Kahan p13 Example 1

Percentage Accurate: 100.0% → 100.0%
Time: 12.2s
Alternatives: 12
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ t_2 := t\_1 \cdot t\_1\\ \frac{1 + t\_2}{2 + t\_2} \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))) (t_2 (* t_1 t_1)))
   (/ (+ 1.0 t_2) (+ 2.0 t_2))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double t_2 = t_1 * t_1;
	return (1.0 + t_2) / (2.0 + t_2);
}
real(8) function code(t)
    real(8), intent (in) :: t
    real(8) :: t_1
    real(8) :: t_2
    t_1 = (2.0d0 * t) / (1.0d0 + t)
    t_2 = t_1 * t_1
    code = (1.0d0 + t_2) / (2.0d0 + t_2)
end function
public static double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double t_2 = t_1 * t_1;
	return (1.0 + t_2) / (2.0 + t_2);
}
def code(t):
	t_1 = (2.0 * t) / (1.0 + t)
	t_2 = t_1 * t_1
	return (1.0 + t_2) / (2.0 + t_2)
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	t_2 = Float64(t_1 * t_1)
	return Float64(Float64(1.0 + t_2) / Float64(2.0 + t_2))
end
function tmp = code(t)
	t_1 = (2.0 * t) / (1.0 + t);
	t_2 = t_1 * t_1;
	tmp = (1.0 + t_2) / (2.0 + t_2);
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[(1.0 + t$95$2), $MachinePrecision] / N[(2.0 + t$95$2), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
t_2 := t\_1 \cdot t\_1\\
\frac{1 + t\_2}{2 + t\_2}
\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 12 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: 100.0% accurate, 1.0× speedup?

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

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
t_2 := t\_1 \cdot t\_1\\
\frac{1 + t\_2}{2 + t\_2}
\end{array}
\end{array}

Alternative 1: 100.0% accurate, 1.0× speedup?

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

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
t_2 := t\_1 \cdot t\_1\\
\frac{1 + t\_2}{2 + t\_2}
\end{array}
\end{array}
Derivation
  1. Initial program 100.0%

    \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
  2. Add Preprocessing
  3. Add Preprocessing

Alternative 2: 99.5% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \mathsf{fma}\left(t, -16, 12\right), -8\right), 4\right), 2\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (/
      (fma t (/ (* t 4.0) (fma t (+ 2.0 t) 1.0)) 1.0)
      (fma t (* t (fma t (fma t (fma t -16.0 12.0) -8.0) 4.0)) 2.0))
     (+
      (/ -0.2222222222222222 t)
      (-
       0.8333333333333334
       (/ (+ -0.037037037037037035 (/ -0.04938271604938271 t)) (* t t)))))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, ((t * 4.0) / fma(t, (2.0 + t), 1.0)), 1.0) / fma(t, (t * fma(t, fma(t, fma(t, -16.0, 12.0), -8.0), 4.0)), 2.0);
	} else {
		tmp = (-0.2222222222222222 / t) + (0.8333333333333334 - ((-0.037037037037037035 + (-0.04938271604938271 / t)) / (t * t)));
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = Float64(fma(t, Float64(Float64(t * 4.0) / fma(t, Float64(2.0 + t), 1.0)), 1.0) / fma(t, Float64(t * fma(t, fma(t, fma(t, -16.0, 12.0), -8.0), 4.0)), 2.0));
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + Float64(0.8333333333333334 - Float64(Float64(-0.037037037037037035 + Float64(-0.04938271604938271 / t)) / Float64(t * t))));
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(N[(t * N[(N[(t * 4.0), $MachinePrecision] / N[(t * N[(2.0 + t), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] / N[(t * N[(t * N[(t * N[(t * N[(t * -16.0 + 12.0), $MachinePrecision] + -8.0), $MachinePrecision] + 4.0), $MachinePrecision]), $MachinePrecision] + 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + N[(0.8333333333333334 - N[(N[(-0.037037037037037035 + N[(-0.04938271604938271 / t), $MachinePrecision]), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \mathsf{fma}\left(t, -16, 12\right), -8\right), 4\right), 2\right)}\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites100.0%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{\color{blue}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    6. Applied rewrites100.0%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)}} \]
    7. Taylor expanded in t around 0

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{1 + t \cdot \left(2 + t\right)}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
    8. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(2 + t\right) + 1}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      2. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(2 \cdot t + t \cdot t\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot t + \color{blue}{{t}^{2}}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      4. *-rgt-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \color{blue}{\left(t \cdot 1\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      5. *-inversesN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \color{blue}{\frac{t}{t}}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      6. *-rgt-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \frac{\color{blue}{t \cdot 1}}{t}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      7. associate-/l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \color{blue}{\left(t \cdot \frac{1}{t}\right)}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      8. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \color{blue}{\left(\left(t \cdot t\right) \cdot \frac{1}{t}\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      9. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(\color{blue}{{t}^{2}} \cdot \frac{1}{t}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      10. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left({t}^{2} \cdot \frac{1}{t}\right) \cdot 2} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      11. associate-*r*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{{t}^{2} \cdot \left(\frac{1}{t} \cdot 2\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      12. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left({t}^{2} \cdot \color{blue}{\left(2 \cdot \frac{1}{t}\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      13. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2}} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      14. *-lft-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2} + \color{blue}{1 \cdot {t}^{2}}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      15. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{{t}^{2} \cdot \left(2 \cdot \frac{1}{t} + 1\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      16. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{{t}^{2} \cdot \color{blue}{\left(1 + 2 \cdot \frac{1}{t}\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      17. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(t \cdot t\right)} \cdot \left(1 + 2 \cdot \frac{1}{t}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      18. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(t \cdot \left(1 + 2 \cdot \frac{1}{t}\right)\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      19. lower-fma.f64N/A

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

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\mathsf{fma}\left(t, 2 + t, 1\right)}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
    10. Taylor expanded in t around 0

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \color{blue}{t \cdot \left(4 + t \cdot \left(t \cdot \left(12 + -16 \cdot t\right) - 8\right)\right)}, 2\right)} \]
    11. Step-by-step derivation
      1. lower-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \color{blue}{t \cdot \left(4 + t \cdot \left(t \cdot \left(12 + -16 \cdot t\right) - 8\right)\right)}, 2\right)} \]
      2. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \color{blue}{\left(t \cdot \left(t \cdot \left(12 + -16 \cdot t\right) - 8\right) + 4\right)}, 2\right)} \]
      3. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \color{blue}{\mathsf{fma}\left(t, t \cdot \left(12 + -16 \cdot t\right) - 8, 4\right)}, 2\right)} \]
      4. sub-negN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \color{blue}{t \cdot \left(12 + -16 \cdot t\right) + \left(\mathsf{neg}\left(8\right)\right)}, 4\right), 2\right)} \]
      5. metadata-evalN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, t \cdot \left(12 + -16 \cdot t\right) + \color{blue}{-8}, 4\right), 2\right)} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \color{blue}{\mathsf{fma}\left(t, 12 + -16 \cdot t, -8\right)}, 4\right), 2\right)} \]
      7. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \color{blue}{-16 \cdot t + 12}, -8\right), 4\right), 2\right)} \]
      8. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \color{blue}{t \cdot -16} + 12, -8\right), 4\right), 2\right)} \]
      9. lower-fma.f6499.1

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \color{blue}{\mathsf{fma}\left(t, -16, 12\right)}, -8\right), 4\right), 2\right)} \]
    12. Applied rewrites99.1%

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \color{blue}{t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \mathsf{fma}\left(t, -16, 12\right), -8\right), 4\right)}, 2\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites54.2%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{\color{blue}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    6. Applied rewrites63.2%

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

      \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
    8. Step-by-step derivation
      1. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
      2. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
      3. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
    9. Applied rewrites99.1%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t}}{t}} \]
    10. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \color{blue}{\frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      2. lift-+.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\color{blue}{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      3. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      4. lift--.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      5. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} \]
      6. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} + \frac{5}{6}} \]
      7. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} + \frac{5}{6} \]
      8. lift--.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} + \frac{5}{6} \]
      9. div-subN/A

        \[\leadsto \color{blue}{\left(\frac{\frac{-2}{9}}{t} - \frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}\right)} + \frac{5}{6} \]
      10. associate-+l-N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      11. lower--.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      12. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t}} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right) \]
      13. lower--.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \color{blue}{\left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      14. lift-/.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} - \frac{5}{6}\right) \]
      15. associate-/l/N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t \cdot t}} - \frac{5}{6}\right) \]
      16. lift-*.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{\color{blue}{t \cdot t}} - \frac{5}{6}\right) \]
      17. lower-/.f6499.1

        \[\leadsto \frac{-0.2222222222222222}{t} - \left(\color{blue}{\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}} - 0.8333333333333334\right) \]
    11. Applied rewrites99.1%

      \[\leadsto \color{blue}{\frac{-0.2222222222222222}{t} - \left(\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t} - 0.8333333333333334\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.1%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, t \cdot \mathsf{fma}\left(t, \mathsf{fma}\left(t, \mathsf{fma}\left(t, -16, 12\right), -8\right), 4\right), 2\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 99.8% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}\\ \mathbf{if}\;\frac{2 \cdot t}{1 + t} \leq 1.95:\\ \;\;\;\;\frac{\mathsf{fma}\left(t, t\_1, 1\right)}{\mathsf{fma}\left(t, t\_1, 2\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* t 4.0) (fma t (+ 2.0 t) 1.0))))
   (if (<= (/ (* 2.0 t) (+ 1.0 t)) 1.95)
     (/ (fma t t_1 1.0) (fma t t_1 2.0))
     (+
      (/ -0.2222222222222222 t)
      (-
       0.8333333333333334
       (/ (+ -0.037037037037037035 (/ -0.04938271604938271 t)) (* t t)))))))
double code(double t) {
	double t_1 = (t * 4.0) / fma(t, (2.0 + t), 1.0);
	double tmp;
	if (((2.0 * t) / (1.0 + t)) <= 1.95) {
		tmp = fma(t, t_1, 1.0) / fma(t, t_1, 2.0);
	} else {
		tmp = (-0.2222222222222222 / t) + (0.8333333333333334 - ((-0.037037037037037035 + (-0.04938271604938271 / t)) / (t * t)));
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(t * 4.0) / fma(t, Float64(2.0 + t), 1.0))
	tmp = 0.0
	if (Float64(Float64(2.0 * t) / Float64(1.0 + t)) <= 1.95)
		tmp = Float64(fma(t, t_1, 1.0) / fma(t, t_1, 2.0));
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + Float64(0.8333333333333334 - Float64(Float64(-0.037037037037037035 + Float64(-0.04938271604938271 / t)) / Float64(t * t))));
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(t * 4.0), $MachinePrecision] / N[(t * N[(2.0 + t), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision], 1.95], N[(N[(t * t$95$1 + 1.0), $MachinePrecision] / N[(t * t$95$1 + 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + N[(0.8333333333333334 - N[(N[(-0.037037037037037035 + N[(-0.04938271604938271 / t), $MachinePrecision]), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}\\
\mathbf{if}\;\frac{2 \cdot t}{1 + t} \leq 1.95:\\
\;\;\;\;\frac{\mathsf{fma}\left(t, t\_1, 1\right)}{\mathsf{fma}\left(t, t\_1, 2\right)}\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) < 1.94999999999999996

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites100.0%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{\color{blue}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    6. Applied rewrites100.0%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)}} \]
    7. Taylor expanded in t around 0

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{1 + t \cdot \left(2 + t\right)}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
    8. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(2 + t\right) + 1}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      2. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(2 \cdot t + t \cdot t\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      3. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot t + \color{blue}{{t}^{2}}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      4. *-rgt-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \color{blue}{\left(t \cdot 1\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      5. *-inversesN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \color{blue}{\frac{t}{t}}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      6. *-rgt-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \frac{\color{blue}{t \cdot 1}}{t}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      7. associate-/l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(t \cdot \color{blue}{\left(t \cdot \frac{1}{t}\right)}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      8. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \color{blue}{\left(\left(t \cdot t\right) \cdot \frac{1}{t}\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      9. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(2 \cdot \left(\color{blue}{{t}^{2}} \cdot \frac{1}{t}\right) + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      10. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left({t}^{2} \cdot \frac{1}{t}\right) \cdot 2} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      11. associate-*r*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{{t}^{2} \cdot \left(\frac{1}{t} \cdot 2\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      12. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left({t}^{2} \cdot \color{blue}{\left(2 \cdot \frac{1}{t}\right)} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      13. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2}} + {t}^{2}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      14. *-lft-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2} + \color{blue}{1 \cdot {t}^{2}}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      15. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{{t}^{2} \cdot \left(2 \cdot \frac{1}{t} + 1\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      16. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{{t}^{2} \cdot \color{blue}{\left(1 + 2 \cdot \frac{1}{t}\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      17. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(t \cdot t\right)} \cdot \left(1 + 2 \cdot \frac{1}{t}\right) + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      18. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(t \cdot \left(1 + 2 \cdot \frac{1}{t}\right)\right)} + 1}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
      19. lower-fma.f64N/A

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

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\mathsf{fma}\left(t, 2 + t, 1\right)}}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(1 + t\right) \cdot \left(1 + t\right)}, 2\right)} \]
    10. Taylor expanded in t around 0

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{1 + t \cdot \left(2 + t\right)}}, 2\right)} \]
    11. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(2 + t\right) + 1}}, 2\right)} \]
      2. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(2 \cdot t + t \cdot t\right)} + 1}, 2\right)} \]
      3. metadata-evalN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left(2 \cdot 1\right)} \cdot t + t \cdot t\right) + 1}, 2\right)} \]
      4. lft-mult-inverseN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \color{blue}{\left(\frac{1}{t} \cdot t\right)}\right) \cdot t + t \cdot t\right) + 1}, 2\right)} \]
      5. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot t\right)} \cdot t + t \cdot t\right) + 1}, 2\right)} \]
      6. associate-*r*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\color{blue}{\left(2 \cdot \frac{1}{t}\right) \cdot \left(t \cdot t\right)} + t \cdot t\right) + 1}, 2\right)} \]
      7. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot \color{blue}{{t}^{2}} + t \cdot t\right) + 1}, 2\right)} \]
      8. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2} + \color{blue}{{t}^{2}}\right) + 1}, 2\right)} \]
      9. *-lft-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\left(\left(2 \cdot \frac{1}{t}\right) \cdot {t}^{2} + \color{blue}{1 \cdot {t}^{2}}\right) + 1}, 2\right)} \]
      10. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{{t}^{2} \cdot \left(2 \cdot \frac{1}{t} + 1\right)} + 1}, 2\right)} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{{t}^{2} \cdot \color{blue}{\left(1 + 2 \cdot \frac{1}{t}\right)} + 1}, 2\right)} \]
      12. unpow2N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\left(t \cdot t\right)} \cdot \left(1 + 2 \cdot \frac{1}{t}\right) + 1}, 2\right)} \]
      13. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{t \cdot \left(t \cdot \left(1 + 2 \cdot \frac{1}{t}\right)\right)} + 1}, 2\right)} \]
      14. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\mathsf{fma}\left(t, t \cdot \left(1 + 2 \cdot \frac{1}{t}\right), 1\right)}}, 2\right)} \]
      15. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, t \cdot \color{blue}{\left(2 \cdot \frac{1}{t} + 1\right)}, 1\right)}, 2\right)} \]
      16. distribute-rgt-inN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, \color{blue}{\left(2 \cdot \frac{1}{t}\right) \cdot t + 1 \cdot t}, 1\right)}, 2\right)} \]
      17. associate-*l*N/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, \color{blue}{2 \cdot \left(\frac{1}{t} \cdot t\right)} + 1 \cdot t, 1\right)}, 2\right)} \]
      18. lft-mult-inverseN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 \cdot \color{blue}{1} + 1 \cdot t, 1\right)}, 2\right)} \]
      19. metadata-evalN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, \color{blue}{2} + 1 \cdot t, 1\right)}, 2\right)} \]
      20. *-lft-identityN/A

        \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + \color{blue}{t}, 1\right)}, 2\right)} \]
      21. lower-+.f64100.0

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

      \[\leadsto \frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\color{blue}{\mathsf{fma}\left(t, 2 + t, 1\right)}}, 2\right)} \]

    if 1.94999999999999996 < (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites53.5%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{\color{blue}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    6. Applied rewrites62.6%

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

      \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
    8. Step-by-step derivation
      1. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
      2. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
      3. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
    9. Applied rewrites100.0%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t}}{t}} \]
    10. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \color{blue}{\frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      2. lift-+.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\color{blue}{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      3. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      4. lift--.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      5. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} \]
      6. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} + \frac{5}{6}} \]
      7. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} + \frac{5}{6} \]
      8. lift--.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} + \frac{5}{6} \]
      9. div-subN/A

        \[\leadsto \color{blue}{\left(\frac{\frac{-2}{9}}{t} - \frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}\right)} + \frac{5}{6} \]
      10. associate-+l-N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      11. lower--.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      12. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t}} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right) \]
      13. lower--.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \color{blue}{\left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      14. lift-/.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} - \frac{5}{6}\right) \]
      15. associate-/l/N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t \cdot t}} - \frac{5}{6}\right) \]
      16. lift-*.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{\color{blue}{t \cdot t}} - \frac{5}{6}\right) \]
      17. lower-/.f64100.0

        \[\leadsto \frac{-0.2222222222222222}{t} - \left(\color{blue}{\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}} - 0.8333333333333334\right) \]
    11. Applied rewrites100.0%

      \[\leadsto \color{blue}{\frac{-0.2222222222222222}{t} - \left(\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t} - 0.8333333333333334\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification100.0%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \leq 1.95:\\ \;\;\;\;\frac{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 1\right)}{\mathsf{fma}\left(t, \frac{t \cdot 4}{\mathsf{fma}\left(t, 2 + t, 1\right)}, 2\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 4: 99.4% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma t (fma (* t t) (+ t -2.0) t) 0.5)
     (+
      (/ -0.2222222222222222 t)
      (-
       0.8333333333333334
       (/ (+ -0.037037037037037035 (/ -0.04938271604938271 t)) (* t t)))))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, fma((t * t), (t + -2.0), t), 0.5);
	} else {
		tmp = (-0.2222222222222222 / t) + (0.8333333333333334 - ((-0.037037037037037035 + (-0.04938271604938271 / t)) / (t * t)));
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(t, fma(Float64(t * t), Float64(t + -2.0), t), 0.5);
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + Float64(0.8333333333333334 - Float64(Float64(-0.037037037037037035 + Float64(-0.04938271604938271 / t)) / Float64(t * t))));
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(t * N[(N[(t * t), $MachinePrecision] * N[(t + -2.0), $MachinePrecision] + t), $MachinePrecision] + 0.5), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + N[(0.8333333333333334 - N[(N[(-0.037037037037037035 + N[(-0.04938271604938271 / t), $MachinePrecision]), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

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

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

        \[\leadsto \color{blue}{\left(t \cdot t\right)} \cdot \left(1 + t \cdot \left(t - 2\right)\right) + \frac{1}{2} \]
      3. associate-*l*N/A

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

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

        \[\leadsto \mathsf{fma}\left(t, t \cdot \color{blue}{\left(t \cdot \left(t - 2\right) + 1\right)}, \frac{1}{2}\right) \]
      6. distribute-lft-inN/A

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{t \cdot \left(t \cdot \left(t - 2\right)\right) + t \cdot 1}, \frac{1}{2}\right) \]
      7. associate-*r*N/A

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

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{{t}^{2}} \cdot \left(t - 2\right) + t \cdot 1, \frac{1}{2}\right) \]
      9. *-rgt-identityN/A

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

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

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(\color{blue}{t \cdot t}, t - 2, t\right), \frac{1}{2}\right) \]
      13. sub-negN/A

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + \color{blue}{-2}, t\right), \frac{1}{2}\right) \]
      15. lower-+.f6499.1

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, \color{blue}{t + -2}, t\right), 0.5\right) \]
    5. Applied rewrites99.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites54.2%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{\color{blue}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    6. Applied rewrites63.2%

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

      \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
    8. Step-by-step derivation
      1. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + -1 \cdot \frac{\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}}{t}} \]
      2. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
      3. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{-1 \cdot \left(\frac{2}{9} + -1 \cdot \frac{\frac{1}{27} + \frac{4}{81} \cdot \frac{1}{t}}{t}\right)}{t}} \]
    9. Applied rewrites99.1%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t}}{t}} \]
    10. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \color{blue}{\frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      2. lift-+.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \frac{\color{blue}{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}}{t}}{t} \]
      3. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\frac{-2}{9} - \color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      4. lift--.f64N/A

        \[\leadsto \frac{5}{6} + \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} \]
      5. lift-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} \]
      6. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} + \frac{5}{6}} \]
      7. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}} + \frac{5}{6} \]
      8. lift--.f64N/A

        \[\leadsto \frac{\color{blue}{\frac{-2}{9} - \frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} + \frac{5}{6} \]
      9. div-subN/A

        \[\leadsto \color{blue}{\left(\frac{\frac{-2}{9}}{t} - \frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t}\right)} + \frac{5}{6} \]
      10. associate-+l-N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      11. lower--.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      12. lower-/.f64N/A

        \[\leadsto \color{blue}{\frac{\frac{-2}{9}}{t}} - \left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right) \]
      13. lower--.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \color{blue}{\left(\frac{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}{t} - \frac{5}{6}\right)} \]
      14. lift-/.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t}}}{t} - \frac{5}{6}\right) \]
      15. associate-/l/N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\color{blue}{\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{t \cdot t}} - \frac{5}{6}\right) \]
      16. lift-*.f64N/A

        \[\leadsto \frac{\frac{-2}{9}}{t} - \left(\frac{\frac{-1}{27} + \frac{\frac{-4}{81}}{t}}{\color{blue}{t \cdot t}} - \frac{5}{6}\right) \]
      17. lower-/.f6499.1

        \[\leadsto \frac{-0.2222222222222222}{t} - \left(\color{blue}{\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}} - 0.8333333333333334\right) \]
    11. Applied rewrites99.1%

      \[\leadsto \color{blue}{\frac{-0.2222222222222222}{t} - \left(\frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t} - 0.8333333333333334\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.1%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + \left(0.8333333333333334 - \frac{-0.037037037037037035 + \frac{-0.04938271604938271}{t}}{t \cdot t}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 5: 99.4% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;0.8333333333333334 + \frac{-0.2222222222222222 + \frac{0.037037037037037035 + \frac{0.04938271604938271}{t}}{t}}{t}\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma t (fma (* t t) (+ t -2.0) t) 0.5)
     (+
      0.8333333333333334
      (/
       (+
        -0.2222222222222222
        (/ (+ 0.037037037037037035 (/ 0.04938271604938271 t)) t))
       t)))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, fma((t * t), (t + -2.0), t), 0.5);
	} else {
		tmp = 0.8333333333333334 + ((-0.2222222222222222 + ((0.037037037037037035 + (0.04938271604938271 / t)) / t)) / t);
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(t, fma(Float64(t * t), Float64(t + -2.0), t), 0.5);
	else
		tmp = Float64(0.8333333333333334 + Float64(Float64(-0.2222222222222222 + Float64(Float64(0.037037037037037035 + Float64(0.04938271604938271 / t)) / t)) / t));
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(t * N[(N[(t * t), $MachinePrecision] * N[(t + -2.0), $MachinePrecision] + t), $MachinePrecision] + 0.5), $MachinePrecision], N[(0.8333333333333334 + N[(N[(-0.2222222222222222 + N[(N[(0.037037037037037035 + N[(0.04938271604938271 / t), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;0.8333333333333334 + \frac{-0.2222222222222222 + \frac{0.037037037037037035 + \frac{0.04938271604938271}{t}}{t}}{t}\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

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

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

        \[\leadsto \color{blue}{\left(t \cdot t\right)} \cdot \left(1 + t \cdot \left(t - 2\right)\right) + \frac{1}{2} \]
      3. associate-*l*N/A

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

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

        \[\leadsto \mathsf{fma}\left(t, t \cdot \color{blue}{\left(t \cdot \left(t - 2\right) + 1\right)}, \frac{1}{2}\right) \]
      6. distribute-lft-inN/A

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{t \cdot \left(t \cdot \left(t - 2\right)\right) + t \cdot 1}, \frac{1}{2}\right) \]
      7. associate-*r*N/A

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

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{{t}^{2}} \cdot \left(t - 2\right) + t \cdot 1, \frac{1}{2}\right) \]
      9. *-rgt-identityN/A

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

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

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(\color{blue}{t \cdot t}, t - 2, t\right), \frac{1}{2}\right) \]
      13. sub-negN/A

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + \color{blue}{-2}, t\right), \frac{1}{2}\right) \]
      15. lower-+.f6499.1

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, \color{blue}{t + -2}, t\right), 0.5\right) \]
    5. Applied rewrites99.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \color{blue}{\left(\frac{5}{6} + \left(\frac{\frac{1}{27}}{{t}^{2}} + \frac{4}{81} \cdot \frac{1}{{t}^{3}}\right)\right) - \frac{2}{9} \cdot \frac{1}{t}} \]
    4. Applied rewrites99.1%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{\frac{0.037037037037037035 + \frac{0.04938271604938271}{t}}{t} + -0.2222222222222222}{t}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.1%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;0.8333333333333334 + \frac{-0.2222222222222222 + \frac{0.037037037037037035 + \frac{0.04938271604938271}{t}}{t}}{t}\\ \end{array} \]
  5. Add Preprocessing

Alternative 6: 99.4% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;0.8333333333333334 - \frac{\mathsf{fma}\left(t, 0.2222222222222222, -0.037037037037037035\right)}{t \cdot t}\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma t (fma (* t t) (+ t -2.0) t) 0.5)
     (-
      0.8333333333333334
      (/ (fma t 0.2222222222222222 -0.037037037037037035) (* t t))))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, fma((t * t), (t + -2.0), t), 0.5);
	} else {
		tmp = 0.8333333333333334 - (fma(t, 0.2222222222222222, -0.037037037037037035) / (t * t));
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(t, fma(Float64(t * t), Float64(t + -2.0), t), 0.5);
	else
		tmp = Float64(0.8333333333333334 - Float64(fma(t, 0.2222222222222222, -0.037037037037037035) / Float64(t * t)));
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(t * N[(N[(t * t), $MachinePrecision] * N[(t + -2.0), $MachinePrecision] + t), $MachinePrecision] + 0.5), $MachinePrecision], N[(0.8333333333333334 - N[(N[(t * 0.2222222222222222 + -0.037037037037037035), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;0.8333333333333334 - \frac{\mathsf{fma}\left(t, 0.2222222222222222, -0.037037037037037035\right)}{t \cdot t}\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

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

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

        \[\leadsto \color{blue}{\left(t \cdot t\right)} \cdot \left(1 + t \cdot \left(t - 2\right)\right) + \frac{1}{2} \]
      3. associate-*l*N/A

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

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

        \[\leadsto \mathsf{fma}\left(t, t \cdot \color{blue}{\left(t \cdot \left(t - 2\right) + 1\right)}, \frac{1}{2}\right) \]
      6. distribute-lft-inN/A

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{t \cdot \left(t \cdot \left(t - 2\right)\right) + t \cdot 1}, \frac{1}{2}\right) \]
      7. associate-*r*N/A

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

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{{t}^{2}} \cdot \left(t - 2\right) + t \cdot 1, \frac{1}{2}\right) \]
      9. *-rgt-identityN/A

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

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

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(\color{blue}{t \cdot t}, t - 2, t\right), \frac{1}{2}\right) \]
      13. sub-negN/A

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + \color{blue}{-2}, t\right), \frac{1}{2}\right) \]
      15. lower-+.f6499.1

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, \color{blue}{t + -2}, t\right), 0.5\right) \]
    5. Applied rewrites99.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      3. frac-2negN/A

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

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{2 \cdot t}{\color{blue}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      5. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)} \cdot \frac{\color{blue}{2 \cdot t}}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      6. frac-2negN/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      7. lift-/.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      8. lift-/.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \color{blue}{\frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      9. lift-*.f64N/A

        \[\leadsto \frac{1 + \color{blue}{\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\color{blue}{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      11. lift-+.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{\color{blue}{1 + t}} \cdot \frac{2 \cdot t}{1 + t}} \]
      12. lift-*.f64N/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{\color{blue}{2 \cdot t}}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      13. frac-2negN/A

        \[\leadsto \frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \color{blue}{\frac{\mathsf{neg}\left(2 \cdot t\right)}{\mathsf{neg}\left(\left(1 + t\right)\right)}} \cdot \frac{2 \cdot t}{1 + t}} \]
    4. Applied rewrites54.2%

      \[\leadsto \color{blue}{\frac{1 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}{2 + \frac{t \cdot \left(t \cdot 4\right)}{\left(1 + t\right) \cdot \left(1 + t\right)}}} \]
    5. Taylor expanded in t around inf

      \[\leadsto \color{blue}{\left(\frac{5}{6} + \frac{\frac{1}{27}}{{t}^{2}}\right) - \frac{2}{9} \cdot \frac{1}{t}} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{\left(\frac{\frac{1}{27}}{{t}^{2}} + \frac{5}{6}\right)} - \frac{2}{9} \cdot \frac{1}{t} \]
      2. associate--l+N/A

        \[\leadsto \color{blue}{\frac{\frac{1}{27}}{{t}^{2}} + \left(\frac{5}{6} - \frac{2}{9} \cdot \frac{1}{t}\right)} \]
      3. +-commutativeN/A

        \[\leadsto \color{blue}{\left(\frac{5}{6} - \frac{2}{9} \cdot \frac{1}{t}\right) + \frac{\frac{1}{27}}{{t}^{2}}} \]
      4. associate--r-N/A

        \[\leadsto \color{blue}{\frac{5}{6} - \left(\frac{2}{9} \cdot \frac{1}{t} - \frac{\frac{1}{27}}{{t}^{2}}\right)} \]
      5. associate-*r/N/A

        \[\leadsto \frac{5}{6} - \left(\color{blue}{\frac{\frac{2}{9} \cdot 1}{t}} - \frac{\frac{1}{27}}{{t}^{2}}\right) \]
      6. metadata-evalN/A

        \[\leadsto \frac{5}{6} - \left(\frac{\color{blue}{\frac{2}{9}}}{t} - \frac{\frac{1}{27}}{{t}^{2}}\right) \]
      7. unpow2N/A

        \[\leadsto \frac{5}{6} - \left(\frac{\frac{2}{9}}{t} - \frac{\frac{1}{27}}{\color{blue}{t \cdot t}}\right) \]
      8. associate-/r*N/A

        \[\leadsto \frac{5}{6} - \left(\frac{\frac{2}{9}}{t} - \color{blue}{\frac{\frac{\frac{1}{27}}{t}}{t}}\right) \]
      9. metadata-evalN/A

        \[\leadsto \frac{5}{6} - \left(\frac{\frac{2}{9}}{t} - \frac{\frac{\color{blue}{\frac{1}{27} \cdot 1}}{t}}{t}\right) \]
      10. associate-*r/N/A

        \[\leadsto \frac{5}{6} - \left(\frac{\frac{2}{9}}{t} - \frac{\color{blue}{\frac{1}{27} \cdot \frac{1}{t}}}{t}\right) \]
      11. div-subN/A

        \[\leadsto \frac{5}{6} - \color{blue}{\frac{\frac{2}{9} - \frac{1}{27} \cdot \frac{1}{t}}{t}} \]
      12. lower--.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} - \frac{\frac{2}{9} - \frac{1}{27} \cdot \frac{1}{t}}{t}} \]
      13. metadata-evalN/A

        \[\leadsto \frac{5}{6} - \frac{\color{blue}{\frac{2}{9} \cdot 1} - \frac{1}{27} \cdot \frac{1}{t}}{t} \]
      14. *-inversesN/A

        \[\leadsto \frac{5}{6} - \frac{\frac{2}{9} \cdot \color{blue}{\frac{t}{t}} - \frac{1}{27} \cdot \frac{1}{t}}{t} \]
      15. associate-/l*N/A

        \[\leadsto \frac{5}{6} - \frac{\color{blue}{\frac{\frac{2}{9} \cdot t}{t}} - \frac{1}{27} \cdot \frac{1}{t}}{t} \]
      16. associate-*r/N/A

        \[\leadsto \frac{5}{6} - \frac{\frac{\frac{2}{9} \cdot t}{t} - \color{blue}{\frac{\frac{1}{27} \cdot 1}{t}}}{t} \]
      17. metadata-evalN/A

        \[\leadsto \frac{5}{6} - \frac{\frac{\frac{2}{9} \cdot t}{t} - \frac{\color{blue}{\frac{1}{27}}}{t}}{t} \]
      18. div-subN/A

        \[\leadsto \frac{5}{6} - \frac{\color{blue}{\frac{\frac{2}{9} \cdot t - \frac{1}{27}}{t}}}{t} \]
      19. associate-/r*N/A

        \[\leadsto \frac{5}{6} - \color{blue}{\frac{\frac{2}{9} \cdot t - \frac{1}{27}}{t \cdot t}} \]
      20. unpow2N/A

        \[\leadsto \frac{5}{6} - \frac{\frac{2}{9} \cdot t - \frac{1}{27}}{\color{blue}{{t}^{2}}} \]
    7. Applied rewrites98.9%

      \[\leadsto \color{blue}{0.8333333333333334 - \frac{\mathsf{fma}\left(t, 0.2222222222222222, -0.037037037037037035\right)}{t \cdot t}} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 7: 99.2% accurate, 1.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma t (fma (* t t) (+ t -2.0) t) 0.5)
     (+ (/ -0.2222222222222222 t) 0.8333333333333334))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, fma((t * t), (t + -2.0), t), 0.5);
	} else {
		tmp = (-0.2222222222222222 / t) + 0.8333333333333334;
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(t, fma(Float64(t * t), Float64(t + -2.0), t), 0.5);
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + 0.8333333333333334);
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(t * N[(N[(t * t), $MachinePrecision] * N[(t + -2.0), $MachinePrecision] + t), $MachinePrecision] + 0.5), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + 0.8333333333333334), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

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

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

        \[\leadsto \color{blue}{\left(t \cdot t\right)} \cdot \left(1 + t \cdot \left(t - 2\right)\right) + \frac{1}{2} \]
      3. associate-*l*N/A

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

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

        \[\leadsto \mathsf{fma}\left(t, t \cdot \color{blue}{\left(t \cdot \left(t - 2\right) + 1\right)}, \frac{1}{2}\right) \]
      6. distribute-lft-inN/A

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{t \cdot \left(t \cdot \left(t - 2\right)\right) + t \cdot 1}, \frac{1}{2}\right) \]
      7. associate-*r*N/A

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

        \[\leadsto \mathsf{fma}\left(t, \color{blue}{{t}^{2}} \cdot \left(t - 2\right) + t \cdot 1, \frac{1}{2}\right) \]
      9. *-rgt-identityN/A

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

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

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(\color{blue}{t \cdot t}, t - 2, t\right), \frac{1}{2}\right) \]
      13. sub-negN/A

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

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + \color{blue}{-2}, t\right), \frac{1}{2}\right) \]
      15. lower-+.f6499.1

        \[\leadsto \mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, \color{blue}{t + -2}, t\right), 0.5\right) \]
    5. Applied rewrites99.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \color{blue}{\frac{5}{6} - \frac{2}{9} \cdot \frac{1}{t}} \]
    4. Step-by-step derivation
      1. sub-negN/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      3. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{2}{9} \cdot 1}{t}}\right)\right) \]
      4. metadata-evalN/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\frac{\color{blue}{\frac{2}{9}}}{t}\right)\right) \]
      5. distribute-neg-fracN/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      6. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      7. metadata-eval98.4

        \[\leadsto 0.8333333333333334 + \frac{\color{blue}{-0.2222222222222222}}{t} \]
    5. Applied rewrites98.4%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222}{t}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification98.7%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, \mathsf{fma}\left(t \cdot t, t + -2, t\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \]
  5. Add Preprocessing

Alternative 8: 99.2% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t \cdot t, \mathsf{fma}\left(t, -2, 1\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma (* t t) (fma t -2.0 1.0) 0.5)
     (+ (/ -0.2222222222222222 t) 0.8333333333333334))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma((t * t), fma(t, -2.0, 1.0), 0.5);
	} else {
		tmp = (-0.2222222222222222 / t) + 0.8333333333333334;
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(Float64(t * t), fma(t, -2.0, 1.0), 0.5);
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + 0.8333333333333334);
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(N[(t * t), $MachinePrecision] * N[(t * -2.0 + 1.0), $MachinePrecision] + 0.5), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + 0.8333333333333334), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t \cdot t, \mathsf{fma}\left(t, -2, 1\right), 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

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

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

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

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

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

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

        \[\leadsto \mathsf{fma}\left(t \cdot t, \color{blue}{t \cdot -2} + 1, \frac{1}{2}\right) \]
      7. lower-fma.f6498.8

        \[\leadsto \mathsf{fma}\left(t \cdot t, \color{blue}{\mathsf{fma}\left(t, -2, 1\right)}, 0.5\right) \]
    5. Applied rewrites98.8%

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

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \color{blue}{\frac{5}{6} - \frac{2}{9} \cdot \frac{1}{t}} \]
    4. Step-by-step derivation
      1. sub-negN/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      3. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{2}{9} \cdot 1}{t}}\right)\right) \]
      4. metadata-evalN/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\frac{\color{blue}{\frac{2}{9}}}{t}\right)\right) \]
      5. distribute-neg-fracN/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      6. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      7. metadata-eval98.4

        \[\leadsto 0.8333333333333334 + \frac{\color{blue}{-0.2222222222222222}}{t} \]
    5. Applied rewrites98.4%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222}{t}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification98.6%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t \cdot t, \mathsf{fma}\left(t, -2, 1\right), 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \]
  5. Add Preprocessing

Alternative 9: 99.1% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, t, 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 0.5)
     (fma t t 0.5)
     (+ (/ -0.2222222222222222 t) 0.8333333333333334))))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 0.5) {
		tmp = fma(t, t, 0.5);
	} else {
		tmp = (-0.2222222222222222 / t) + 0.8333333333333334;
	}
	return tmp;
}
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 0.5)
		tmp = fma(t, t, 0.5);
	else
		tmp = Float64(Float64(-0.2222222222222222 / t) + 0.8333333333333334);
	end
	return tmp
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 0.5], N[(t * t + 0.5), $MachinePrecision], N[(N[(-0.2222222222222222 / t), $MachinePrecision] + 0.8333333333333334), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 0.5:\\
\;\;\;\;\mathsf{fma}\left(t, t, 0.5\right)\\

\mathbf{else}:\\
\;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\


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

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

      \[\leadsto \color{blue}{\frac{1}{2} + {t}^{2}} \]
    4. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{{t}^{2} + \frac{1}{2}} \]
      2. unpow2N/A

        \[\leadsto \color{blue}{t \cdot t} + \frac{1}{2} \]
      3. lower-fma.f6498.2

        \[\leadsto \color{blue}{\mathsf{fma}\left(t, t, 0.5\right)} \]
    5. Applied rewrites98.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, t, 0.5\right)} \]

    if 0.5 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around inf

      \[\leadsto \color{blue}{\frac{5}{6} - \frac{2}{9} \cdot \frac{1}{t}} \]
    4. Step-by-step derivation
      1. sub-negN/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      2. lower-+.f64N/A

        \[\leadsto \color{blue}{\frac{5}{6} + \left(\mathsf{neg}\left(\frac{2}{9} \cdot \frac{1}{t}\right)\right)} \]
      3. associate-*r/N/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{2}{9} \cdot 1}{t}}\right)\right) \]
      4. metadata-evalN/A

        \[\leadsto \frac{5}{6} + \left(\mathsf{neg}\left(\frac{\color{blue}{\frac{2}{9}}}{t}\right)\right) \]
      5. distribute-neg-fracN/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      6. lower-/.f64N/A

        \[\leadsto \frac{5}{6} + \color{blue}{\frac{\mathsf{neg}\left(\frac{2}{9}\right)}{t}} \]
      7. metadata-eval98.4

        \[\leadsto 0.8333333333333334 + \frac{\color{blue}{-0.2222222222222222}}{t} \]
    5. Applied rewrites98.4%

      \[\leadsto \color{blue}{0.8333333333333334 + \frac{-0.2222222222222222}{t}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification98.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t} \leq 0.5:\\ \;\;\;\;\mathsf{fma}\left(t, t, 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{-0.2222222222222222}{t} + 0.8333333333333334\\ \end{array} \]
  5. Add Preprocessing

Alternative 10: 98.4% accurate, 2.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{2 \cdot t}{1 + t}\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 1:\\ \;\;\;\;0.5\\ \mathbf{else}:\\ \;\;\;\;0.8333333333333334\\ \end{array} \end{array} \]
(FPCore (t)
 :precision binary64
 (let* ((t_1 (/ (* 2.0 t) (+ 1.0 t))))
   (if (<= (* t_1 t_1) 1.0) 0.5 0.8333333333333334)))
double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 1.0) {
		tmp = 0.5;
	} else {
		tmp = 0.8333333333333334;
	}
	return tmp;
}
real(8) function code(t)
    real(8), intent (in) :: t
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (2.0d0 * t) / (1.0d0 + t)
    if ((t_1 * t_1) <= 1.0d0) then
        tmp = 0.5d0
    else
        tmp = 0.8333333333333334d0
    end if
    code = tmp
end function
public static double code(double t) {
	double t_1 = (2.0 * t) / (1.0 + t);
	double tmp;
	if ((t_1 * t_1) <= 1.0) {
		tmp = 0.5;
	} else {
		tmp = 0.8333333333333334;
	}
	return tmp;
}
def code(t):
	t_1 = (2.0 * t) / (1.0 + t)
	tmp = 0
	if (t_1 * t_1) <= 1.0:
		tmp = 0.5
	else:
		tmp = 0.8333333333333334
	return tmp
function code(t)
	t_1 = Float64(Float64(2.0 * t) / Float64(1.0 + t))
	tmp = 0.0
	if (Float64(t_1 * t_1) <= 1.0)
		tmp = 0.5;
	else
		tmp = 0.8333333333333334;
	end
	return tmp
end
function tmp_2 = code(t)
	t_1 = (2.0 * t) / (1.0 + t);
	tmp = 0.0;
	if ((t_1 * t_1) <= 1.0)
		tmp = 0.5;
	else
		tmp = 0.8333333333333334;
	end
	tmp_2 = tmp;
end
code[t_] := Block[{t$95$1 = N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 * t$95$1), $MachinePrecision], 1.0], 0.5, 0.8333333333333334]]
\begin{array}{l}

\\
\begin{array}{l}
t_1 := \frac{2 \cdot t}{1 + t}\\
\mathbf{if}\;t\_1 \cdot t\_1 \leq 1:\\
\;\;\;\;0.5\\

\mathbf{else}:\\
\;\;\;\;0.8333333333333334\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t))) < 1

    1. Initial program 100.0%

      \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
    2. Add Preprocessing
    3. Taylor expanded in t around 0

      \[\leadsto \color{blue}{\frac{1}{2}} \]
    4. Step-by-step derivation
      1. Applied rewrites97.4%

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

      if 1 < (*.f64 (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)))

      1. Initial program 100.0%

        \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
      2. Add Preprocessing
      3. Taylor expanded in t around inf

        \[\leadsto \color{blue}{\frac{5}{6}} \]
      4. Step-by-step derivation
        1. Applied rewrites97.2%

          \[\leadsto \color{blue}{0.8333333333333334} \]
      5. Recombined 2 regimes into one program.
      6. Add Preprocessing

      Alternative 11: 98.6% accurate, 3.2× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\frac{2 \cdot t}{1 + t} \leq 1:\\ \;\;\;\;\mathsf{fma}\left(t, t, 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;0.8333333333333334\\ \end{array} \end{array} \]
      (FPCore (t)
       :precision binary64
       (if (<= (/ (* 2.0 t) (+ 1.0 t)) 1.0) (fma t t 0.5) 0.8333333333333334))
      double code(double t) {
      	double tmp;
      	if (((2.0 * t) / (1.0 + t)) <= 1.0) {
      		tmp = fma(t, t, 0.5);
      	} else {
      		tmp = 0.8333333333333334;
      	}
      	return tmp;
      }
      
      function code(t)
      	tmp = 0.0
      	if (Float64(Float64(2.0 * t) / Float64(1.0 + t)) <= 1.0)
      		tmp = fma(t, t, 0.5);
      	else
      		tmp = 0.8333333333333334;
      	end
      	return tmp
      end
      
      code[t_] := If[LessEqual[N[(N[(2.0 * t), $MachinePrecision] / N[(1.0 + t), $MachinePrecision]), $MachinePrecision], 1.0], N[(t * t + 0.5), $MachinePrecision], 0.8333333333333334]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;\frac{2 \cdot t}{1 + t} \leq 1:\\
      \;\;\;\;\mathsf{fma}\left(t, t, 0.5\right)\\
      
      \mathbf{else}:\\
      \;\;\;\;0.8333333333333334\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t)) < 1

        1. Initial program 100.0%

          \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
        2. Add Preprocessing
        3. Taylor expanded in t around 0

          \[\leadsto \color{blue}{\frac{1}{2} + {t}^{2}} \]
        4. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \color{blue}{{t}^{2} + \frac{1}{2}} \]
          2. unpow2N/A

            \[\leadsto \color{blue}{t \cdot t} + \frac{1}{2} \]
          3. lower-fma.f6497.6

            \[\leadsto \color{blue}{\mathsf{fma}\left(t, t, 0.5\right)} \]
        5. Applied rewrites97.6%

          \[\leadsto \color{blue}{\mathsf{fma}\left(t, t, 0.5\right)} \]

        if 1 < (/.f64 (*.f64 #s(literal 2 binary64) t) (+.f64 #s(literal 1 binary64) t))

        1. Initial program 100.0%

          \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
        2. Add Preprocessing
        3. Taylor expanded in t around inf

          \[\leadsto \color{blue}{\frac{5}{6}} \]
        4. Step-by-step derivation
          1. Applied rewrites97.8%

            \[\leadsto \color{blue}{0.8333333333333334} \]
        5. Recombined 2 regimes into one program.
        6. Add Preprocessing

        Alternative 12: 58.8% accurate, 104.0× speedup?

        \[\begin{array}{l} \\ 0.5 \end{array} \]
        (FPCore (t) :precision binary64 0.5)
        double code(double t) {
        	return 0.5;
        }
        
        real(8) function code(t)
            real(8), intent (in) :: t
            code = 0.5d0
        end function
        
        public static double code(double t) {
        	return 0.5;
        }
        
        def code(t):
        	return 0.5
        
        function code(t)
        	return 0.5
        end
        
        function tmp = code(t)
        	tmp = 0.5;
        end
        
        code[t_] := 0.5
        
        \begin{array}{l}
        
        \\
        0.5
        \end{array}
        
        Derivation
        1. Initial program 100.0%

          \[\frac{1 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}}{2 + \frac{2 \cdot t}{1 + t} \cdot \frac{2 \cdot t}{1 + t}} \]
        2. Add Preprocessing
        3. Taylor expanded in t around 0

          \[\leadsto \color{blue}{\frac{1}{2}} \]
        4. Step-by-step derivation
          1. Applied rewrites57.6%

            \[\leadsto \color{blue}{0.5} \]
          2. Add Preprocessing

          Reproduce

          ?
          herbie shell --seed 2024214 
          (FPCore (t)
            :name "Kahan p13 Example 1"
            :precision binary64
            (/ (+ 1.0 (* (/ (* 2.0 t) (+ 1.0 t)) (/ (* 2.0 t) (+ 1.0 t)))) (+ 2.0 (* (/ (* 2.0 t) (+ 1.0 t)) (/ (* 2.0 t) (+ 1.0 t))))))