Given's Rotation SVD example

Percentage Accurate: 79.4% → 99.6%
Time: 10.1s
Alternatives: 10
Speedup: 0.6×

Specification

?
\[10^{-150} < \left|x\right| \land \left|x\right| < 10^{+150}\]
\[\begin{array}{l} \\ \sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \end{array} \]
(FPCore (p x)
 :precision binary64
 (sqrt (* 0.5 (+ 1.0 (/ x (sqrt (+ (* (* 4.0 p) p) (* x x))))))))
double code(double p, double x) {
	return sqrt((0.5 * (1.0 + (x / sqrt((((4.0 * p) * p) + (x * x)))))));
}
real(8) function code(p, x)
    real(8), intent (in) :: p
    real(8), intent (in) :: x
    code = sqrt((0.5d0 * (1.0d0 + (x / sqrt((((4.0d0 * p) * p) + (x * x)))))))
end function
public static double code(double p, double x) {
	return Math.sqrt((0.5 * (1.0 + (x / Math.sqrt((((4.0 * p) * p) + (x * x)))))));
}
def code(p, x):
	return math.sqrt((0.5 * (1.0 + (x / math.sqrt((((4.0 * p) * p) + (x * x)))))))
function code(p, x)
	return sqrt(Float64(0.5 * Float64(1.0 + Float64(x / sqrt(Float64(Float64(Float64(4.0 * p) * p) + Float64(x * x)))))))
end
function tmp = code(p, x)
	tmp = sqrt((0.5 * (1.0 + (x / sqrt((((4.0 * p) * p) + (x * x)))))));
end
code[p_, x_] := N[Sqrt[N[(0.5 * N[(1.0 + N[(x / N[Sqrt[N[(N[(N[(4.0 * p), $MachinePrecision] * p), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}
\end{array}

Sampling outcomes in binary64 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 10 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 79.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \end{array} \]
(FPCore (p x)
 :precision binary64
 (sqrt (* 0.5 (+ 1.0 (/ x (sqrt (+ (* (* 4.0 p) p) (* x x))))))))
double code(double p, double x) {
	return sqrt((0.5 * (1.0 + (x / sqrt((((4.0 * p) * p) + (x * x)))))));
}
real(8) function code(p, x)
    real(8), intent (in) :: p
    real(8), intent (in) :: x
    code = sqrt((0.5d0 * (1.0d0 + (x / sqrt((((4.0d0 * p) * p) + (x * x)))))))
end function
public static double code(double p, double x) {
	return Math.sqrt((0.5 * (1.0 + (x / Math.sqrt((((4.0 * p) * p) + (x * x)))))));
}
def code(p, x):
	return math.sqrt((0.5 * (1.0 + (x / math.sqrt((((4.0 * p) * p) + (x * x)))))))
function code(p, x)
	return sqrt(Float64(0.5 * Float64(1.0 + Float64(x / sqrt(Float64(Float64(Float64(4.0 * p) * p) + Float64(x * x)))))))
end
function tmp = code(p, x)
	tmp = sqrt((0.5 * (1.0 + (x / sqrt((((4.0 * p) * p) + (x * x)))))));
end
code[p_, x_] := N[Sqrt[N[(0.5 * N[(1.0 + N[(x / N[Sqrt[N[(N[(N[(4.0 * p), $MachinePrecision] * p), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}
\end{array}

Alternative 1: 99.6% accurate, 0.6× speedup?

\[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := p\_m \cdot \left(4 \cdot p\_m\right)\\ \mathbf{if}\;\frac{x}{\sqrt{t\_0 + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, t\_0\right)}}, x, 0.5\right)}\\ \end{array} \end{array} \]
p_m = (fabs.f64 p)
(FPCore (p_m x)
 :precision binary64
 (let* ((t_0 (* p_m (* 4.0 p_m))))
   (if (<= (/ x (sqrt (+ t_0 (* x x)))) -0.5)
     (/ (fma (/ -1.5 (* x x)) (* p_m (* p_m p_m)) p_m) (- x))
     (sqrt (fma (/ 0.5 (sqrt (fma x x t_0))) x 0.5)))))
p_m = fabs(p);
double code(double p_m, double x) {
	double t_0 = p_m * (4.0 * p_m);
	double tmp;
	if ((x / sqrt((t_0 + (x * x)))) <= -0.5) {
		tmp = fma((-1.5 / (x * x)), (p_m * (p_m * p_m)), p_m) / -x;
	} else {
		tmp = sqrt(fma((0.5 / sqrt(fma(x, x, t_0))), x, 0.5));
	}
	return tmp;
}
p_m = abs(p)
function code(p_m, x)
	t_0 = Float64(p_m * Float64(4.0 * p_m))
	tmp = 0.0
	if (Float64(x / sqrt(Float64(t_0 + Float64(x * x)))) <= -0.5)
		tmp = Float64(fma(Float64(-1.5 / Float64(x * x)), Float64(p_m * Float64(p_m * p_m)), p_m) / Float64(-x));
	else
		tmp = sqrt(fma(Float64(0.5 / sqrt(fma(x, x, t_0))), x, 0.5));
	end
	return tmp
end
p_m = N[Abs[p], $MachinePrecision]
code[p$95$m_, x_] := Block[{t$95$0 = N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(x / N[Sqrt[N[(t$95$0 + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], -0.5], N[(N[(N[(-1.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(p$95$m * N[(p$95$m * p$95$m), $MachinePrecision]), $MachinePrecision] + p$95$m), $MachinePrecision] / (-x)), $MachinePrecision], N[Sqrt[N[(N[(0.5 / N[Sqrt[N[(x * x + t$95$0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * x + 0.5), $MachinePrecision]], $MachinePrecision]]]
\begin{array}{l}
p_m = \left|p\right|

\\
\begin{array}{l}
t_0 := p\_m \cdot \left(4 \cdot p\_m\right)\\
\mathbf{if}\;\frac{x}{\sqrt{t\_0 + x \cdot x}} \leq -0.5:\\
\;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, t\_0\right)}}, x, 0.5\right)}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

    1. Initial program 18.1%

      \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
      2. lift-+.f64N/A

        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
      3. +-commutativeN/A

        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
      4. distribute-lft-inN/A

        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
      5. *-commutativeN/A

        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
      6. lift-/.f64N/A

        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
      7. div-invN/A

        \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
      8. associate-*l*N/A

        \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
      9. *-commutativeN/A

        \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
      10. metadata-evalN/A

        \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
      11. lower-fma.f64N/A

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
    4. Applied rewrites3.5%

      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
    5. Taylor expanded in x around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}} \]
    6. Step-by-step derivation
      1. mul-1-negN/A

        \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
      2. lower-neg.f64N/A

        \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
      3. lower-/.f64N/A

        \[\leadsto \mathsf{neg}\left(\color{blue}{\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}}\right) \]
    7. Applied rewrites47.6%

      \[\leadsto \color{blue}{-\frac{\mathsf{fma}\left(0.125, \frac{\left(\left(p \cdot p\right) \cdot \left(p \cdot p\right)\right) \cdot -12}{p \cdot \left(x \cdot x\right)}, p\right)}{x}} \]
    8. Step-by-step derivation
      1. Applied rewrites58.8%

        \[\leadsto \frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{\color{blue}{-x}} \]

      if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

      1. Initial program 100.0%

        \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
        2. lift-+.f64N/A

          \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
        4. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
        5. *-commutativeN/A

          \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
        6. lift-/.f64N/A

          \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
        7. div-invN/A

          \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
        8. associate-*l*N/A

          \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
        9. *-commutativeN/A

          \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
        10. metadata-evalN/A

          \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
        11. lower-fma.f64N/A

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
      4. Applied rewrites100.0%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
    9. Recombined 2 regimes into one program.
    10. Final simplification91.0%

      \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{-x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}\\ \end{array} \]
    11. Add Preprocessing

    Alternative 2: 98.4% accurate, 0.4× speedup?

    \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{1 + \frac{p\_m \cdot p\_m}{x \cdot x}}}\\ \end{array} \end{array} \]
    p_m = (fabs.f64 p)
    (FPCore (p_m x)
     :precision binary64
     (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
       (if (<= t_0 -0.5)
         (/ (fma (/ -1.5 (* x x)) (* p_m (* p_m p_m)) p_m) (- x))
         (if (<= t_0 2e-16)
           (sqrt (fma 0.25 (/ x p_m) 0.5))
           (/ 1.0 (sqrt (+ 1.0 (/ (* p_m p_m) (* x x)))))))))
    p_m = fabs(p);
    double code(double p_m, double x) {
    	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
    	double tmp;
    	if (t_0 <= -0.5) {
    		tmp = fma((-1.5 / (x * x)), (p_m * (p_m * p_m)), p_m) / -x;
    	} else if (t_0 <= 2e-16) {
    		tmp = sqrt(fma(0.25, (x / p_m), 0.5));
    	} else {
    		tmp = 1.0 / sqrt((1.0 + ((p_m * p_m) / (x * x))));
    	}
    	return tmp;
    }
    
    p_m = abs(p)
    function code(p_m, x)
    	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
    	tmp = 0.0
    	if (t_0 <= -0.5)
    		tmp = Float64(fma(Float64(-1.5 / Float64(x * x)), Float64(p_m * Float64(p_m * p_m)), p_m) / Float64(-x));
    	elseif (t_0 <= 2e-16)
    		tmp = sqrt(fma(0.25, Float64(x / p_m), 0.5));
    	else
    		tmp = Float64(1.0 / sqrt(Float64(1.0 + Float64(Float64(p_m * p_m) / Float64(x * x)))));
    	end
    	return tmp
    end
    
    p_m = N[Abs[p], $MachinePrecision]
    code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(N[(N[(-1.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(p$95$m * N[(p$95$m * p$95$m), $MachinePrecision]), $MachinePrecision] + p$95$m), $MachinePrecision] / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[N[(0.25 * N[(x / p$95$m), $MachinePrecision] + 0.5), $MachinePrecision]], $MachinePrecision], N[(1.0 / N[Sqrt[N[(1.0 + N[(N[(p$95$m * p$95$m), $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
    
    \begin{array}{l}
    p_m = \left|p\right|
    
    \\
    \begin{array}{l}
    t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
    \mathbf{if}\;t\_0 \leq -0.5:\\
    \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\
    
    \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
    \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\
    
    \mathbf{else}:\\
    \;\;\;\;\frac{1}{\sqrt{1 + \frac{p\_m \cdot p\_m}{x \cdot x}}}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 3 regimes
    2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

      1. Initial program 18.1%

        \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
        2. lift-+.f64N/A

          \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
        3. +-commutativeN/A

          \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
        4. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
        5. *-commutativeN/A

          \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
        6. lift-/.f64N/A

          \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
        7. div-invN/A

          \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
        8. associate-*l*N/A

          \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
        9. *-commutativeN/A

          \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
        10. metadata-evalN/A

          \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
        11. lower-fma.f64N/A

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
      4. Applied rewrites3.5%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
      5. Taylor expanded in x around -inf

        \[\leadsto \color{blue}{-1 \cdot \frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}} \]
      6. Step-by-step derivation
        1. mul-1-negN/A

          \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
        2. lower-neg.f64N/A

          \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
        3. lower-/.f64N/A

          \[\leadsto \mathsf{neg}\left(\color{blue}{\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}}\right) \]
      7. Applied rewrites47.6%

        \[\leadsto \color{blue}{-\frac{\mathsf{fma}\left(0.125, \frac{\left(\left(p \cdot p\right) \cdot \left(p \cdot p\right)\right) \cdot -12}{p \cdot \left(x \cdot x\right)}, p\right)}{x}} \]
      8. Step-by-step derivation
        1. Applied rewrites58.8%

          \[\leadsto \frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{\color{blue}{-x}} \]

        if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

        1. Initial program 100.0%

          \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
        2. Add Preprocessing
        3. Taylor expanded in x around 0

          \[\leadsto \sqrt{\color{blue}{\frac{1}{2} + \frac{1}{4} \cdot \frac{x}{p}}} \]
        4. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \sqrt{\color{blue}{\frac{1}{4} \cdot \frac{x}{p} + \frac{1}{2}}} \]
          2. lower-fma.f64N/A

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{4}, \frac{x}{p}, \frac{1}{2}\right)}} \]
          3. lower-/.f64100.0

            \[\leadsto \sqrt{\mathsf{fma}\left(0.25, \color{blue}{\frac{x}{p}}, 0.5\right)} \]
        5. Applied rewrites100.0%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}} \]

        if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

        1. Initial program 100.0%

          \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
          2. lift-+.f64N/A

            \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
          3. +-commutativeN/A

            \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
          4. distribute-lft-inN/A

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
          5. *-commutativeN/A

            \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
          6. lift-/.f64N/A

            \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
          7. div-invN/A

            \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
          8. associate-*l*N/A

            \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
          9. *-commutativeN/A

            \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
          10. metadata-evalN/A

            \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
          11. lower-fma.f64N/A

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
        4. Applied rewrites100.0%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
        5. Applied rewrites100.0%

          \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{1}{\mathsf{fma}\left(0.5, \frac{x}{\sqrt{\mathsf{fma}\left(p, p \cdot 4, x \cdot x\right)}}, 0.5\right)}}}} \]
        6. Taylor expanded in x around inf

          \[\leadsto \frac{1}{\sqrt{\color{blue}{1 + \frac{{p}^{2}}{{x}^{2}}}}} \]
        7. Step-by-step derivation
          1. lower-+.f64N/A

            \[\leadsto \frac{1}{\sqrt{\color{blue}{1 + \frac{{p}^{2}}{{x}^{2}}}}} \]
          2. lower-/.f64N/A

            \[\leadsto \frac{1}{\sqrt{1 + \color{blue}{\frac{{p}^{2}}{{x}^{2}}}}} \]
          3. unpow2N/A

            \[\leadsto \frac{1}{\sqrt{1 + \frac{\color{blue}{p \cdot p}}{{x}^{2}}}} \]
          4. lower-*.f64N/A

            \[\leadsto \frac{1}{\sqrt{1 + \frac{\color{blue}{p \cdot p}}{{x}^{2}}}} \]
          5. unpow2N/A

            \[\leadsto \frac{1}{\sqrt{1 + \frac{p \cdot p}{\color{blue}{x \cdot x}}}} \]
          6. lower-*.f6498.6

            \[\leadsto \frac{1}{\sqrt{1 + \frac{p \cdot p}{\color{blue}{x \cdot x}}}} \]
        8. Applied rewrites98.6%

          \[\leadsto \frac{1}{\sqrt{\color{blue}{1 + \frac{p \cdot p}{x \cdot x}}}} \]
      9. Recombined 3 regimes into one program.
      10. Final simplification90.6%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\sqrt{1 + \frac{p \cdot p}{x \cdot x}}}\\ \end{array} \]
      11. Add Preprocessing

      Alternative 3: 98.4% accurate, 0.4× speedup?

      \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{fma}\left(p\_m \cdot p\_m, \frac{0.5}{x \cdot x}, 1\right)}\\ \end{array} \end{array} \]
      p_m = (fabs.f64 p)
      (FPCore (p_m x)
       :precision binary64
       (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
         (if (<= t_0 -0.5)
           (/ (fma (/ -1.5 (* x x)) (* p_m (* p_m p_m)) p_m) (- x))
           (if (<= t_0 2e-16)
             (sqrt (fma 0.25 (/ x p_m) 0.5))
             (/ 1.0 (fma (* p_m p_m) (/ 0.5 (* x x)) 1.0))))))
      p_m = fabs(p);
      double code(double p_m, double x) {
      	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
      	double tmp;
      	if (t_0 <= -0.5) {
      		tmp = fma((-1.5 / (x * x)), (p_m * (p_m * p_m)), p_m) / -x;
      	} else if (t_0 <= 2e-16) {
      		tmp = sqrt(fma(0.25, (x / p_m), 0.5));
      	} else {
      		tmp = 1.0 / fma((p_m * p_m), (0.5 / (x * x)), 1.0);
      	}
      	return tmp;
      }
      
      p_m = abs(p)
      function code(p_m, x)
      	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
      	tmp = 0.0
      	if (t_0 <= -0.5)
      		tmp = Float64(fma(Float64(-1.5 / Float64(x * x)), Float64(p_m * Float64(p_m * p_m)), p_m) / Float64(-x));
      	elseif (t_0 <= 2e-16)
      		tmp = sqrt(fma(0.25, Float64(x / p_m), 0.5));
      	else
      		tmp = Float64(1.0 / fma(Float64(p_m * p_m), Float64(0.5 / Float64(x * x)), 1.0));
      	end
      	return tmp
      end
      
      p_m = N[Abs[p], $MachinePrecision]
      code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(N[(N[(-1.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(p$95$m * N[(p$95$m * p$95$m), $MachinePrecision]), $MachinePrecision] + p$95$m), $MachinePrecision] / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[N[(0.25 * N[(x / p$95$m), $MachinePrecision] + 0.5), $MachinePrecision]], $MachinePrecision], N[(1.0 / N[(N[(p$95$m * p$95$m), $MachinePrecision] * N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]]]]
      
      \begin{array}{l}
      p_m = \left|p\right|
      
      \\
      \begin{array}{l}
      t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
      \mathbf{if}\;t\_0 \leq -0.5:\\
      \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\
      
      \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
      \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\
      
      \mathbf{else}:\\
      \;\;\;\;\frac{1}{\mathsf{fma}\left(p\_m \cdot p\_m, \frac{0.5}{x \cdot x}, 1\right)}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 3 regimes
      2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

        1. Initial program 18.1%

          \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
          2. lift-+.f64N/A

            \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
          3. +-commutativeN/A

            \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
          4. distribute-lft-inN/A

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
          5. *-commutativeN/A

            \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
          6. lift-/.f64N/A

            \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
          7. div-invN/A

            \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
          8. associate-*l*N/A

            \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
          9. *-commutativeN/A

            \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
          10. metadata-evalN/A

            \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
          11. lower-fma.f64N/A

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
        4. Applied rewrites3.5%

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
        5. Taylor expanded in x around -inf

          \[\leadsto \color{blue}{-1 \cdot \frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}} \]
        6. Step-by-step derivation
          1. mul-1-negN/A

            \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
          2. lower-neg.f64N/A

            \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
          3. lower-/.f64N/A

            \[\leadsto \mathsf{neg}\left(\color{blue}{\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}}\right) \]
        7. Applied rewrites47.6%

          \[\leadsto \color{blue}{-\frac{\mathsf{fma}\left(0.125, \frac{\left(\left(p \cdot p\right) \cdot \left(p \cdot p\right)\right) \cdot -12}{p \cdot \left(x \cdot x\right)}, p\right)}{x}} \]
        8. Step-by-step derivation
          1. Applied rewrites58.8%

            \[\leadsto \frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{\color{blue}{-x}} \]

          if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in x around 0

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} + \frac{1}{4} \cdot \frac{x}{p}}} \]
          4. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{4} \cdot \frac{x}{p} + \frac{1}{2}}} \]
            2. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{4}, \frac{x}{p}, \frac{1}{2}\right)}} \]
            3. lower-/.f64100.0

              \[\leadsto \sqrt{\mathsf{fma}\left(0.25, \color{blue}{\frac{x}{p}}, 0.5\right)} \]
          5. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}} \]

          if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Applied rewrites100.0%

            \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{1}{\mathsf{fma}\left(0.5, \frac{x}{\sqrt{\mathsf{fma}\left(p, p \cdot 4, x \cdot x\right)}}, 0.5\right)}}}} \]
          6. Taylor expanded in x around inf

            \[\leadsto \frac{1}{\color{blue}{1 + \frac{1}{2} \cdot \frac{{p}^{2}}{{x}^{2}}}} \]
          7. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \frac{1}{\color{blue}{\frac{1}{2} \cdot \frac{{p}^{2}}{{x}^{2}} + 1}} \]
            2. *-commutativeN/A

              \[\leadsto \frac{1}{\color{blue}{\frac{{p}^{2}}{{x}^{2}} \cdot \frac{1}{2}} + 1} \]
            3. associate-*l/N/A

              \[\leadsto \frac{1}{\color{blue}{\frac{{p}^{2} \cdot \frac{1}{2}}{{x}^{2}}} + 1} \]
            4. associate-*r/N/A

              \[\leadsto \frac{1}{\color{blue}{{p}^{2} \cdot \frac{\frac{1}{2}}{{x}^{2}}} + 1} \]
            5. metadata-evalN/A

              \[\leadsto \frac{1}{{p}^{2} \cdot \frac{\color{blue}{\frac{1}{2} \cdot 1}}{{x}^{2}} + 1} \]
            6. associate-*r/N/A

              \[\leadsto \frac{1}{{p}^{2} \cdot \color{blue}{\left(\frac{1}{2} \cdot \frac{1}{{x}^{2}}\right)} + 1} \]
            7. lower-fma.f64N/A

              \[\leadsto \frac{1}{\color{blue}{\mathsf{fma}\left({p}^{2}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)}} \]
            8. unpow2N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(\color{blue}{p \cdot p}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)} \]
            9. lower-*.f64N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(\color{blue}{p \cdot p}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)} \]
            10. associate-*r/N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \color{blue}{\frac{\frac{1}{2} \cdot 1}{{x}^{2}}}, 1\right)} \]
            11. metadata-evalN/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{\color{blue}{\frac{1}{2}}}{{x}^{2}}, 1\right)} \]
            12. lower-/.f64N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \color{blue}{\frac{\frac{1}{2}}{{x}^{2}}}, 1\right)} \]
            13. unpow2N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{\frac{1}{2}}{\color{blue}{x \cdot x}}, 1\right)} \]
            14. lower-*.f6498.6

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{\color{blue}{x \cdot x}}, 1\right)} \]
          8. Applied rewrites98.6%

            \[\leadsto \frac{1}{\color{blue}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{x \cdot x}, 1\right)}} \]
        9. Recombined 3 regimes into one program.
        10. Final simplification90.6%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{x \cdot x}, 1\right)}\\ \end{array} \]
        11. Add Preprocessing

        Alternative 4: 98.6% accurate, 0.4× speedup?

        \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{p\_m}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{fma}\left(p\_m \cdot p\_m, \frac{0.5}{x \cdot x}, 1\right)}\\ \end{array} \end{array} \]
        p_m = (fabs.f64 p)
        (FPCore (p_m x)
         :precision binary64
         (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
           (if (<= t_0 -0.5)
             (/ p_m (- x))
             (if (<= t_0 2e-16)
               (sqrt (fma 0.25 (/ x p_m) 0.5))
               (/ 1.0 (fma (* p_m p_m) (/ 0.5 (* x x)) 1.0))))))
        p_m = fabs(p);
        double code(double p_m, double x) {
        	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
        	double tmp;
        	if (t_0 <= -0.5) {
        		tmp = p_m / -x;
        	} else if (t_0 <= 2e-16) {
        		tmp = sqrt(fma(0.25, (x / p_m), 0.5));
        	} else {
        		tmp = 1.0 / fma((p_m * p_m), (0.5 / (x * x)), 1.0);
        	}
        	return tmp;
        }
        
        p_m = abs(p)
        function code(p_m, x)
        	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
        	tmp = 0.0
        	if (t_0 <= -0.5)
        		tmp = Float64(p_m / Float64(-x));
        	elseif (t_0 <= 2e-16)
        		tmp = sqrt(fma(0.25, Float64(x / p_m), 0.5));
        	else
        		tmp = Float64(1.0 / fma(Float64(p_m * p_m), Float64(0.5 / Float64(x * x)), 1.0));
        	end
        	return tmp
        end
        
        p_m = N[Abs[p], $MachinePrecision]
        code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(p$95$m / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[N[(0.25 * N[(x / p$95$m), $MachinePrecision] + 0.5), $MachinePrecision]], $MachinePrecision], N[(1.0 / N[(N[(p$95$m * p$95$m), $MachinePrecision] * N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]]]]
        
        \begin{array}{l}
        p_m = \left|p\right|
        
        \\
        \begin{array}{l}
        t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
        \mathbf{if}\;t\_0 \leq -0.5:\\
        \;\;\;\;\frac{p\_m}{-x}\\
        
        \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
        \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\
        
        \mathbf{else}:\\
        \;\;\;\;\frac{1}{\mathsf{fma}\left(p\_m \cdot p\_m, \frac{0.5}{x \cdot x}, 1\right)}\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 3 regimes
        2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

          1. Initial program 18.1%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites3.5%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Taylor expanded in x around -inf

            \[\leadsto \color{blue}{-1 \cdot \frac{p}{x}} \]
          6. Step-by-step derivation
            1. mul-1-negN/A

              \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p}{x}\right)} \]
            2. distribute-neg-frac2N/A

              \[\leadsto \color{blue}{\frac{p}{\mathsf{neg}\left(x\right)}} \]
            3. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{-1 \cdot x}} \]
            4. lower-/.f64N/A

              \[\leadsto \color{blue}{\frac{p}{-1 \cdot x}} \]
            5. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{\mathsf{neg}\left(x\right)}} \]
            6. lower-neg.f6458.8

              \[\leadsto \frac{p}{\color{blue}{-x}} \]
          7. Applied rewrites58.8%

            \[\leadsto \color{blue}{\frac{p}{-x}} \]

          if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in x around 0

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} + \frac{1}{4} \cdot \frac{x}{p}}} \]
          4. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{4} \cdot \frac{x}{p} + \frac{1}{2}}} \]
            2. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{4}, \frac{x}{p}, \frac{1}{2}\right)}} \]
            3. lower-/.f64100.0

              \[\leadsto \sqrt{\mathsf{fma}\left(0.25, \color{blue}{\frac{x}{p}}, 0.5\right)} \]
          5. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}} \]

          if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Applied rewrites100.0%

            \[\leadsto \color{blue}{\frac{1}{\sqrt{\frac{1}{\mathsf{fma}\left(0.5, \frac{x}{\sqrt{\mathsf{fma}\left(p, p \cdot 4, x \cdot x\right)}}, 0.5\right)}}}} \]
          6. Taylor expanded in x around inf

            \[\leadsto \frac{1}{\color{blue}{1 + \frac{1}{2} \cdot \frac{{p}^{2}}{{x}^{2}}}} \]
          7. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \frac{1}{\color{blue}{\frac{1}{2} \cdot \frac{{p}^{2}}{{x}^{2}} + 1}} \]
            2. *-commutativeN/A

              \[\leadsto \frac{1}{\color{blue}{\frac{{p}^{2}}{{x}^{2}} \cdot \frac{1}{2}} + 1} \]
            3. associate-*l/N/A

              \[\leadsto \frac{1}{\color{blue}{\frac{{p}^{2} \cdot \frac{1}{2}}{{x}^{2}}} + 1} \]
            4. associate-*r/N/A

              \[\leadsto \frac{1}{\color{blue}{{p}^{2} \cdot \frac{\frac{1}{2}}{{x}^{2}}} + 1} \]
            5. metadata-evalN/A

              \[\leadsto \frac{1}{{p}^{2} \cdot \frac{\color{blue}{\frac{1}{2} \cdot 1}}{{x}^{2}} + 1} \]
            6. associate-*r/N/A

              \[\leadsto \frac{1}{{p}^{2} \cdot \color{blue}{\left(\frac{1}{2} \cdot \frac{1}{{x}^{2}}\right)} + 1} \]
            7. lower-fma.f64N/A

              \[\leadsto \frac{1}{\color{blue}{\mathsf{fma}\left({p}^{2}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)}} \]
            8. unpow2N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(\color{blue}{p \cdot p}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)} \]
            9. lower-*.f64N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(\color{blue}{p \cdot p}, \frac{1}{2} \cdot \frac{1}{{x}^{2}}, 1\right)} \]
            10. associate-*r/N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \color{blue}{\frac{\frac{1}{2} \cdot 1}{{x}^{2}}}, 1\right)} \]
            11. metadata-evalN/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{\color{blue}{\frac{1}{2}}}{{x}^{2}}, 1\right)} \]
            12. lower-/.f64N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \color{blue}{\frac{\frac{1}{2}}{{x}^{2}}}, 1\right)} \]
            13. unpow2N/A

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{\frac{1}{2}}{\color{blue}{x \cdot x}}, 1\right)} \]
            14. lower-*.f6498.6

              \[\leadsto \frac{1}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{\color{blue}{x \cdot x}}, 1\right)} \]
          8. Applied rewrites98.6%

            \[\leadsto \frac{1}{\color{blue}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{x \cdot x}, 1\right)}} \]
        3. Recombined 3 regimes into one program.
        4. Final simplification90.6%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{p}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{fma}\left(p \cdot p, \frac{0.5}{x \cdot x}, 1\right)}\\ \end{array} \]
        5. Add Preprocessing

        Alternative 5: 98.5% accurate, 0.5× speedup?

        \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{p\_m}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p\_m \cdot p\_m}{x \cdot x}, 1\right)\\ \end{array} \end{array} \]
        p_m = (fabs.f64 p)
        (FPCore (p_m x)
         :precision binary64
         (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
           (if (<= t_0 -0.5)
             (/ p_m (- x))
             (if (<= t_0 2e-16)
               (sqrt (fma 0.25 (/ x p_m) 0.5))
               (fma -0.5 (/ (* p_m p_m) (* x x)) 1.0)))))
        p_m = fabs(p);
        double code(double p_m, double x) {
        	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
        	double tmp;
        	if (t_0 <= -0.5) {
        		tmp = p_m / -x;
        	} else if (t_0 <= 2e-16) {
        		tmp = sqrt(fma(0.25, (x / p_m), 0.5));
        	} else {
        		tmp = fma(-0.5, ((p_m * p_m) / (x * x)), 1.0);
        	}
        	return tmp;
        }
        
        p_m = abs(p)
        function code(p_m, x)
        	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
        	tmp = 0.0
        	if (t_0 <= -0.5)
        		tmp = Float64(p_m / Float64(-x));
        	elseif (t_0 <= 2e-16)
        		tmp = sqrt(fma(0.25, Float64(x / p_m), 0.5));
        	else
        		tmp = fma(-0.5, Float64(Float64(p_m * p_m) / Float64(x * x)), 1.0);
        	end
        	return tmp
        end
        
        p_m = N[Abs[p], $MachinePrecision]
        code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(p$95$m / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[N[(0.25 * N[(x / p$95$m), $MachinePrecision] + 0.5), $MachinePrecision]], $MachinePrecision], N[(-0.5 * N[(N[(p$95$m * p$95$m), $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]]]]
        
        \begin{array}{l}
        p_m = \left|p\right|
        
        \\
        \begin{array}{l}
        t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
        \mathbf{if}\;t\_0 \leq -0.5:\\
        \;\;\;\;\frac{p\_m}{-x}\\
        
        \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
        \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p\_m}, 0.5\right)}\\
        
        \mathbf{else}:\\
        \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p\_m \cdot p\_m}{x \cdot x}, 1\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 3 regimes
        2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

          1. Initial program 18.1%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites3.5%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Taylor expanded in x around -inf

            \[\leadsto \color{blue}{-1 \cdot \frac{p}{x}} \]
          6. Step-by-step derivation
            1. mul-1-negN/A

              \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p}{x}\right)} \]
            2. distribute-neg-frac2N/A

              \[\leadsto \color{blue}{\frac{p}{\mathsf{neg}\left(x\right)}} \]
            3. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{-1 \cdot x}} \]
            4. lower-/.f64N/A

              \[\leadsto \color{blue}{\frac{p}{-1 \cdot x}} \]
            5. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{\mathsf{neg}\left(x\right)}} \]
            6. lower-neg.f6458.8

              \[\leadsto \frac{p}{\color{blue}{-x}} \]
          7. Applied rewrites58.8%

            \[\leadsto \color{blue}{\frac{p}{-x}} \]

          if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in x around 0

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2} + \frac{1}{4} \cdot \frac{x}{p}}} \]
          4. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{4} \cdot \frac{x}{p} + \frac{1}{2}}} \]
            2. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{4}, \frac{x}{p}, \frac{1}{2}\right)}} \]
            3. lower-/.f64100.0

              \[\leadsto \sqrt{\mathsf{fma}\left(0.25, \color{blue}{\frac{x}{p}}, 0.5\right)} \]
          5. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}} \]

          if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites100.0%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Taylor expanded in x around inf

            \[\leadsto \color{blue}{1 + \frac{-1}{2} \cdot \frac{{p}^{2}}{{x}^{2}}} \]
          6. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \color{blue}{\frac{-1}{2} \cdot \frac{{p}^{2}}{{x}^{2}} + 1} \]
            2. lower-fma.f64N/A

              \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{-1}{2}, \frac{{p}^{2}}{{x}^{2}}, 1\right)} \]
            3. lower-/.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \color{blue}{\frac{{p}^{2}}{{x}^{2}}}, 1\right) \]
            4. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{\color{blue}{p \cdot p}}{{x}^{2}}, 1\right) \]
            5. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{\color{blue}{p \cdot p}}{{x}^{2}}, 1\right) \]
            6. unpow2N/A

              \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{p \cdot p}{\color{blue}{x \cdot x}}, 1\right) \]
            7. lower-*.f6498.5

              \[\leadsto \mathsf{fma}\left(-0.5, \frac{p \cdot p}{\color{blue}{x \cdot x}}, 1\right) \]
          7. Applied rewrites98.5%

            \[\leadsto \color{blue}{\mathsf{fma}\left(-0.5, \frac{p \cdot p}{x \cdot x}, 1\right)} \]
        3. Recombined 3 regimes into one program.
        4. Final simplification90.6%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{p}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(0.25, \frac{x}{p}, 0.5\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p \cdot p}{x \cdot x}, 1\right)\\ \end{array} \]
        5. Add Preprocessing

        Alternative 6: 98.1% accurate, 0.5× speedup?

        \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{p\_m}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p\_m \cdot p\_m}{x \cdot x}, 1\right)\\ \end{array} \end{array} \]
        p_m = (fabs.f64 p)
        (FPCore (p_m x)
         :precision binary64
         (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
           (if (<= t_0 -0.5)
             (/ p_m (- x))
             (if (<= t_0 2e-16) (sqrt 0.5) (fma -0.5 (/ (* p_m p_m) (* x x)) 1.0)))))
        p_m = fabs(p);
        double code(double p_m, double x) {
        	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
        	double tmp;
        	if (t_0 <= -0.5) {
        		tmp = p_m / -x;
        	} else if (t_0 <= 2e-16) {
        		tmp = sqrt(0.5);
        	} else {
        		tmp = fma(-0.5, ((p_m * p_m) / (x * x)), 1.0);
        	}
        	return tmp;
        }
        
        p_m = abs(p)
        function code(p_m, x)
        	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
        	tmp = 0.0
        	if (t_0 <= -0.5)
        		tmp = Float64(p_m / Float64(-x));
        	elseif (t_0 <= 2e-16)
        		tmp = sqrt(0.5);
        	else
        		tmp = fma(-0.5, Float64(Float64(p_m * p_m) / Float64(x * x)), 1.0);
        	end
        	return tmp
        end
        
        p_m = N[Abs[p], $MachinePrecision]
        code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(p$95$m / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[0.5], $MachinePrecision], N[(-0.5 * N[(N[(p$95$m * p$95$m), $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]]]]
        
        \begin{array}{l}
        p_m = \left|p\right|
        
        \\
        \begin{array}{l}
        t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
        \mathbf{if}\;t\_0 \leq -0.5:\\
        \;\;\;\;\frac{p\_m}{-x}\\
        
        \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
        \;\;\;\;\sqrt{0.5}\\
        
        \mathbf{else}:\\
        \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p\_m \cdot p\_m}{x \cdot x}, 1\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 3 regimes
        2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

          1. Initial program 18.1%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            2. lift-+.f64N/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
            3. +-commutativeN/A

              \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
            4. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
            5. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
            6. lift-/.f64N/A

              \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            7. div-invN/A

              \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
            8. associate-*l*N/A

              \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
            9. *-commutativeN/A

              \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
            10. metadata-evalN/A

              \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
            11. lower-fma.f64N/A

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
          4. Applied rewrites3.5%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
          5. Taylor expanded in x around -inf

            \[\leadsto \color{blue}{-1 \cdot \frac{p}{x}} \]
          6. Step-by-step derivation
            1. mul-1-negN/A

              \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p}{x}\right)} \]
            2. distribute-neg-frac2N/A

              \[\leadsto \color{blue}{\frac{p}{\mathsf{neg}\left(x\right)}} \]
            3. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{-1 \cdot x}} \]
            4. lower-/.f64N/A

              \[\leadsto \color{blue}{\frac{p}{-1 \cdot x}} \]
            5. mul-1-negN/A

              \[\leadsto \frac{p}{\color{blue}{\mathsf{neg}\left(x\right)}} \]
            6. lower-neg.f6458.8

              \[\leadsto \frac{p}{\color{blue}{-x}} \]
          7. Applied rewrites58.8%

            \[\leadsto \color{blue}{\frac{p}{-x}} \]

          if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

          1. Initial program 100.0%

            \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in x around 0

            \[\leadsto \sqrt{\color{blue}{\frac{1}{2}}} \]
          4. Step-by-step derivation
            1. Applied rewrites99.8%

              \[\leadsto \sqrt{\color{blue}{0.5}} \]

            if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

            1. Initial program 100.0%

              \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-*.f64N/A

                \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
              2. lift-+.f64N/A

                \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
              3. +-commutativeN/A

                \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
              4. distribute-lft-inN/A

                \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
              5. *-commutativeN/A

                \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
              6. lift-/.f64N/A

                \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
              7. div-invN/A

                \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
              8. associate-*l*N/A

                \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
              9. *-commutativeN/A

                \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
              10. metadata-evalN/A

                \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
              11. lower-fma.f64N/A

                \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
            4. Applied rewrites100.0%

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
            5. Taylor expanded in x around inf

              \[\leadsto \color{blue}{1 + \frac{-1}{2} \cdot \frac{{p}^{2}}{{x}^{2}}} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \color{blue}{\frac{-1}{2} \cdot \frac{{p}^{2}}{{x}^{2}} + 1} \]
              2. lower-fma.f64N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{-1}{2}, \frac{{p}^{2}}{{x}^{2}}, 1\right)} \]
              3. lower-/.f64N/A

                \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \color{blue}{\frac{{p}^{2}}{{x}^{2}}}, 1\right) \]
              4. unpow2N/A

                \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{\color{blue}{p \cdot p}}{{x}^{2}}, 1\right) \]
              5. lower-*.f64N/A

                \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{\color{blue}{p \cdot p}}{{x}^{2}}, 1\right) \]
              6. unpow2N/A

                \[\leadsto \mathsf{fma}\left(\frac{-1}{2}, \frac{p \cdot p}{\color{blue}{x \cdot x}}, 1\right) \]
              7. lower-*.f6498.5

                \[\leadsto \mathsf{fma}\left(-0.5, \frac{p \cdot p}{\color{blue}{x \cdot x}}, 1\right) \]
            7. Applied rewrites98.5%

              \[\leadsto \color{blue}{\mathsf{fma}\left(-0.5, \frac{p \cdot p}{x \cdot x}, 1\right)} \]
          5. Recombined 3 regimes into one program.
          6. Final simplification90.5%

            \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{p}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.5, \frac{p \cdot p}{x \cdot x}, 1\right)\\ \end{array} \]
          7. Add Preprocessing

          Alternative 7: 98.2% accurate, 0.6× speedup?

          \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\ \mathbf{if}\;t\_0 \leq -0.5:\\ \;\;\;\;\frac{p\_m}{-x}\\ \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \end{array} \]
          p_m = (fabs.f64 p)
          (FPCore (p_m x)
           :precision binary64
           (let* ((t_0 (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x))))))
             (if (<= t_0 -0.5) (/ p_m (- x)) (if (<= t_0 2e-16) (sqrt 0.5) 1.0))))
          p_m = fabs(p);
          double code(double p_m, double x) {
          	double t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
          	double tmp;
          	if (t_0 <= -0.5) {
          		tmp = p_m / -x;
          	} else if (t_0 <= 2e-16) {
          		tmp = sqrt(0.5);
          	} else {
          		tmp = 1.0;
          	}
          	return tmp;
          }
          
          p_m = abs(p)
          real(8) function code(p_m, x)
              real(8), intent (in) :: p_m
              real(8), intent (in) :: x
              real(8) :: t_0
              real(8) :: tmp
              t_0 = x / sqrt(((p_m * (4.0d0 * p_m)) + (x * x)))
              if (t_0 <= (-0.5d0)) then
                  tmp = p_m / -x
              else if (t_0 <= 2d-16) then
                  tmp = sqrt(0.5d0)
              else
                  tmp = 1.0d0
              end if
              code = tmp
          end function
          
          p_m = Math.abs(p);
          public static double code(double p_m, double x) {
          	double t_0 = x / Math.sqrt(((p_m * (4.0 * p_m)) + (x * x)));
          	double tmp;
          	if (t_0 <= -0.5) {
          		tmp = p_m / -x;
          	} else if (t_0 <= 2e-16) {
          		tmp = Math.sqrt(0.5);
          	} else {
          		tmp = 1.0;
          	}
          	return tmp;
          }
          
          p_m = math.fabs(p)
          def code(p_m, x):
          	t_0 = x / math.sqrt(((p_m * (4.0 * p_m)) + (x * x)))
          	tmp = 0
          	if t_0 <= -0.5:
          		tmp = p_m / -x
          	elif t_0 <= 2e-16:
          		tmp = math.sqrt(0.5)
          	else:
          		tmp = 1.0
          	return tmp
          
          p_m = abs(p)
          function code(p_m, x)
          	t_0 = Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x))))
          	tmp = 0.0
          	if (t_0 <= -0.5)
          		tmp = Float64(p_m / Float64(-x));
          	elseif (t_0 <= 2e-16)
          		tmp = sqrt(0.5);
          	else
          		tmp = 1.0;
          	end
          	return tmp
          end
          
          p_m = abs(p);
          function tmp_2 = code(p_m, x)
          	t_0 = x / sqrt(((p_m * (4.0 * p_m)) + (x * x)));
          	tmp = 0.0;
          	if (t_0 <= -0.5)
          		tmp = p_m / -x;
          	elseif (t_0 <= 2e-16)
          		tmp = sqrt(0.5);
          	else
          		tmp = 1.0;
          	end
          	tmp_2 = tmp;
          end
          
          p_m = N[Abs[p], $MachinePrecision]
          code[p$95$m_, x_] := Block[{t$95$0 = N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.5], N[(p$95$m / (-x)), $MachinePrecision], If[LessEqual[t$95$0, 2e-16], N[Sqrt[0.5], $MachinePrecision], 1.0]]]
          
          \begin{array}{l}
          p_m = \left|p\right|
          
          \\
          \begin{array}{l}
          t_0 := \frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}}\\
          \mathbf{if}\;t\_0 \leq -0.5:\\
          \;\;\;\;\frac{p\_m}{-x}\\
          
          \mathbf{elif}\;t\_0 \leq 2 \cdot 10^{-16}:\\
          \;\;\;\;\sqrt{0.5}\\
          
          \mathbf{else}:\\
          \;\;\;\;1\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 3 regimes
          2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

            1. Initial program 18.1%

              \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-*.f64N/A

                \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
              2. lift-+.f64N/A

                \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
              3. +-commutativeN/A

                \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
              4. distribute-lft-inN/A

                \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
              5. *-commutativeN/A

                \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
              6. lift-/.f64N/A

                \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
              7. div-invN/A

                \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
              8. associate-*l*N/A

                \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
              9. *-commutativeN/A

                \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
              10. metadata-evalN/A

                \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
              11. lower-fma.f64N/A

                \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
            4. Applied rewrites3.5%

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
            5. Taylor expanded in x around -inf

              \[\leadsto \color{blue}{-1 \cdot \frac{p}{x}} \]
            6. Step-by-step derivation
              1. mul-1-negN/A

                \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p}{x}\right)} \]
              2. distribute-neg-frac2N/A

                \[\leadsto \color{blue}{\frac{p}{\mathsf{neg}\left(x\right)}} \]
              3. mul-1-negN/A

                \[\leadsto \frac{p}{\color{blue}{-1 \cdot x}} \]
              4. lower-/.f64N/A

                \[\leadsto \color{blue}{\frac{p}{-1 \cdot x}} \]
              5. mul-1-negN/A

                \[\leadsto \frac{p}{\color{blue}{\mathsf{neg}\left(x\right)}} \]
              6. lower-neg.f6458.8

                \[\leadsto \frac{p}{\color{blue}{-x}} \]
            7. Applied rewrites58.8%

              \[\leadsto \color{blue}{\frac{p}{-x}} \]

            if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 2e-16

            1. Initial program 100.0%

              \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
            2. Add Preprocessing
            3. Taylor expanded in x around 0

              \[\leadsto \sqrt{\color{blue}{\frac{1}{2}}} \]
            4. Step-by-step derivation
              1. Applied rewrites99.8%

                \[\leadsto \sqrt{\color{blue}{0.5}} \]

              if 2e-16 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

              1. Initial program 100.0%

                \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-*.f64N/A

                  \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                2. lift-+.f64N/A

                  \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                3. +-commutativeN/A

                  \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
                4. distribute-lft-inN/A

                  \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
                5. *-commutativeN/A

                  \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
                6. lift-/.f64N/A

                  \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                7. div-invN/A

                  \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                8. associate-*l*N/A

                  \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
                9. *-commutativeN/A

                  \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
                10. metadata-evalN/A

                  \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
                11. lower-fma.f64N/A

                  \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
              4. Applied rewrites100.0%

                \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
              5. Taylor expanded in x around inf

                \[\leadsto \color{blue}{1} \]
              6. Step-by-step derivation
                1. Applied rewrites97.9%

                  \[\leadsto \color{blue}{1} \]
              7. Recombined 3 regimes into one program.
              8. Final simplification90.3%

                \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{p}{-x}\\ \mathbf{elif}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 2 \cdot 10^{-16}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
              9. Add Preprocessing

              Alternative 8: 98.6% accurate, 0.6× speedup?

              \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\mathsf{fma}\left(2, \frac{p\_m \cdot p\_m}{x}, x\right)}, x, 0.5\right)}\\ \end{array} \end{array} \]
              p_m = (fabs.f64 p)
              (FPCore (p_m x)
               :precision binary64
               (if (<= (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x)))) -0.5)
                 (/ (fma (/ -1.5 (* x x)) (* p_m (* p_m p_m)) p_m) (- x))
                 (sqrt (fma (/ 0.5 (fma 2.0 (/ (* p_m p_m) x) x)) x 0.5))))
              p_m = fabs(p);
              double code(double p_m, double x) {
              	double tmp;
              	if ((x / sqrt(((p_m * (4.0 * p_m)) + (x * x)))) <= -0.5) {
              		tmp = fma((-1.5 / (x * x)), (p_m * (p_m * p_m)), p_m) / -x;
              	} else {
              		tmp = sqrt(fma((0.5 / fma(2.0, ((p_m * p_m) / x), x)), x, 0.5));
              	}
              	return tmp;
              }
              
              p_m = abs(p)
              function code(p_m, x)
              	tmp = 0.0
              	if (Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x)))) <= -0.5)
              		tmp = Float64(fma(Float64(-1.5 / Float64(x * x)), Float64(p_m * Float64(p_m * p_m)), p_m) / Float64(-x));
              	else
              		tmp = sqrt(fma(Float64(0.5 / fma(2.0, Float64(Float64(p_m * p_m) / x), x)), x, 0.5));
              	end
              	return tmp
              end
              
              p_m = N[Abs[p], $MachinePrecision]
              code[p$95$m_, x_] := If[LessEqual[N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], -0.5], N[(N[(N[(-1.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(p$95$m * N[(p$95$m * p$95$m), $MachinePrecision]), $MachinePrecision] + p$95$m), $MachinePrecision] / (-x)), $MachinePrecision], N[Sqrt[N[(N[(0.5 / N[(2.0 * N[(N[(p$95$m * p$95$m), $MachinePrecision] / x), $MachinePrecision] + x), $MachinePrecision]), $MachinePrecision] * x + 0.5), $MachinePrecision]], $MachinePrecision]]
              
              \begin{array}{l}
              p_m = \left|p\right|
              
              \\
              \begin{array}{l}
              \mathbf{if}\;\frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}} \leq -0.5:\\
              \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p\_m \cdot \left(p\_m \cdot p\_m\right), p\_m\right)}{-x}\\
              
              \mathbf{else}:\\
              \;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\mathsf{fma}\left(2, \frac{p\_m \cdot p\_m}{x}, x\right)}, x, 0.5\right)}\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < -0.5

                1. Initial program 18.1%

                  \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
                2. Add Preprocessing
                3. Step-by-step derivation
                  1. lift-*.f64N/A

                    \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                  2. lift-+.f64N/A

                    \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                  3. +-commutativeN/A

                    \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
                  4. distribute-lft-inN/A

                    \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
                  5. *-commutativeN/A

                    \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
                  6. lift-/.f64N/A

                    \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                  7. div-invN/A

                    \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                  8. associate-*l*N/A

                    \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
                  9. *-commutativeN/A

                    \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
                  10. metadata-evalN/A

                    \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
                  11. lower-fma.f64N/A

                    \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
                4. Applied rewrites3.5%

                  \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
                5. Taylor expanded in x around -inf

                  \[\leadsto \color{blue}{-1 \cdot \frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}} \]
                6. Step-by-step derivation
                  1. mul-1-negN/A

                    \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
                  2. lower-neg.f64N/A

                    \[\leadsto \color{blue}{\mathsf{neg}\left(\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}\right)} \]
                  3. lower-/.f64N/A

                    \[\leadsto \mathsf{neg}\left(\color{blue}{\frac{p + \frac{1}{8} \cdot \frac{-16 \cdot {p}^{4} + 4 \cdot {p}^{4}}{p \cdot {x}^{2}}}{x}}\right) \]
                7. Applied rewrites47.6%

                  \[\leadsto \color{blue}{-\frac{\mathsf{fma}\left(0.125, \frac{\left(\left(p \cdot p\right) \cdot \left(p \cdot p\right)\right) \cdot -12}{p \cdot \left(x \cdot x\right)}, p\right)}{x}} \]
                8. Step-by-step derivation
                  1. Applied rewrites58.8%

                    \[\leadsto \frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{\color{blue}{-x}} \]

                  if -0.5 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

                  1. Initial program 100.0%

                    \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
                  2. Add Preprocessing
                  3. Step-by-step derivation
                    1. lift-*.f64N/A

                      \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                    2. lift-+.f64N/A

                      \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                    3. +-commutativeN/A

                      \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
                    4. distribute-lft-inN/A

                      \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
                    5. *-commutativeN/A

                      \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
                    6. lift-/.f64N/A

                      \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                    7. div-invN/A

                      \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                    8. associate-*l*N/A

                      \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
                    9. *-commutativeN/A

                      \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
                    10. metadata-evalN/A

                      \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
                    11. lower-fma.f64N/A

                      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
                  4. Applied rewrites100.0%

                    \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
                  5. Taylor expanded in p around 0

                    \[\leadsto \sqrt{\mathsf{fma}\left(\frac{\frac{1}{2}}{\color{blue}{x + 2 \cdot \frac{{p}^{2}}{x}}}, x, \frac{1}{2}\right)} \]
                  6. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto \sqrt{\mathsf{fma}\left(\frac{\frac{1}{2}}{\color{blue}{2 \cdot \frac{{p}^{2}}{x} + x}}, x, \frac{1}{2}\right)} \]
                    2. lower-fma.f64N/A

                      \[\leadsto \sqrt{\mathsf{fma}\left(\frac{\frac{1}{2}}{\color{blue}{\mathsf{fma}\left(2, \frac{{p}^{2}}{x}, x\right)}}, x, \frac{1}{2}\right)} \]
                    3. lower-/.f64N/A

                      \[\leadsto \sqrt{\mathsf{fma}\left(\frac{\frac{1}{2}}{\mathsf{fma}\left(2, \color{blue}{\frac{{p}^{2}}{x}}, x\right)}, x, \frac{1}{2}\right)} \]
                    4. unpow2N/A

                      \[\leadsto \sqrt{\mathsf{fma}\left(\frac{\frac{1}{2}}{\mathsf{fma}\left(2, \frac{\color{blue}{p \cdot p}}{x}, x\right)}, x, \frac{1}{2}\right)} \]
                    5. lower-*.f6499.4

                      \[\leadsto \sqrt{\mathsf{fma}\left(\frac{0.5}{\mathsf{fma}\left(2, \frac{\color{blue}{p \cdot p}}{x}, x\right)}, x, 0.5\right)} \]
                  7. Applied rewrites99.4%

                    \[\leadsto \sqrt{\mathsf{fma}\left(\frac{0.5}{\color{blue}{\mathsf{fma}\left(2, \frac{p \cdot p}{x}, x\right)}}, x, 0.5\right)} \]
                9. Recombined 2 regimes into one program.
                10. Final simplification90.5%

                  \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(\frac{-1.5}{x \cdot x}, p \cdot \left(p \cdot p\right), p\right)}{-x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(\frac{0.5}{\mathsf{fma}\left(2, \frac{p \cdot p}{x}, x\right)}, x, 0.5\right)}\\ \end{array} \]
                11. Add Preprocessing

                Alternative 9: 75.0% accurate, 1.0× speedup?

                \[\begin{array}{l} p_m = \left|p\right| \\ \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}} \leq 0.45:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \end{array} \]
                p_m = (fabs.f64 p)
                (FPCore (p_m x)
                 :precision binary64
                 (if (<= (/ x (sqrt (+ (* p_m (* 4.0 p_m)) (* x x)))) 0.45) (sqrt 0.5) 1.0))
                p_m = fabs(p);
                double code(double p_m, double x) {
                	double tmp;
                	if ((x / sqrt(((p_m * (4.0 * p_m)) + (x * x)))) <= 0.45) {
                		tmp = sqrt(0.5);
                	} else {
                		tmp = 1.0;
                	}
                	return tmp;
                }
                
                p_m = abs(p)
                real(8) function code(p_m, x)
                    real(8), intent (in) :: p_m
                    real(8), intent (in) :: x
                    real(8) :: tmp
                    if ((x / sqrt(((p_m * (4.0d0 * p_m)) + (x * x)))) <= 0.45d0) then
                        tmp = sqrt(0.5d0)
                    else
                        tmp = 1.0d0
                    end if
                    code = tmp
                end function
                
                p_m = Math.abs(p);
                public static double code(double p_m, double x) {
                	double tmp;
                	if ((x / Math.sqrt(((p_m * (4.0 * p_m)) + (x * x)))) <= 0.45) {
                		tmp = Math.sqrt(0.5);
                	} else {
                		tmp = 1.0;
                	}
                	return tmp;
                }
                
                p_m = math.fabs(p)
                def code(p_m, x):
                	tmp = 0
                	if (x / math.sqrt(((p_m * (4.0 * p_m)) + (x * x)))) <= 0.45:
                		tmp = math.sqrt(0.5)
                	else:
                		tmp = 1.0
                	return tmp
                
                p_m = abs(p)
                function code(p_m, x)
                	tmp = 0.0
                	if (Float64(x / sqrt(Float64(Float64(p_m * Float64(4.0 * p_m)) + Float64(x * x)))) <= 0.45)
                		tmp = sqrt(0.5);
                	else
                		tmp = 1.0;
                	end
                	return tmp
                end
                
                p_m = abs(p);
                function tmp_2 = code(p_m, x)
                	tmp = 0.0;
                	if ((x / sqrt(((p_m * (4.0 * p_m)) + (x * x)))) <= 0.45)
                		tmp = sqrt(0.5);
                	else
                		tmp = 1.0;
                	end
                	tmp_2 = tmp;
                end
                
                p_m = N[Abs[p], $MachinePrecision]
                code[p$95$m_, x_] := If[LessEqual[N[(x / N[Sqrt[N[(N[(p$95$m * N[(4.0 * p$95$m), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], 0.45], N[Sqrt[0.5], $MachinePrecision], 1.0]
                
                \begin{array}{l}
                p_m = \left|p\right|
                
                \\
                \begin{array}{l}
                \mathbf{if}\;\frac{x}{\sqrt{p\_m \cdot \left(4 \cdot p\_m\right) + x \cdot x}} \leq 0.45:\\
                \;\;\;\;\sqrt{0.5}\\
                
                \mathbf{else}:\\
                \;\;\;\;1\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x)))) < 0.450000000000000011

                  1. Initial program 75.2%

                    \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
                  2. Add Preprocessing
                  3. Taylor expanded in x around 0

                    \[\leadsto \sqrt{\color{blue}{\frac{1}{2}}} \]
                  4. Step-by-step derivation
                    1. Applied rewrites71.2%

                      \[\leadsto \sqrt{\color{blue}{0.5}} \]

                    if 0.450000000000000011 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 #s(literal 4 binary64) p) p) (*.f64 x x))))

                    1. Initial program 100.0%

                      \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
                    2. Add Preprocessing
                    3. Step-by-step derivation
                      1. lift-*.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                      2. lift-+.f64N/A

                        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                      3. +-commutativeN/A

                        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
                      4. distribute-lft-inN/A

                        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
                      5. *-commutativeN/A

                        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
                      6. lift-/.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                      7. div-invN/A

                        \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                      8. associate-*l*N/A

                        \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
                      9. *-commutativeN/A

                        \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
                      10. metadata-evalN/A

                        \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
                      11. lower-fma.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
                    4. Applied rewrites100.0%

                      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
                    5. Taylor expanded in x around inf

                      \[\leadsto \color{blue}{1} \]
                    6. Step-by-step derivation
                      1. Applied rewrites97.9%

                        \[\leadsto \color{blue}{1} \]
                    7. Recombined 2 regimes into one program.
                    8. Final simplification78.6%

                      \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq 0.45:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
                    9. Add Preprocessing

                    Alternative 10: 35.8% accurate, 58.0× speedup?

                    \[\begin{array}{l} p_m = \left|p\right| \\ 1 \end{array} \]
                    p_m = (fabs.f64 p)
                    (FPCore (p_m x) :precision binary64 1.0)
                    p_m = fabs(p);
                    double code(double p_m, double x) {
                    	return 1.0;
                    }
                    
                    p_m = abs(p)
                    real(8) function code(p_m, x)
                        real(8), intent (in) :: p_m
                        real(8), intent (in) :: x
                        code = 1.0d0
                    end function
                    
                    p_m = Math.abs(p);
                    public static double code(double p_m, double x) {
                    	return 1.0;
                    }
                    
                    p_m = math.fabs(p)
                    def code(p_m, x):
                    	return 1.0
                    
                    p_m = abs(p)
                    function code(p_m, x)
                    	return 1.0
                    end
                    
                    p_m = abs(p);
                    function tmp = code(p_m, x)
                    	tmp = 1.0;
                    end
                    
                    p_m = N[Abs[p], $MachinePrecision]
                    code[p$95$m_, x_] := 1.0
                    
                    \begin{array}{l}
                    p_m = \left|p\right|
                    
                    \\
                    1
                    \end{array}
                    
                    Derivation
                    1. Initial program 82.1%

                      \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]
                    2. Add Preprocessing
                    3. Step-by-step derivation
                      1. lift-*.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                      2. lift-+.f64N/A

                        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)}} \]
                      3. +-commutativeN/A

                        \[\leadsto \sqrt{\frac{1}{2} \cdot \color{blue}{\left(\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + 1\right)}} \]
                      4. distribute-lft-inN/A

                        \[\leadsto \sqrt{\color{blue}{\frac{1}{2} \cdot \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} + \frac{1}{2} \cdot 1}} \]
                      5. *-commutativeN/A

                        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}} + \frac{1}{2} \cdot 1} \]
                      6. lift-/.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                      7. div-invN/A

                        \[\leadsto \sqrt{\color{blue}{\left(x \cdot \frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \cdot \frac{1}{2} + \frac{1}{2} \cdot 1} \]
                      8. associate-*l*N/A

                        \[\leadsto \sqrt{\color{blue}{x \cdot \left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right)} + \frac{1}{2} \cdot 1} \]
                      9. *-commutativeN/A

                        \[\leadsto \sqrt{\color{blue}{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x} + \frac{1}{2} \cdot 1} \]
                      10. metadata-evalN/A

                        \[\leadsto \sqrt{\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}\right) \cdot x + \color{blue}{\frac{1}{2}}} \]
                      11. lower-fma.f64N/A

                        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{1}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}} \cdot \frac{1}{2}, x, \frac{1}{2}\right)}} \]
                    4. Applied rewrites78.9%

                      \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(\frac{0.5}{\sqrt{\mathsf{fma}\left(x, x, p \cdot \left(4 \cdot p\right)\right)}}, x, 0.5\right)}} \]
                    5. Taylor expanded in x around inf

                      \[\leadsto \color{blue}{1} \]
                    6. Step-by-step derivation
                      1. Applied rewrites38.4%

                        \[\leadsto \color{blue}{1} \]
                      2. Add Preprocessing

                      Developer Target 1: 79.4% accurate, 0.2× speedup?

                      \[\begin{array}{l} \\ \sqrt{0.5 + \frac{\mathsf{copysign}\left(0.5, x\right)}{\mathsf{hypot}\left(1, \frac{2 \cdot p}{x}\right)}} \end{array} \]
                      (FPCore (p x)
                       :precision binary64
                       (sqrt (+ 0.5 (/ (copysign 0.5 x) (hypot 1.0 (/ (* 2.0 p) x))))))
                      double code(double p, double x) {
                      	return sqrt((0.5 + (copysign(0.5, x) / hypot(1.0, ((2.0 * p) / x)))));
                      }
                      
                      public static double code(double p, double x) {
                      	return Math.sqrt((0.5 + (Math.copySign(0.5, x) / Math.hypot(1.0, ((2.0 * p) / x)))));
                      }
                      
                      def code(p, x):
                      	return math.sqrt((0.5 + (math.copysign(0.5, x) / math.hypot(1.0, ((2.0 * p) / x)))))
                      
                      function code(p, x)
                      	return sqrt(Float64(0.5 + Float64(copysign(0.5, x) / hypot(1.0, Float64(Float64(2.0 * p) / x)))))
                      end
                      
                      function tmp = code(p, x)
                      	tmp = sqrt((0.5 + ((sign(x) * abs(0.5)) / hypot(1.0, ((2.0 * p) / x)))));
                      end
                      
                      code[p_, x_] := N[Sqrt[N[(0.5 + N[(N[With[{TMP1 = Abs[0.5], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision] / N[Sqrt[1.0 ^ 2 + N[(N[(2.0 * p), $MachinePrecision] / x), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
                      
                      \begin{array}{l}
                      
                      \\
                      \sqrt{0.5 + \frac{\mathsf{copysign}\left(0.5, x\right)}{\mathsf{hypot}\left(1, \frac{2 \cdot p}{x}\right)}}
                      \end{array}
                      

                      Reproduce

                      ?
                      herbie shell --seed 2024238 
                      (FPCore (p x)
                        :name "Given's Rotation SVD example"
                        :precision binary64
                        :pre (and (< 1e-150 (fabs x)) (< (fabs x) 1e+150))
                      
                        :alt
                        (! :herbie-platform default (sqrt (+ 1/2 (/ (copysign 1/2 x) (hypot 1 (/ (* 2 p) x))))))
                      
                        (sqrt (* 0.5 (+ 1.0 (/ x (sqrt (+ (* (* 4.0 p) p) (* x x))))))))