2}}\right)} \]
6. Step-by-step derivation

   1. distribute-rgt-out N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot \sqrt{\frac{1}{2}}\right) \cdot \left({a1}^{2} + {a2}^{2}\right)} \]

   2. associate-*r* N/A

      \[\leadsto \color{blue}{\cos th \cdot \left(\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)\right)} \]

   3. *-commutative N/A

      \[\leadsto \cos th \cdot \color{blue}{\left(\left({a1}^{2} + {a2}^{2}\right) \cdot \sqrt{\frac{1}{2}}\right)} \]

   4. associate-*r* N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot \left({a1}^{2} + {a2}^{2}\right)\right) \cdot \sqrt{\frac{1}{2}}} \]

   5. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot \left({a1}^{2} + {a2}^{2}\right)\right) \cdot \sqrt{\frac{1}{2}}} \]

   6. *-commutative N/A

      \[\leadsto \color{blue}{\left(\left({a1}^{2} + {a2}^{2}\right) \cdot \cos th\right)} \cdot \sqrt{\frac{1}{2}} \]

   7. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\left({a1}^{2} + {a2}^{2}\right) \cdot \cos th\right)} \cdot \sqrt{\frac{1}{2}} \]

   8. +-commutative N/A

      \[\leadsto \left(\color{blue}{\left({a2}^{2} + {a1}^{2}\right)} \cdot \cos th\right) \cdot \sqrt{\frac{1}{2}} \]

   9. unpow2 N/A

      \[\leadsto \left(\left(\color{blue}{a2 \cdot a2} + {a1}^{2}\right) \cdot \cos th\right) \cdot \sqrt{\frac{1}{2}} \]

   10. lower-fma.f64 N/A

       \[\leadsto \left(\color{blue}{\mathsf{fma}\left(a2, a2, {a1}^{2}\right)} \cdot \cos th\right) \cdot \sqrt{\frac{1}{2}} \]

   11. unpow2 N/A

       \[\leadsto \left(\mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \cdot \cos th\right) \cdot \sqrt{\frac{1}{2}} \]

   12. lower-*.f64 N/A

       \[\leadsto \left(\mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \cdot \cos th\right) \cdot \sqrt{\frac{1}{2}} \]

   13. lower-cos.f64 N/A

       \[\leadsto \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \color{blue}{\cos th}\right) \cdot \sqrt{\frac{1}{2}} \]

   14. lower-sqrt.f64 99.4

       \[\leadsto \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right) \cdot \color{blue}{\sqrt{0.5}} \]

7. Applied rewrites 99.4%

   \[\leadsto \color{blue}{\left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right) \cdot \sqrt{0.5}} \]
8. Add Preprocessing

Alternative 9: 99.1% accurate, 2.1× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(\sqrt{0.5} \cdot \cos th\right) \cdot \left(a2\_m \cdot a2\_m\right) \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th)
 :precision binary64
 (* (* (sqrt 0.5) (cos th)) (* a2_m a2_m)))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return (sqrt(0.5) * cos(th)) * (a2_m * a2_m);
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = (sqrt(0.5d0) * cos(th)) * (a2_m * a2_m)
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return (Math.sqrt(0.5) * Math.cos(th)) * (a2_m * a2_m);
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return (math.sqrt(0.5) * math.cos(th)) * (a2_m * a2_m)

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(sqrt(0.5) * cos(th)) * Float64(a2_m * a2_m))
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = (sqrt(0.5) * cos(th)) * (a2_m * a2_m);
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[Sqrt[0.5], $MachinePrecision] * N[Cos[th], $MachinePrecision]), $MachinePrecision] * N[(a2$95$m * a2$95$m), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift-+.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

   3. lift-*.f64 N/A

      \[\leadsto \frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   4. distribute-lft-out N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)} \]

   5. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   6. clear-num N/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{2}}{\cos th}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   7. associate-/r/ N/A

      \[\leadsto \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \cos th\right)} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   8. associate-*l* N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   9. lower-*.f64 N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   10. lift-sqrt.f64 N/A

       \[\leadsto \frac{1}{\color{blue}{\sqrt{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   11. pow1/2 N/A

       \[\leadsto \frac{1}{\color{blue}{{2}^{\frac{1}{2}}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   12. pow-flip N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   13. lower-pow.f64 N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   14. metadata-eval N/A

       \[\leadsto {2}^{\color{blue}{\frac{-1}{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   15. *-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   16. lower-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   17. +-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\color{blue}{\left(a2 \cdot a2 + a1 \cdot a1\right)} \cdot \cos th\right) \]

   18. lift-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\left(\color{blue}{a2 \cdot a2} + a1 \cdot a1\right) \cdot \cos th\right) \]

   19. lower-fma.f64 99.4

       \[\leadsto {2}^{-0.5} \cdot \left(\color{blue}{\mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \cdot \cos th\right) \]

4. Applied rewrites 99.4%

   \[\leadsto \color{blue}{{2}^{-0.5} \cdot \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right)} \]

5. Taylor expanded in a1 around 0

   \[\leadsto \color{blue}{{a2}^{2} \cdot \left(\cos th \cdot \sqrt{\frac{1}{2}}\right)} \]
6. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot \sqrt{\frac{1}{2}}\right) \cdot {a2}^{2}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\cos th \cdot \sqrt{\frac{1}{2}}\right) \cdot {a2}^{2}} \]

   3. *-commutative N/A

      \[\leadsto \color{blue}{\left(\sqrt{\frac{1}{2}} \cdot \cos th\right)} \cdot {a2}^{2} \]

   4. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\sqrt{\frac{1}{2}} \cdot \cos th\right)} \cdot {a2}^{2} \]

   5. lower-sqrt.f64 N/A

      \[\leadsto \left(\color{blue}{\sqrt{\frac{1}{2}}} \cdot \cos th\right) \cdot {a2}^{2} \]

   6. lower-cos.f64 N/A

      \[\leadsto \left(\sqrt{\frac{1}{2}} \cdot \color{blue}{\cos th}\right) \cdot {a2}^{2} \]

   7. unpow2 N/A

      \[\leadsto \left(\sqrt{\frac{1}{2}} \cdot \cos th\right) \cdot \color{blue}{\left(a2 \cdot a2\right)} \]

   8. lower-*.f64 57.2

      \[\leadsto \left(\sqrt{0.5} \cdot \cos th\right) \cdot \color{blue}{\left(a2 \cdot a2\right)} \]

7. Applied rewrites 57.2%

   \[\leadsto \color{blue}{\left(\sqrt{0.5} \cdot \cos th\right) \cdot \left(a2 \cdot a2\right)} \]
8. Add Preprocessing

Alternative 10: 65.5% accurate, 12.7× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(\sqrt{0.5} \cdot a2\_m\right) \cdot a2\_m \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th) :precision binary64 (* (* (sqrt 0.5) a2_m) a2_m))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return (sqrt(0.5) * a2_m) * a2_m;
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = (sqrt(0.5d0) * a2_m) * a2_m
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return (Math.sqrt(0.5) * a2_m) * a2_m;
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return (math.sqrt(0.5) * a2_m) * a2_m

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(sqrt(0.5) * a2_m) * a2_m)
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = (sqrt(0.5) * a2_m) * a2_m;
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(N[Sqrt[0.5], $MachinePrecision] * a2$95$m), $MachinePrecision] * a2$95$m), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift-+.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

   3. lift-*.f64 N/A

      \[\leadsto \frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   4. distribute-lft-out N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)} \]

   5. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   6. clear-num N/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{2}}{\cos th}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   7. associate-/r/ N/A

      \[\leadsto \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \cos th\right)} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   8. associate-*l* N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   9. lower-*.f64 N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   10. lift-sqrt.f64 N/A

       \[\leadsto \frac{1}{\color{blue}{\sqrt{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   11. pow1/2 N/A

       \[\leadsto \frac{1}{\color{blue}{{2}^{\frac{1}{2}}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   12. pow-flip N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   13. lower-pow.f64 N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   14. metadata-eval N/A

       \[\leadsto {2}^{\color{blue}{\frac{-1}{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   15. *-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   16. lower-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   17. +-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\color{blue}{\left(a2 \cdot a2 + a1 \cdot a1\right)} \cdot \cos th\right) \]

   18. lift-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\left(\color{blue}{a2 \cdot a2} + a1 \cdot a1\right) \cdot \cos th\right) \]

   19. lower-fma.f64 99.4

       \[\leadsto {2}^{-0.5} \cdot \left(\color{blue}{\mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \cdot \cos th\right) \]

4. Applied rewrites 99.4%

   \[\leadsto \color{blue}{{2}^{-0.5} \cdot \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right)} \]

5. Taylor expanded in th around 0

   \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]
6. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]

   2. lower-sqrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt{\frac{1}{2}}} \cdot \left({a1}^{2} + {a2}^{2}\right) \]

   3. +-commutative N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\left({a2}^{2} + {a1}^{2}\right)} \]

   4. unpow2 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \left(\color{blue}{a2 \cdot a2} + {a1}^{2}\right) \]

   5. lower-fma.f64 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\mathsf{fma}\left(a2, a2, {a1}^{2}\right)} \]

   6. unpow2 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

   7. lower-*.f64 64.6

      \[\leadsto \sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

7. Applied rewrites 64.6%

   \[\leadsto \color{blue}{\sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \]

8. Taylor expanded in a1 around 0

   \[\leadsto {a2}^{2} \cdot \color{blue}{\sqrt{\frac{1}{2}}} \]
9. Step-by-step derivation

10. Applied rewrites 39.8%

    \[\leadsto \left(\sqrt{0.5} \cdot a2\right) \cdot \color{blue}{a2} \]
11. Add Preprocessing

Alternative 11: 13.4% accurate, 12.7× speedup

Math

\[\begin{array}{l} a2_m = \left|a2\right| \\ a1_m = \left|a1\right| \\ [a1_m, a2_m, th] = \mathsf{sort}([a1_m, a2_m, th])\\ \\ \left(a1\_m \cdot a1\_m\right) \cdot \sqrt{0.5} \end{array} \]

FPCore

a2_m = (fabs.f64 a2)
a1_m = (fabs.f64 a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
(FPCore (a1_m a2_m th) :precision binary64 (* (* a1_m a1_m) (sqrt 0.5)))

C

a2_m = fabs(a2);
a1_m = fabs(a1);
assert(a1_m < a2_m && a2_m < th);
double code(double a1_m, double a2_m, double th) {
	return (a1_m * a1_m) * sqrt(0.5);
}

Fortran

a2_m = abs(a2)
a1_m = abs(a1)
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
real(8) function code(a1_m, a2_m, th)
    real(8), intent (in) :: a1_m
    real(8), intent (in) :: a2_m
    real(8), intent (in) :: th
    code = (a1_m * a1_m) * sqrt(0.5d0)
end function

Java

a2_m = Math.abs(a2);
a1_m = Math.abs(a1);
assert a1_m < a2_m && a2_m < th;
public static double code(double a1_m, double a2_m, double th) {
	return (a1_m * a1_m) * Math.sqrt(0.5);
}

Python

a2_m = math.fabs(a2)
a1_m = math.fabs(a1)
[a1_m, a2_m, th] = sort([a1_m, a2_m, th])
def code(a1_m, a2_m, th):
	return (a1_m * a1_m) * math.sqrt(0.5)

Julia

a2_m = abs(a2)
a1_m = abs(a1)
a1_m, a2_m, th = sort([a1_m, a2_m, th])
function code(a1_m, a2_m, th)
	return Float64(Float64(a1_m * a1_m) * sqrt(0.5))
end

MATLAB

a2_m = abs(a2);
a1_m = abs(a1);
a1_m, a2_m, th = num2cell(sort([a1_m, a2_m, th])){:}
function tmp = code(a1_m, a2_m, th)
	tmp = (a1_m * a1_m) * sqrt(0.5);
end

Wolfram

a2_m = N[Abs[a2], $MachinePrecision]
a1_m = N[Abs[a1], $MachinePrecision]
NOTE: a1_m, a2_m, and th should be sorted in increasing order before calling this function.
code[a1$95$m_, a2$95$m_, th_] := N[(N[(a1$95$m * a1$95$m), $MachinePrecision] * N[Sqrt[0.5], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 99.2%

   \[\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift-+.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right)} + \frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right) \]

   3. lift-*.f64 N/A

      \[\leadsto \frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1\right) + \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a2 \cdot a2\right)} \]

   4. distribute-lft-out N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)} \]

   5. lift-/.f64 N/A

      \[\leadsto \color{blue}{\frac{\cos th}{\sqrt{2}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   6. clear-num N/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\sqrt{2}}{\cos th}}} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   7. associate-/r/ N/A

      \[\leadsto \color{blue}{\left(\frac{1}{\sqrt{2}} \cdot \cos th\right)} \cdot \left(a1 \cdot a1 + a2 \cdot a2\right) \]

   8. associate-*l* N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   9. lower-*.f64 N/A

      \[\leadsto \color{blue}{\frac{1}{\sqrt{2}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right)} \]

   10. lift-sqrt.f64 N/A

       \[\leadsto \frac{1}{\color{blue}{\sqrt{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   11. pow1/2 N/A

       \[\leadsto \frac{1}{\color{blue}{{2}^{\frac{1}{2}}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   12. pow-flip N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   13. lower-pow.f64 N/A

       \[\leadsto \color{blue}{{2}^{\left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   14. metadata-eval N/A

       \[\leadsto {2}^{\color{blue}{\frac{-1}{2}}} \cdot \left(\cos th \cdot \left(a1 \cdot a1 + a2 \cdot a2\right)\right) \]

   15. *-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   16. lower-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \color{blue}{\left(\left(a1 \cdot a1 + a2 \cdot a2\right) \cdot \cos th\right)} \]

   17. +-commutative N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\color{blue}{\left(a2 \cdot a2 + a1 \cdot a1\right)} \cdot \cos th\right) \]

   18. lift-*.f64 N/A

       \[\leadsto {2}^{\frac{-1}{2}} \cdot \left(\left(\color{blue}{a2 \cdot a2} + a1 \cdot a1\right) \cdot \cos th\right) \]

   19. lower-fma.f64 99.4

       \[\leadsto {2}^{-0.5} \cdot \left(\color{blue}{\mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \cdot \cos th\right) \]

4. Applied rewrites 99.4%

   \[\leadsto \color{blue}{{2}^{-0.5} \cdot \left(\mathsf{fma}\left(a2, a2, a1 \cdot a1\right) \cdot \cos th\right)} \]

5. Taylor expanded in th around 0

   \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]
6. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt{\frac{1}{2}} \cdot \left({a1}^{2} + {a2}^{2}\right)} \]

   2. lower-sqrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt{\frac{1}{2}}} \cdot \left({a1}^{2} + {a2}^{2}\right) \]

   3. +-commutative N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\left({a2}^{2} + {a1}^{2}\right)} \]

   4. unpow2 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \left(\color{blue}{a2 \cdot a2} + {a1}^{2}\right) \]

   5. lower-fma.f64 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \color{blue}{\mathsf{fma}\left(a2, a2, {a1}^{2}\right)} \]

   6. unpow2 N/A

      \[\leadsto \sqrt{\frac{1}{2}} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

   7. lower-*.f64 64.6

      \[\leadsto \sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, \color{blue}{a1 \cdot a1}\right) \]

7. Applied rewrites 64.6%

   \[\leadsto \color{blue}{\sqrt{0.5} \cdot \mathsf{fma}\left(a2, a2, a1 \cdot a1\right)} \]

8. Taylor expanded in a1 around inf

   \[\leadsto {a1}^{2} \cdot \color{blue}{\sqrt{\frac{1}{2}}} \]
9. Step-by-step derivation

10. Applied rewrites 39.1%

    \[\leadsto \left(\sqrt{0.5} \cdot a1\right) \cdot \color{blue}{a1} \]
11. Step-by-step derivation

12. Applied rewrites 38.8%

    \[\leadsto \left(a1 \cdot a1\right) \cdot \sqrt{0.5} \]
13. Add Preprocessing

Reproduce

herbie shell --seed 2024307 
(FPCore (a1 a2 th)
  :name "Migdal et al, Equation (64)"
  :precision binary64
  (+ (* (/ (cos th) (sqrt 2.0)) (* a1 a1)) (* (/ (cos th) (sqrt 2.0)) (* a2 a2))))