Octave 3.8, jcobi/4

Percentage Accurate: 15.9% → 86.9%
Time: 14.7s
Alternatives: 8
Speedup: 115.0×

Specification

?
\[\left(\alpha > -1 \land \beta > -1\right) \land i > 1\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_2 := t\_1 \cdot t\_1\\ \frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1} \end{array} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (* i (+ (+ alpha beta) i)))
        (t_1 (+ (+ alpha beta) (* 2.0 i)))
        (t_2 (* t_1 t_1)))
   (/ (/ (* t_0 (+ (* beta alpha) t_0)) t_2) (- t_2 1.0))))
double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: t_2
    t_0 = i * ((alpha + beta) + i)
    t_1 = (alpha + beta) + (2.0d0 * i)
    t_2 = t_1 * t_1
    code = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0d0)
end function
public static double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
def code(alpha, beta, i):
	t_0 = i * ((alpha + beta) + i)
	t_1 = (alpha + beta) + (2.0 * i)
	t_2 = t_1 * t_1
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0)
function code(alpha, beta, i)
	t_0 = Float64(i * Float64(Float64(alpha + beta) + i))
	t_1 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
	t_2 = Float64(t_1 * t_1)
	return Float64(Float64(Float64(t_0 * Float64(Float64(beta * alpha) + t_0)) / t_2) / Float64(t_2 - 1.0))
end
function tmp = code(alpha, beta, i)
	t_0 = i * ((alpha + beta) + i);
	t_1 = (alpha + beta) + (2.0 * i);
	t_2 = t_1 * t_1;
	tmp = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[(N[(t$95$0 * N[(N[(beta * alpha), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision] / N[(t$95$2 - 1.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_2 := t\_1 \cdot t\_1\\
\frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1}
\end{array}
\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 8 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: 15.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_2 := t\_1 \cdot t\_1\\ \frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1} \end{array} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (* i (+ (+ alpha beta) i)))
        (t_1 (+ (+ alpha beta) (* 2.0 i)))
        (t_2 (* t_1 t_1)))
   (/ (/ (* t_0 (+ (* beta alpha) t_0)) t_2) (- t_2 1.0))))
double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: t_2
    t_0 = i * ((alpha + beta) + i)
    t_1 = (alpha + beta) + (2.0d0 * i)
    t_2 = t_1 * t_1
    code = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0d0)
end function
public static double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
def code(alpha, beta, i):
	t_0 = i * ((alpha + beta) + i)
	t_1 = (alpha + beta) + (2.0 * i)
	t_2 = t_1 * t_1
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0)
function code(alpha, beta, i)
	t_0 = Float64(i * Float64(Float64(alpha + beta) + i))
	t_1 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
	t_2 = Float64(t_1 * t_1)
	return Float64(Float64(Float64(t_0 * Float64(Float64(beta * alpha) + t_0)) / t_2) / Float64(t_2 - 1.0))
end
function tmp = code(alpha, beta, i)
	t_0 = i * ((alpha + beta) + i);
	t_1 = (alpha + beta) + (2.0 * i);
	t_2 = t_1 * t_1;
	tmp = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[(N[(t$95$0 * N[(N[(beta * alpha), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision] / N[(t$95$2 - 1.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_2 := t\_1 \cdot t\_1\\
\frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1}
\end{array}
\end{array}

Alternative 1: 86.9% accurate, 1.9× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 1.35 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + 1\right)} \cdot \frac{i}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + -1\right)}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 1.35e+119)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (*
    (/ (+ i alpha) (+ alpha (+ (fma i 2.0 beta) 1.0)))
    (/ i (+ alpha (+ (fma i 2.0 beta) -1.0))))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 1.35e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = ((i + alpha) / (alpha + (fma(i, 2.0, beta) + 1.0))) * (i / (alpha + (fma(i, 2.0, beta) + -1.0)));
	}
	return tmp;
}
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 1.35e+119)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(Float64(Float64(i + alpha) / Float64(alpha + Float64(fma(i, 2.0, beta) + 1.0))) * Float64(i / Float64(alpha + Float64(fma(i, 2.0, beta) + -1.0))));
	end
	return tmp
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 1.35e+119], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / N[(alpha + N[(N[(i * 2.0 + beta), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(i / N[(alpha + N[(N[(i * 2.0 + beta), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 1.35 \cdot 10^{+119}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;\frac{i + \alpha}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + 1\right)} \cdot \frac{i}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + -1\right)}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 1.3499999999999999e119

    1. Initial program 21.7%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified17.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified78.2%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6478.3

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified78.3%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 1.3499999999999999e119 < beta

    1. Initial program 1.8%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in beta around inf

      \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    4. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      2. lower-+.f6431.1

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    5. Simplified31.1%

      \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    6. Applied egg-rr69.3%

      \[\leadsto \color{blue}{\frac{i + \alpha}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + 1\right)} \cdot \frac{i}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) - 1\right)}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification76.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 1.35 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + 1\right)} \cdot \frac{i}{\alpha + \left(\mathsf{fma}\left(i, 2, \beta\right) + -1\right)}\\ \end{array} \]
  5. Add Preprocessing

Alternative 2: 85.7% accurate, 2.7× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{1 + \left(\beta + \alpha\right)} \cdot \frac{i + \alpha}{\beta}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 2.9e+119)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (* (/ i (+ 1.0 (+ beta alpha))) (/ (+ i alpha) beta))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = (i / (1.0 + (beta + alpha))) * ((i + alpha) / beta);
	}
	return tmp;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: tmp
    if (beta <= 2.9d+119) then
        tmp = (0.015625d0 / (i * i)) + 0.0625d0
    else
        tmp = (i / (1.0d0 + (beta + alpha))) * ((i + alpha) / beta)
    end if
    code = tmp
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = (i / (1.0 + (beta + alpha))) * ((i + alpha) / beta);
	}
	return tmp;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	tmp = 0
	if beta <= 2.9e+119:
		tmp = (0.015625 / (i * i)) + 0.0625
	else:
		tmp = (i / (1.0 + (beta + alpha))) * ((i + alpha) / beta)
	return tmp
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 2.9e+119)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(Float64(i / Float64(1.0 + Float64(beta + alpha))) * Float64(Float64(i + alpha) / beta));
	end
	return tmp
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp_2 = code(alpha, beta, i)
	tmp = 0.0;
	if (beta <= 2.9e+119)
		tmp = (0.015625 / (i * i)) + 0.0625;
	else
		tmp = (i / (1.0 + (beta + alpha))) * ((i + alpha) / beta);
	end
	tmp_2 = tmp;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 2.9e+119], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(N[(i / N[(1.0 + N[(beta + alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;\frac{i}{1 + \left(\beta + \alpha\right)} \cdot \frac{i + \alpha}{\beta}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 2.90000000000000007e119

    1. Initial program 21.7%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified17.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified78.2%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6478.3

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified78.3%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 2.90000000000000007e119 < beta

    1. Initial program 1.8%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Applied egg-rr30.8%

      \[\leadsto \color{blue}{\frac{\frac{i \cdot \left(i + \left(\alpha + \beta\right)\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + 1} \cdot \frac{\frac{\mathsf{fma}\left(i, i + \left(\alpha + \beta\right), \alpha \cdot \beta\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + -1}} \]
    4. Taylor expanded in beta around inf

      \[\leadsto \frac{\frac{i \cdot \left(i + \left(\alpha + \beta\right)\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + 1} \cdot \color{blue}{\frac{\alpha + i}{\beta}} \]
    5. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{\frac{i \cdot \left(i + \left(\alpha + \beta\right)\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + 1} \cdot \color{blue}{\frac{\alpha + i}{\beta}} \]
      2. lower-+.f6431.2

        \[\leadsto \frac{\frac{i \cdot \left(i + \left(\alpha + \beta\right)\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + 1} \cdot \frac{\color{blue}{\alpha + i}}{\beta} \]
    6. Simplified31.2%

      \[\leadsto \frac{\frac{i \cdot \left(i + \left(\alpha + \beta\right)\right)}{\mathsf{fma}\left(i, 2, \alpha + \beta\right)}}{\mathsf{fma}\left(i, 2, \alpha + \beta\right) + 1} \cdot \color{blue}{\frac{\alpha + i}{\beta}} \]
    7. Taylor expanded in i around 0

      \[\leadsto \color{blue}{\frac{i}{1 + \left(\alpha + \beta\right)}} \cdot \frac{\alpha + i}{\beta} \]
    8. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{i}{1 + \left(\alpha + \beta\right)}} \cdot \frac{\alpha + i}{\beta} \]
      2. lower-+.f64N/A

        \[\leadsto \frac{i}{\color{blue}{1 + \left(\alpha + \beta\right)}} \cdot \frac{\alpha + i}{\beta} \]
      3. +-commutativeN/A

        \[\leadsto \frac{i}{1 + \color{blue}{\left(\beta + \alpha\right)}} \cdot \frac{\alpha + i}{\beta} \]
      4. lower-+.f6466.5

        \[\leadsto \frac{i}{1 + \color{blue}{\left(\beta + \alpha\right)}} \cdot \frac{\alpha + i}{\beta} \]
    9. Simplified66.5%

      \[\leadsto \color{blue}{\frac{i}{1 + \left(\beta + \alpha\right)}} \cdot \frac{\alpha + i}{\beta} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification75.6%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{1 + \left(\beta + \alpha\right)} \cdot \frac{i + \alpha}{\beta}\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 85.7% accurate, 3.1× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 2.9e+119)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (* (/ (+ i alpha) beta) (/ i beta))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = ((i + alpha) / beta) * (i / beta);
	}
	return tmp;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: tmp
    if (beta <= 2.9d+119) then
        tmp = (0.015625d0 / (i * i)) + 0.0625d0
    else
        tmp = ((i + alpha) / beta) * (i / beta)
    end if
    code = tmp
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = ((i + alpha) / beta) * (i / beta);
	}
	return tmp;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	tmp = 0
	if beta <= 2.9e+119:
		tmp = (0.015625 / (i * i)) + 0.0625
	else:
		tmp = ((i + alpha) / beta) * (i / beta)
	return tmp
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 2.9e+119)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(Float64(Float64(i + alpha) / beta) * Float64(i / beta));
	end
	return tmp
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp_2 = code(alpha, beta, i)
	tmp = 0.0;
	if (beta <= 2.9e+119)
		tmp = (0.015625 / (i * i)) + 0.0625;
	else
		tmp = ((i + alpha) / beta) * (i / beta);
	end
	tmp_2 = tmp;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 2.9e+119], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision] * N[(i / beta), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 2.90000000000000007e119

    1. Initial program 21.7%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified17.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified78.2%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6478.3

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified78.3%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 2.90000000000000007e119 < beta

    1. Initial program 1.8%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in beta around inf

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{{\beta}^{2}} \]
      3. lower-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{{\beta}^{2}} \]
      4. unpow2N/A

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
      5. lower-*.f6431.3

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
    5. Simplified31.3%

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{\beta \cdot \beta} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{\beta \cdot \beta} \]
      3. times-fracN/A

        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
      4. lower-*.f64N/A

        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
      6. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{\alpha + i}}{\beta} \cdot \frac{i}{\beta} \]
      7. +-commutativeN/A

        \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
      9. lower-/.f6466.4

        \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
    7. Applied egg-rr66.4%

      \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 4: 76.2% accurate, 3.4× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i \cdot i}{\beta}}{\beta}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 2.9e+119)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (/ (/ (* i i) beta) beta)))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = ((i * i) / beta) / beta;
	}
	return tmp;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: tmp
    if (beta <= 2.9d+119) then
        tmp = (0.015625d0 / (i * i)) + 0.0625d0
    else
        tmp = ((i * i) / beta) / beta
    end if
    code = tmp
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 2.9e+119) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = ((i * i) / beta) / beta;
	}
	return tmp;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	tmp = 0
	if beta <= 2.9e+119:
		tmp = (0.015625 / (i * i)) + 0.0625
	else:
		tmp = ((i * i) / beta) / beta
	return tmp
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 2.9e+119)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(Float64(Float64(i * i) / beta) / beta);
	end
	return tmp
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp_2 = code(alpha, beta, i)
	tmp = 0.0;
	if (beta <= 2.9e+119)
		tmp = (0.015625 / (i * i)) + 0.0625;
	else
		tmp = ((i * i) / beta) / beta;
	end
	tmp_2 = tmp;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 2.9e+119], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(N[(N[(i * i), $MachinePrecision] / beta), $MachinePrecision] / beta), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 2.9 \cdot 10^{+119}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;\frac{\frac{i \cdot i}{\beta}}{\beta}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 2.90000000000000007e119

    1. Initial program 21.7%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified17.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified78.2%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6478.3

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified78.3%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 2.90000000000000007e119 < beta

    1. Initial program 1.8%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in beta around inf

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{{\beta}^{2}} \]
      3. lower-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{{\beta}^{2}} \]
      4. unpow2N/A

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
      5. lower-*.f6431.3

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
    5. Simplified31.3%

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{\beta \cdot \beta} \]
      2. times-fracN/A

        \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha + i}{\beta}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(\alpha + i\right)}{\beta}} \]
      4. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(\alpha + i\right)}{\beta}} \]
      5. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{i}{\beta} \cdot \left(\alpha + i\right)}}{\beta} \]
      6. lower-/.f6466.4

        \[\leadsto \frac{\color{blue}{\frac{i}{\beta}} \cdot \left(\alpha + i\right)}{\beta} \]
      7. lift-+.f64N/A

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(\alpha + i\right)}}{\beta} \]
      8. +-commutativeN/A

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(i + \alpha\right)}}{\beta} \]
      9. lower-+.f6466.4

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(i + \alpha\right)}}{\beta} \]
    7. Applied egg-rr66.4%

      \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(i + \alpha\right)}{\beta}} \]
    8. Taylor expanded in i around inf

      \[\leadsto \frac{\color{blue}{\frac{{i}^{2}}{\beta}}}{\beta} \]
    9. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{{i}^{2}}{\beta}}}{\beta} \]
      2. unpow2N/A

        \[\leadsto \frac{\frac{\color{blue}{i \cdot i}}{\beta}}{\beta} \]
      3. lower-*.f6450.9

        \[\leadsto \frac{\frac{\color{blue}{i \cdot i}}{\beta}}{\beta} \]
    10. Simplified50.9%

      \[\leadsto \frac{\color{blue}{\frac{i \cdot i}{\beta}}}{\beta} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 5: 76.1% accurate, 3.4× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 7.2 \cdot 10^{+239}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha}{\beta}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 7.2e+239)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (* (/ i beta) (/ alpha beta))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 7.2e+239) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = (i / beta) * (alpha / beta);
	}
	return tmp;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: tmp
    if (beta <= 7.2d+239) then
        tmp = (0.015625d0 / (i * i)) + 0.0625d0
    else
        tmp = (i / beta) * (alpha / beta)
    end if
    code = tmp
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 7.2e+239) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = (i / beta) * (alpha / beta);
	}
	return tmp;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	tmp = 0
	if beta <= 7.2e+239:
		tmp = (0.015625 / (i * i)) + 0.0625
	else:
		tmp = (i / beta) * (alpha / beta)
	return tmp
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 7.2e+239)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(Float64(i / beta) * Float64(alpha / beta));
	end
	return tmp
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp_2 = code(alpha, beta, i)
	tmp = 0.0;
	if (beta <= 7.2e+239)
		tmp = (0.015625 / (i * i)) + 0.0625;
	else
		tmp = (i / beta) * (alpha / beta);
	end
	tmp_2 = tmp;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 7.2e+239], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(N[(i / beta), $MachinePrecision] * N[(alpha / beta), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 7.2 \cdot 10^{+239}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha}{\beta}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 7.2e239

    1. Initial program 18.5%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified14.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified66.4%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6471.0

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified71.0%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 7.2e239 < beta

    1. Initial program 0.0%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in beta around inf

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{{\beta}^{2}} \]
      3. lower-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{{\beta}^{2}} \]
      4. unpow2N/A

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
      5. lower-*.f6462.4

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
    5. Simplified62.4%

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
    6. Taylor expanded in i around 0

      \[\leadsto \color{blue}{\frac{\alpha \cdot i}{{\beta}^{2}}} \]
    7. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\alpha \cdot i}{{\beta}^{2}}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\alpha \cdot i}}{{\beta}^{2}} \]
      3. unpow2N/A

        \[\leadsto \frac{\alpha \cdot i}{\color{blue}{\beta \cdot \beta}} \]
      4. lower-*.f6463.1

        \[\leadsto \frac{\alpha \cdot i}{\color{blue}{\beta \cdot \beta}} \]
    8. Simplified63.1%

      \[\leadsto \color{blue}{\frac{\alpha \cdot i}{\beta \cdot \beta}} \]
    9. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\color{blue}{i \cdot \alpha}}{\beta \cdot \beta} \]
      2. times-fracN/A

        \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha}{\beta}} \]
      3. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{i}{\beta}} \cdot \frac{\alpha}{\beta} \]
      4. lower-*.f64N/A

        \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha}{\beta}} \]
      5. lower-/.f6463.9

        \[\leadsto \frac{i}{\beta} \cdot \color{blue}{\frac{\alpha}{\beta}} \]
    10. Applied egg-rr63.9%

      \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha}{\beta}} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 6: 75.0% accurate, 4.1× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 1.16 \cdot 10^{+241}:\\ \;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\ \mathbf{else}:\\ \;\;\;\;i \cdot \frac{i}{\beta \cdot \beta}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (if (<= beta 1.16e+241)
   (+ (/ 0.015625 (* i i)) 0.0625)
   (* i (/ i (* beta beta)))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 1.16e+241) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = i * (i / (beta * beta));
	}
	return tmp;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: tmp
    if (beta <= 1.16d+241) then
        tmp = (0.015625d0 / (i * i)) + 0.0625d0
    else
        tmp = i * (i / (beta * beta))
    end if
    code = tmp
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	double tmp;
	if (beta <= 1.16e+241) {
		tmp = (0.015625 / (i * i)) + 0.0625;
	} else {
		tmp = i * (i / (beta * beta));
	}
	return tmp;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	tmp = 0
	if beta <= 1.16e+241:
		tmp = (0.015625 / (i * i)) + 0.0625
	else:
		tmp = i * (i / (beta * beta))
	return tmp
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	tmp = 0.0
	if (beta <= 1.16e+241)
		tmp = Float64(Float64(0.015625 / Float64(i * i)) + 0.0625);
	else
		tmp = Float64(i * Float64(i / Float64(beta * beta)));
	end
	return tmp
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp_2 = code(alpha, beta, i)
	tmp = 0.0;
	if (beta <= 1.16e+241)
		tmp = (0.015625 / (i * i)) + 0.0625;
	else
		tmp = i * (i / (beta * beta));
	end
	tmp_2 = tmp;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := If[LessEqual[beta, 1.16e+241], N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision], N[(i * N[(i / N[(beta * beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
\mathbf{if}\;\beta \leq 1.16 \cdot 10^{+241}:\\
\;\;\;\;\frac{0.015625}{i \cdot i} + 0.0625\\

\mathbf{else}:\\
\;\;\;\;i \cdot \frac{i}{\beta \cdot \beta}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if beta < 1.15999999999999999e241

    1. Initial program 18.5%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in alpha around 0

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      4. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      5. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      6. lower-*.f64N/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      8. lower-+.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      9. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
      10. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      11. lower-*.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      12. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      13. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      16. *-commutativeN/A

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

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
      18. sub-negN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
      19. unpow2N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      20. metadata-evalN/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
      21. lower-fma.f64N/A

        \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
    5. Simplified14.9%

      \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
    6. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    7. Step-by-step derivation
      1. cancel-sign-sub-invN/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      3. lower-+.f64N/A

        \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      4. associate-*r/N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      7. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      8. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      9. unpow2N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      10. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      11. metadata-evalN/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
      12. lower-*.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
      13. lower-/.f64N/A

        \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    8. Simplified66.4%

      \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
    9. Taylor expanded in beta around 0

      \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
    10. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
      4. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
      5. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
      6. unpow2N/A

        \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
      7. lower-*.f6471.0

        \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
    11. Simplified71.0%

      \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]

    if 1.15999999999999999e241 < beta

    1. Initial program 0.0%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Taylor expanded in beta around inf

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{i \cdot \left(\alpha + i\right)}}{{\beta}^{2}} \]
      3. lower-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{{\beta}^{2}} \]
      4. unpow2N/A

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
      5. lower-*.f6462.4

        \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\color{blue}{\beta \cdot \beta}} \]
    5. Simplified62.4%

      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{i \cdot \color{blue}{\left(\alpha + i\right)}}{\beta \cdot \beta} \]
      2. times-fracN/A

        \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha + i}{\beta}} \]
      3. associate-*r/N/A

        \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(\alpha + i\right)}{\beta}} \]
      4. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(\alpha + i\right)}{\beta}} \]
      5. lower-*.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{i}{\beta} \cdot \left(\alpha + i\right)}}{\beta} \]
      6. lower-/.f6499.8

        \[\leadsto \frac{\color{blue}{\frac{i}{\beta}} \cdot \left(\alpha + i\right)}{\beta} \]
      7. lift-+.f64N/A

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(\alpha + i\right)}}{\beta} \]
      8. +-commutativeN/A

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(i + \alpha\right)}}{\beta} \]
      9. lower-+.f6499.8

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(i + \alpha\right)}}{\beta} \]
    7. Applied egg-rr99.8%

      \[\leadsto \color{blue}{\frac{\frac{i}{\beta} \cdot \left(i + \alpha\right)}{\beta}} \]
    8. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{i}{\beta}} \cdot \left(i + \alpha\right)}{\beta} \]
      2. lift-+.f64N/A

        \[\leadsto \frac{\frac{i}{\beta} \cdot \color{blue}{\left(i + \alpha\right)}}{\beta} \]
      3. associate-/l*N/A

        \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{i + \alpha}{\beta}} \]
      4. lift-+.f64N/A

        \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{i + \alpha}}{\beta} \]
      5. +-commutativeN/A

        \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{\alpha + i}}{\beta} \]
      6. lift-+.f64N/A

        \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{\alpha + i}}{\beta} \]
      7. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{i}{\beta}} \cdot \frac{\alpha + i}{\beta} \]
      8. clear-numN/A

        \[\leadsto \color{blue}{\frac{1}{\frac{\beta}{i}}} \cdot \frac{\alpha + i}{\beta} \]
      9. clear-numN/A

        \[\leadsto \frac{1}{\frac{\beta}{i}} \cdot \color{blue}{\frac{1}{\frac{\beta}{\alpha + i}}} \]
      10. frac-timesN/A

        \[\leadsto \color{blue}{\frac{1 \cdot 1}{\frac{\beta}{i} \cdot \frac{\beta}{\alpha + i}}} \]
      11. metadata-evalN/A

        \[\leadsto \frac{\color{blue}{1}}{\frac{\beta}{i} \cdot \frac{\beta}{\alpha + i}} \]
      12. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{1}{\frac{\beta}{i} \cdot \frac{\beta}{\alpha + i}}} \]
      13. lower-*.f64N/A

        \[\leadsto \frac{1}{\color{blue}{\frac{\beta}{i} \cdot \frac{\beta}{\alpha + i}}} \]
      14. lower-/.f64N/A

        \[\leadsto \frac{1}{\color{blue}{\frac{\beta}{i}} \cdot \frac{\beta}{\alpha + i}} \]
      15. lower-/.f6499.7

        \[\leadsto \frac{1}{\frac{\beta}{i} \cdot \color{blue}{\frac{\beta}{\alpha + i}}} \]
      16. lift-+.f64N/A

        \[\leadsto \frac{1}{\frac{\beta}{i} \cdot \frac{\beta}{\color{blue}{\alpha + i}}} \]
      17. +-commutativeN/A

        \[\leadsto \frac{1}{\frac{\beta}{i} \cdot \frac{\beta}{\color{blue}{i + \alpha}}} \]
      18. lift-+.f6499.7

        \[\leadsto \frac{1}{\frac{\beta}{i} \cdot \frac{\beta}{\color{blue}{i + \alpha}}} \]
    9. Applied egg-rr99.7%

      \[\leadsto \color{blue}{\frac{1}{\frac{\beta}{i} \cdot \frac{\beta}{i + \alpha}}} \]
    10. Taylor expanded in i around inf

      \[\leadsto \color{blue}{\frac{{i}^{2}}{{\beta}^{2}}} \]
    11. Step-by-step derivation
      1. unpow2N/A

        \[\leadsto \frac{\color{blue}{i \cdot i}}{{\beta}^{2}} \]
      2. associate-*r/N/A

        \[\leadsto \color{blue}{i \cdot \frac{i}{{\beta}^{2}}} \]
      3. lower-*.f64N/A

        \[\leadsto \color{blue}{i \cdot \frac{i}{{\beta}^{2}}} \]
      4. lower-/.f64N/A

        \[\leadsto i \cdot \color{blue}{\frac{i}{{\beta}^{2}}} \]
      5. unpow2N/A

        \[\leadsto i \cdot \frac{i}{\color{blue}{\beta \cdot \beta}} \]
      6. lower-*.f6463.4

        \[\leadsto i \cdot \frac{i}{\color{blue}{\beta \cdot \beta}} \]
    12. Simplified63.4%

      \[\leadsto \color{blue}{i \cdot \frac{i}{\beta \cdot \beta}} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 7: 71.5% accurate, 5.8× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \frac{0.015625}{i \cdot i} + 0.0625 \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i) :precision binary64 (+ (/ 0.015625 (* i i)) 0.0625))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	return (0.015625 / (i * i)) + 0.0625;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    code = (0.015625d0 / (i * i)) + 0.0625d0
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	return (0.015625 / (i * i)) + 0.0625;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	return (0.015625 / (i * i)) + 0.0625
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	return Float64(Float64(0.015625 / Float64(i * i)) + 0.0625)
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp = code(alpha, beta, i)
	tmp = (0.015625 / (i * i)) + 0.0625;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := N[(N[(0.015625 / N[(i * i), $MachinePrecision]), $MachinePrecision] + 0.0625), $MachinePrecision]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\frac{0.015625}{i \cdot i} + 0.0625
\end{array}
Derivation
  1. Initial program 17.2%

    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
  2. Add Preprocessing
  3. Taylor expanded in alpha around 0

    \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
  4. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    2. lower-*.f64N/A

      \[\leadsto \frac{\color{blue}{{i}^{2} \cdot {\left(\beta + i\right)}^{2}}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    3. unpow2N/A

      \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    4. lower-*.f64N/A

      \[\leadsto \frac{\color{blue}{\left(i \cdot i\right)} \cdot {\left(\beta + i\right)}^{2}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    5. unpow2N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \color{blue}{\left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    6. lower-*.f64N/A

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

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\color{blue}{\left(\beta + i\right)} \cdot \left(\beta + i\right)\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    8. lower-+.f64N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \color{blue}{\left(\beta + i\right)}\right)}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    9. lower-*.f64N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{{\left(\beta + 2 \cdot i\right)}^{2} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)}} \]
    10. unpow2N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    11. lower-*.f64N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\color{blue}{\left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)\right)} \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    12. +-commutativeN/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    13. *-commutativeN/A

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

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\color{blue}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(\beta + 2 \cdot i\right)\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    15. +-commutativeN/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\left(2 \cdot i + \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    16. *-commutativeN/A

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

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \color{blue}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \left({\left(\beta + 2 \cdot i\right)}^{2} - 1\right)} \]
    18. sub-negN/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\left({\left(\beta + 2 \cdot i\right)}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}} \]
    19. unpow2N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right)} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
    20. metadata-evalN/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \left(\left(\beta + 2 \cdot i\right) \cdot \left(\beta + 2 \cdot i\right) + \color{blue}{-1}\right)} \]
    21. lower-fma.f64N/A

      \[\leadsto \frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \color{blue}{\mathsf{fma}\left(\beta + 2 \cdot i, \beta + 2 \cdot i, -1\right)}} \]
  5. Simplified13.9%

    \[\leadsto \color{blue}{\frac{\left(i \cdot i\right) \cdot \left(\left(\beta + i\right) \cdot \left(\beta + i\right)\right)}{\left(\mathsf{fma}\left(i, 2, \beta\right) \cdot \mathsf{fma}\left(i, 2, \beta\right)\right) \cdot \mathsf{fma}\left(\mathsf{fma}\left(i, 2, \beta\right), \mathsf{fma}\left(i, 2, \beta\right), -1\right)}} \]
  6. Taylor expanded in i around inf

    \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) - \frac{1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
  7. Step-by-step derivation
    1. cancel-sign-sub-invN/A

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    2. lower-+.f64N/A

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    3. lower-+.f64N/A

      \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{{\beta}^{2}}{{i}^{2}}\right)} + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    4. associate-*r/N/A

      \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    5. lower-/.f64N/A

      \[\leadsto \left(\frac{1}{16} + \color{blue}{\frac{\frac{1}{16} \cdot {\beta}^{2}}{{i}^{2}}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    6. lower-*.f64N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\color{blue}{\frac{1}{16} \cdot {\beta}^{2}}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    7. unpow2N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    8. lower-*.f64N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \color{blue}{\left(\beta \cdot \beta\right)}}{{i}^{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    9. unpow2N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    10. lower-*.f64N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{\color{blue}{i \cdot i}}\right) + \left(\mathsf{neg}\left(\frac{1}{256}\right)\right) \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    11. metadata-evalN/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256}} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}} \]
    12. lower-*.f64N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \color{blue}{\frac{-1}{256} \cdot \frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
    13. lower-/.f64N/A

      \[\leadsto \left(\frac{1}{16} + \frac{\frac{1}{16} \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + \frac{-1}{256} \cdot \color{blue}{\frac{4 \cdot \left({\beta}^{2} - 1\right) + \left(4 \cdot {\beta}^{2} + 16 \cdot {\beta}^{2}\right)}{{i}^{2}}} \]
  8. Simplified61.7%

    \[\leadsto \color{blue}{\left(0.0625 + \frac{0.0625 \cdot \left(\beta \cdot \beta\right)}{i \cdot i}\right) + -0.00390625 \cdot \frac{\mathsf{fma}\left(4, \mathsf{fma}\left(\beta, \beta, -1\right), \left(\beta \cdot \beta\right) \cdot 20\right)}{i \cdot i}} \]
  9. Taylor expanded in beta around 0

    \[\leadsto \color{blue}{\frac{1}{16} + \frac{1}{64} \cdot \frac{1}{{i}^{2}}} \]
  10. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
    2. lower-+.f64N/A

      \[\leadsto \color{blue}{\frac{1}{64} \cdot \frac{1}{{i}^{2}} + \frac{1}{16}} \]
    3. associate-*r/N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{64} \cdot 1}{{i}^{2}}} + \frac{1}{16} \]
    4. metadata-evalN/A

      \[\leadsto \frac{\color{blue}{\frac{1}{64}}}{{i}^{2}} + \frac{1}{16} \]
    5. lower-/.f64N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{64}}{{i}^{2}}} + \frac{1}{16} \]
    6. unpow2N/A

      \[\leadsto \frac{\frac{1}{64}}{\color{blue}{i \cdot i}} + \frac{1}{16} \]
    7. lower-*.f6466.2

      \[\leadsto \frac{0.015625}{\color{blue}{i \cdot i}} + 0.0625 \]
  11. Simplified66.2%

    \[\leadsto \color{blue}{\frac{0.015625}{i \cdot i} + 0.0625} \]
  12. Add Preprocessing

Alternative 8: 71.3% accurate, 115.0× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ 0.0625 \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i) :precision binary64 0.0625)
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	return 0.0625;
}
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    code = 0.0625d0
end function
assert alpha < beta && beta < i;
public static double code(double alpha, double beta, double i) {
	return 0.0625;
}
[alpha, beta, i] = sort([alpha, beta, i])
def code(alpha, beta, i):
	return 0.0625
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	return 0.0625
end
alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
function tmp = code(alpha, beta, i)
	tmp = 0.0625;
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := 0.0625
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
0.0625
\end{array}
Derivation
  1. Initial program 17.2%

    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
  2. Add Preprocessing
  3. Taylor expanded in i around inf

    \[\leadsto \color{blue}{\frac{1}{16}} \]
  4. Step-by-step derivation
    1. Simplified65.9%

      \[\leadsto \color{blue}{0.0625} \]
    2. Add Preprocessing

    Reproduce

    ?
    herbie shell --seed 2024207 
    (FPCore (alpha beta i)
      :name "Octave 3.8, jcobi/4"
      :precision binary64
      :pre (and (and (> alpha -1.0) (> beta -1.0)) (> i 1.0))
      (/ (/ (* (* i (+ (+ alpha beta) i)) (+ (* beta alpha) (* i (+ (+ alpha beta) i)))) (* (+ (+ alpha beta) (* 2.0 i)) (+ (+ alpha beta) (* 2.0 i)))) (- (* (+ (+ alpha beta) (* 2.0 i)) (+ (+ alpha beta) (* 2.0 i))) 1.0)))