Maksimov and Kolovsky, Equation (4)

Percentage Accurate: 86.6% → 100.0%
Time: 11.1s
Alternatives: 18
Speedup: 1.5×

Specification

?
\[\begin{array}{l} \\ \left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))
double code(double J, double l, double K, double U) {
	return ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
}
real(8) function code(j, l, k, u)
    real(8), intent (in) :: j
    real(8), intent (in) :: l
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    code = ((j * (exp(l) - exp(-l))) * cos((k / 2.0d0))) + u
end function
public static double code(double J, double l, double K, double U) {
	return ((J * (Math.exp(l) - Math.exp(-l))) * Math.cos((K / 2.0))) + U;
}
def code(J, l, K, U):
	return ((J * (math.exp(l) - math.exp(-l))) * math.cos((K / 2.0))) + U
function code(J, l, K, U)
	return Float64(Float64(Float64(J * Float64(exp(l) - exp(Float64(-l)))) * cos(Float64(K / 2.0))) + U)
end
function tmp = code(J, l, K, U)
	tmp = ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
end
code[J_, l_, K_, U_] := N[(N[(N[(J * N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]
\begin{array}{l}

\\
\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U
\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 18 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: 86.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))
double code(double J, double l, double K, double U) {
	return ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
}
real(8) function code(j, l, k, u)
    real(8), intent (in) :: j
    real(8), intent (in) :: l
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    code = ((j * (exp(l) - exp(-l))) * cos((k / 2.0d0))) + u
end function
public static double code(double J, double l, double K, double U) {
	return ((J * (Math.exp(l) - Math.exp(-l))) * Math.cos((K / 2.0))) + U;
}
def code(J, l, K, U):
	return ((J * (math.exp(l) - math.exp(-l))) * math.cos((K / 2.0))) + U
function code(J, l, K, U)
	return Float64(Float64(Float64(J * Float64(exp(l) - exp(Float64(-l)))) * cos(Float64(K / 2.0))) + U)
end
function tmp = code(J, l, K, U)
	tmp = ((J * (exp(l) - exp(-l))) * cos((K / 2.0))) + U;
end
code[J_, l_, K_, U_] := N[(N[(N[(J * N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + U), $MachinePrecision]
\begin{array}{l}

\\
\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U
\end{array}

Alternative 1: 100.0% accurate, 1.5× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\left(2 \cdot \sinh \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right) \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (fma (* (* 2.0 (sinh l)) (cos (* -0.5 K))) J U))
double code(double J, double l, double K, double U) {
	return fma(((2.0 * sinh(l)) * cos((-0.5 * K))), J, U);
}
function code(J, l, K, U)
	return fma(Float64(Float64(2.0 * sinh(l)) * cos(Float64(-0.5 * K))), J, U)
end
code[J_, l_, K_, U_] := N[(N[(N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision] * N[Cos[N[(-0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]
\begin{array}{l}

\\
\mathsf{fma}\left(\left(2 \cdot \sinh \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right)
\end{array}
Derivation
  1. Initial program 84.2%

    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-+.f64N/A

      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
    2. lift-*.f64N/A

      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
    3. lift-*.f64N/A

      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
    4. associate-*l*N/A

      \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
    5. *-commutativeN/A

      \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
    6. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
  4. Applied rewrites100.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
  5. Final simplification100.0%

    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \sinh \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right) \]
  6. Add Preprocessing

Alternative 2: 61.0% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := e^{\ell} - e^{-\ell}\\ t_1 := \mathsf{fma}\left(J \cdot \ell, \mathsf{fma}\left(K \cdot K, -0.25, 2\right), U\right)\\ \mathbf{if}\;t\_0 \leq -5 \cdot 10^{-5}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t\_0 \leq 10^{-6}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]
(FPCore (J l K U)
 :precision binary64
 (let* ((t_0 (- (exp l) (exp (- l))))
        (t_1 (fma (* J l) (fma (* K K) -0.25 2.0) U)))
   (if (<= t_0 -5e-5) t_1 (if (<= t_0 1e-6) (fma (* J l) 2.0 U) t_1))))
double code(double J, double l, double K, double U) {
	double t_0 = exp(l) - exp(-l);
	double t_1 = fma((J * l), fma((K * K), -0.25, 2.0), U);
	double tmp;
	if (t_0 <= -5e-5) {
		tmp = t_1;
	} else if (t_0 <= 1e-6) {
		tmp = fma((J * l), 2.0, U);
	} else {
		tmp = t_1;
	}
	return tmp;
}
function code(J, l, K, U)
	t_0 = Float64(exp(l) - exp(Float64(-l)))
	t_1 = fma(Float64(J * l), fma(Float64(K * K), -0.25, 2.0), U)
	tmp = 0.0
	if (t_0 <= -5e-5)
		tmp = t_1;
	elseif (t_0 <= 1e-6)
		tmp = fma(Float64(J * l), 2.0, U);
	else
		tmp = t_1;
	end
	return tmp
end
code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[Exp[l], $MachinePrecision] - N[Exp[(-l)], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(J * l), $MachinePrecision] * N[(N[(K * K), $MachinePrecision] * -0.25 + 2.0), $MachinePrecision] + U), $MachinePrecision]}, If[LessEqual[t$95$0, -5e-5], t$95$1, If[LessEqual[t$95$0, 1e-6], N[(N[(J * l), $MachinePrecision] * 2.0 + U), $MachinePrecision], t$95$1]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := e^{\ell} - e^{-\ell}\\
t_1 := \mathsf{fma}\left(J \cdot \ell, \mathsf{fma}\left(K \cdot K, -0.25, 2\right), U\right)\\
\mathbf{if}\;t\_0 \leq -5 \cdot 10^{-5}:\\
\;\;\;\;t\_1\\

\mathbf{elif}\;t\_0 \leq 10^{-6}:\\
\;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\

\mathbf{else}:\\
\;\;\;\;t\_1\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (-.f64 (exp.f64 l) (exp.f64 (neg.f64 l))) < -5.00000000000000024e-5 or 9.99999999999999955e-7 < (-.f64 (exp.f64 l) (exp.f64 (neg.f64 l)))

    1. Initial program 99.8%

      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
    2. Add Preprocessing
    3. Taylor expanded in l around 0

      \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
    4. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
      2. associate-*r*N/A

        \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
      3. associate-*r*N/A

        \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
      4. associate-*r*N/A

        \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      5. *-commutativeN/A

        \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
      6. lower-fma.f64N/A

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

        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
      8. *-commutativeN/A

        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
      9. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
      10. lower-*.f64N/A

        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
      11. lower-cos.f64N/A

        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
      12. *-commutativeN/A

        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
      13. lower-*.f6424.9

        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
    5. Applied rewrites24.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
    6. Taylor expanded in K around 0

      \[\leadsto U + \color{blue}{\left(\frac{-1}{4} \cdot \left(J \cdot \left({K}^{2} \cdot \ell\right)\right) + 2 \cdot \left(J \cdot \ell\right)\right)} \]
    7. Step-by-step derivation
      1. Applied rewrites32.0%

        \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{\mathsf{fma}\left(K \cdot K, -0.25, 2\right)}, U\right) \]

      if -5.00000000000000024e-5 < (-.f64 (exp.f64 l) (exp.f64 (neg.f64 l))) < 9.99999999999999955e-7

      1. Initial program 70.2%

        \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
      2. Add Preprocessing
      3. Taylor expanded in l around 0

        \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
        2. associate-*r*N/A

          \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
        3. associate-*r*N/A

          \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
        4. associate-*r*N/A

          \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        5. *-commutativeN/A

          \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
        6. lower-fma.f64N/A

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

          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
        8. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
        9. lower-*.f64N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
        10. lower-*.f64N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
        11. lower-cos.f64N/A

          \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
        12. *-commutativeN/A

          \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
        13. lower-*.f6499.9

          \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
      5. Applied rewrites99.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
      6. Taylor expanded in K around 0

        \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
      7. Step-by-step derivation
        1. Applied rewrites89.1%

          \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
      8. Recombined 2 regimes into one program.
      9. Final simplification62.1%

        \[\leadsto \begin{array}{l} \mathbf{if}\;e^{\ell} - e^{-\ell} \leq -5 \cdot 10^{-5}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, \mathsf{fma}\left(K \cdot K, -0.25, 2\right), U\right)\\ \mathbf{elif}\;e^{\ell} - e^{-\ell} \leq 10^{-6}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, \mathsf{fma}\left(K \cdot K, -0.25, 2\right), U\right)\\ \end{array} \]
      10. Add Preprocessing

      Alternative 3: 96.7% accurate, 1.2× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ \mathbf{if}\;t\_0 \leq 0.72:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot t\_0 + U\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
      (FPCore (J l K U)
       :precision binary64
       (let* ((t_0 (cos (/ K 2.0))))
         (if (<= t_0 0.72)
           (+
            (*
             (*
              (*
               (fma
                (fma
                 (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
                 (* l l)
                 0.3333333333333333)
                (* l l)
                2.0)
               l)
              J)
             t_0)
            U)
           (fma (* 1.0 (* 2.0 (sinh l))) J U))))
      double code(double J, double l, double K, double U) {
      	double t_0 = cos((K / 2.0));
      	double tmp;
      	if (t_0 <= 0.72) {
      		tmp = (((fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l) * J) * t_0) + U;
      	} else {
      		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
      	}
      	return tmp;
      }
      
      function code(J, l, K, U)
      	t_0 = cos(Float64(K / 2.0))
      	tmp = 0.0
      	if (t_0 <= 0.72)
      		tmp = Float64(Float64(Float64(Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l) * J) * t_0) + U);
      	else
      		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
      	end
      	return tmp
      end
      
      code[J_, l_, K_, U_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, 0.72], N[(N[(N[(N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] * J), $MachinePrecision] * t$95$0), $MachinePrecision] + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \cos \left(\frac{K}{2}\right)\\
      \mathbf{if}\;t\_0 \leq 0.72:\\
      \;\;\;\;\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot t\_0 + U\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

        1. Initial program 85.4%

          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. Add Preprocessing
        3. Taylor expanded in l around 0

          \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. lower-*.f64N/A

            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          3. +-commutativeN/A

            \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. *-commutativeN/A

            \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          5. lower-fma.f64N/A

            \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          6. +-commutativeN/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          7. *-commutativeN/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          8. lower-fma.f64N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          9. +-commutativeN/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          10. lower-fma.f64N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          11. unpow2N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          12. lower-*.f64N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          13. unpow2N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          14. lower-*.f64N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          15. unpow2N/A

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          16. lower-*.f6495.7

            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        5. Applied rewrites95.7%

          \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]

        if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

        1. Initial program 83.5%

          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-+.f64N/A

            \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
          2. lift-*.f64N/A

            \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
          3. lift-*.f64N/A

            \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. associate-*l*N/A

            \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
          5. *-commutativeN/A

            \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
          6. lower-fma.f64N/A

            \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
        4. Applied rewrites100.0%

          \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
        5. Taylor expanded in K around 0

          \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
        6. Step-by-step derivation
          1. Applied rewrites99.2%

            \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
        7. Recombined 2 regimes into one program.
        8. Final simplification97.8%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot J\right) \cdot \cos \left(\frac{K}{2}\right) + U\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
        9. Add Preprocessing

        Alternative 4: 96.7% accurate, 1.2× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
        (FPCore (J l K U)
         :precision binary64
         (if (<= (cos (/ K 2.0)) 0.72)
           (fma
            (* (cos (* 0.5 K)) J)
            (*
             (fma
              (fma
               (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
               (* l l)
               0.3333333333333333)
              (* l l)
              2.0)
             l)
            U)
           (fma (* 1.0 (* 2.0 (sinh l))) J U)))
        double code(double J, double l, double K, double U) {
        	double tmp;
        	if (cos((K / 2.0)) <= 0.72) {
        		tmp = fma((cos((0.5 * K)) * J), (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l), U);
        	} else {
        		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
        	}
        	return tmp;
        }
        
        function code(J, l, K, U)
        	tmp = 0.0
        	if (cos(Float64(K / 2.0)) <= 0.72)
        		tmp = fma(Float64(cos(Float64(0.5 * K)) * J), Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l), U);
        	else
        		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
        	end
        	return tmp
        end
        
        code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.72], N[(N[(N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision] * J), $MachinePrecision] * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\
        \;\;\;\;\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

          1. Initial program 85.4%

            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. Add Preprocessing
          3. Taylor expanded in l around 0

            \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          4. Step-by-step derivation
            1. *-commutativeN/A

              \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. lower-*.f64N/A

              \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            3. +-commutativeN/A

              \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            4. *-commutativeN/A

              \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            5. lower-fma.f64N/A

              \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            6. +-commutativeN/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            7. *-commutativeN/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            8. lower-fma.f64N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            9. +-commutativeN/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            10. lower-fma.f64N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            11. unpow2N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            12. lower-*.f64N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            13. unpow2N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            14. lower-*.f64N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            15. unpow2N/A

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            16. lower-*.f6495.7

              \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          5. Applied rewrites95.7%

            \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          6. Step-by-step derivation
            1. lift-+.f64N/A

              \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
          7. Applied rewrites95.6%

            \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)} \]

          if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

          1. Initial program 83.5%

            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-+.f64N/A

              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
            2. lift-*.f64N/A

              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
            3. lift-*.f64N/A

              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
            4. associate-*l*N/A

              \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
            5. *-commutativeN/A

              \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
            6. lower-fma.f64N/A

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
          4. Applied rewrites100.0%

            \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
          5. Taylor expanded in K around 0

            \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
          6. Step-by-step derivation
            1. Applied rewrites99.2%

              \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
          7. Recombined 2 regimes into one program.
          8. Final simplification97.8%

            \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
          9. Add Preprocessing

          Alternative 5: 96.1% accurate, 1.3× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot K\right), J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
          (FPCore (J l K U)
           :precision binary64
           (if (<= (cos (/ K 2.0)) 0.72)
             (fma
              (*
               (*
                (fma (fma 0.016666666666666666 (* l l) 0.3333333333333333) (* l l) 2.0)
                l)
               (cos (* 0.5 K)))
              J
              U)
             (fma (* 1.0 (* 2.0 (sinh l))) J U)))
          double code(double J, double l, double K, double U) {
          	double tmp;
          	if (cos((K / 2.0)) <= 0.72) {
          		tmp = fma(((fma(fma(0.016666666666666666, (l * l), 0.3333333333333333), (l * l), 2.0) * l) * cos((0.5 * K))), J, U);
          	} else {
          		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
          	}
          	return tmp;
          }
          
          function code(J, l, K, U)
          	tmp = 0.0
          	if (cos(Float64(K / 2.0)) <= 0.72)
          		tmp = fma(Float64(Float64(fma(fma(0.016666666666666666, Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l) * cos(Float64(0.5 * K))), J, U);
          	else
          		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
          	end
          	return tmp
          end
          
          code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.72], N[(N[(N[(N[(N[(0.016666666666666666 * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] * N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\
          \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot K\right), J, U\right)\\
          
          \mathbf{else}:\\
          \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

            1. Initial program 85.4%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Add Preprocessing
            3. Taylor expanded in l around 0

              \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            4. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. lower-*.f64N/A

                \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              3. +-commutativeN/A

                \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              4. *-commutativeN/A

                \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              5. lower-fma.f64N/A

                \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + \frac{1}{60} \cdot {\ell}^{2}, {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              6. +-commutativeN/A

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\frac{1}{60} \cdot {\ell}^{2} + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              7. lower-fma.f64N/A

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              8. unpow2N/A

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              9. lower-*.f64N/A

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              10. unpow2N/A

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              11. lower-*.f6492.5

                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            5. Applied rewrites92.5%

              \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            6. Step-by-step derivation
              1. lift-+.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
              2. lift-*.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
              3. lift-*.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
              4. associate-*l*N/A

                \[\leadsto \color{blue}{J \cdot \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
              5. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
              6. lower-fma.f64N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{60}, \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
            7. Applied rewrites92.5%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot K\right), J, U\right)} \]

            if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

            1. Initial program 83.5%

              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-+.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
              2. lift-*.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
              3. lift-*.f64N/A

                \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
              4. associate-*l*N/A

                \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
              5. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
              6. lower-fma.f64N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
            4. Applied rewrites100.0%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
            5. Taylor expanded in K around 0

              \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
            6. Step-by-step derivation
              1. Applied rewrites99.2%

                \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
            7. Recombined 2 regimes into one program.
            8. Final simplification96.6%

              \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(0.016666666666666666, \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right) \cdot \cos \left(0.5 \cdot K\right), J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
            9. Add Preprocessing

            Alternative 6: 94.4% accurate, 1.3× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(0.3333333333333333, \ell \cdot \ell, 2\right) \cdot \cos \left(-0.5 \cdot K\right)\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
            (FPCore (J l K U)
             :precision binary64
             (if (<= (cos (/ K 2.0)) 0.72)
               (fma (* (* (fma 0.3333333333333333 (* l l) 2.0) (cos (* -0.5 K))) l) J U)
               (fma (* 1.0 (* 2.0 (sinh l))) J U)))
            double code(double J, double l, double K, double U) {
            	double tmp;
            	if (cos((K / 2.0)) <= 0.72) {
            		tmp = fma(((fma(0.3333333333333333, (l * l), 2.0) * cos((-0.5 * K))) * l), J, U);
            	} else {
            		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
            	}
            	return tmp;
            }
            
            function code(J, l, K, U)
            	tmp = 0.0
            	if (cos(Float64(K / 2.0)) <= 0.72)
            		tmp = fma(Float64(Float64(fma(0.3333333333333333, Float64(l * l), 2.0) * cos(Float64(-0.5 * K))) * l), J, U);
            	else
            		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
            	end
            	return tmp
            end
            
            code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.72], N[(N[(N[(N[(0.3333333333333333 * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * N[Cos[N[(-0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * l), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\
            \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(0.3333333333333333, \ell \cdot \ell, 2\right) \cdot \cos \left(-0.5 \cdot K\right)\right) \cdot \ell, J, U\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

              1. Initial program 85.4%

                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-+.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                2. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                3. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                4. associate-*l*N/A

                  \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                5. *-commutativeN/A

                  \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                6. lower-fma.f64N/A

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
              4. Applied rewrites99.9%

                \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
              5. Taylor expanded in l around 0

                \[\leadsto \mathsf{fma}\left(\color{blue}{2 \cdot \left(\ell \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
              6. Step-by-step derivation
                1. associate-*r*N/A

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                2. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                3. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot \cos \left(\frac{-1}{2} \cdot K\right), J, U\right) \]
                4. lower-cos.f64N/A

                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \color{blue}{\cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                5. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)}, J, U\right) \]
                6. lower-*.f6464.3

                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot -0.5\right)}, J, U\right) \]
              7. Applied rewrites64.3%

                \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(K \cdot -0.5\right)}, J, U\right) \]
              8. Taylor expanded in l around 0

                \[\leadsto \mathsf{fma}\left(\color{blue}{\ell \cdot \left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
              9. Step-by-step derivation
                1. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot \ell}, J, U\right) \]
                2. *-commutativeN/A

                  \[\leadsto \mathsf{fma}\left(\left(\frac{1}{3} \cdot \color{blue}{\left(\cos \left(\frac{-1}{2} \cdot K\right) \cdot {\ell}^{2}\right)} + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot \ell, J, U\right) \]
                3. associate-*r*N/A

                  \[\leadsto \mathsf{fma}\left(\left(\color{blue}{\left(\frac{1}{3} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot {\ell}^{2}} + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot \ell, J, U\right) \]
                4. lower-*.f64N/A

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\left(\frac{1}{3} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot {\ell}^{2} + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) \cdot \ell}, J, U\right) \]
              10. Applied rewrites86.5%

                \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\cos \left(-0.5 \cdot K\right) \cdot \mathsf{fma}\left(0.3333333333333333, \ell \cdot \ell, 2\right)\right) \cdot \ell}, J, U\right) \]

              if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

              1. Initial program 83.5%

                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-+.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                2. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                3. lift-*.f64N/A

                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                4. associate-*l*N/A

                  \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                5. *-commutativeN/A

                  \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                6. lower-fma.f64N/A

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
              4. Applied rewrites100.0%

                \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
              5. Taylor expanded in K around 0

                \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
              6. Step-by-step derivation
                1. Applied rewrites99.2%

                  \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
              7. Recombined 2 regimes into one program.
              8. Final simplification94.4%

                \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(0.3333333333333333, \ell \cdot \ell, 2\right) \cdot \cos \left(-0.5 \cdot K\right)\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
              9. Add Preprocessing

              Alternative 7: 94.4% accurate, 1.3× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
              (FPCore (J l K U)
               :precision binary64
               (if (<= (cos (/ K 2.0)) 0.72)
                 (fma (* (* (fma (* l l) 0.3333333333333333 2.0) l) (cos (* -0.5 K))) J U)
                 (fma (* 1.0 (* 2.0 (sinh l))) J U)))
              double code(double J, double l, double K, double U) {
              	double tmp;
              	if (cos((K / 2.0)) <= 0.72) {
              		tmp = fma(((fma((l * l), 0.3333333333333333, 2.0) * l) * cos((-0.5 * K))), J, U);
              	} else {
              		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
              	}
              	return tmp;
              }
              
              function code(J, l, K, U)
              	tmp = 0.0
              	if (cos(Float64(K / 2.0)) <= 0.72)
              		tmp = fma(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * l) * cos(Float64(-0.5 * K))), J, U);
              	else
              		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
              	end
              	return tmp
              end
              
              code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.72], N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * l), $MachinePrecision] * N[Cos[N[(-0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\
              \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right)\\
              
              \mathbf{else}:\\
              \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

                1. Initial program 85.4%

                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. Add Preprocessing
                3. Step-by-step derivation
                  1. lift-+.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                  2. lift-*.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                  3. lift-*.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                  4. associate-*l*N/A

                    \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                  5. *-commutativeN/A

                    \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                  6. lower-fma.f64N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                4. Applied rewrites99.9%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                5. Taylor expanded in l around 0

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\ell \cdot \left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) + 2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
                6. Step-by-step derivation
                  1. +-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\ell \cdot \color{blue}{\left(2 \cdot \cos \left(\frac{-1}{2} \cdot K\right) + \frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)\right)}, J, U\right) \]
                  2. distribute-lft-inN/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\ell \cdot \left(2 \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right) + \ell \cdot \left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)\right)}, J, U\right) \]
                  3. associate-*r*N/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)} + \ell \cdot \left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)\right), J, U\right) \]
                  4. *-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot \cos \left(\frac{-1}{2} \cdot K\right) + \ell \cdot \left(\frac{1}{3} \cdot \left({\ell}^{2} \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)\right), J, U\right) \]
                  5. associate-*r*N/A

                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right) + \ell \cdot \color{blue}{\left(\left(\frac{1}{3} \cdot {\ell}^{2}\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
                  6. associate-*r*N/A

                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right) + \color{blue}{\left(\ell \cdot \left(\frac{1}{3} \cdot {\ell}^{2}\right)\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                  7. distribute-rgt-outN/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\cos \left(\frac{-1}{2} \cdot K\right) \cdot \left(2 \cdot \ell + \ell \cdot \left(\frac{1}{3} \cdot {\ell}^{2}\right)\right)}, J, U\right) \]
                  8. *-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\cos \left(\frac{-1}{2} \cdot K\right) \cdot \left(\color{blue}{\ell \cdot 2} + \ell \cdot \left(\frac{1}{3} \cdot {\ell}^{2}\right)\right), J, U\right) \]
                  9. distribute-lft-inN/A

                    \[\leadsto \mathsf{fma}\left(\cos \left(\frac{-1}{2} \cdot K\right) \cdot \color{blue}{\left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}, J, U\right) \]
                  10. lower-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\cos \left(\frac{-1}{2} \cdot K\right) \cdot \left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right)}, J, U\right) \]
                  11. lower-cos.f64N/A

                    \[\leadsto \mathsf{fma}\left(\color{blue}{\cos \left(\frac{-1}{2} \cdot K\right)} \cdot \left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right), J, U\right) \]
                  12. *-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)} \cdot \left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right), J, U\right) \]
                  13. lower-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(\cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)} \cdot \left(\ell \cdot \left(2 + \frac{1}{3} \cdot {\ell}^{2}\right)\right), J, U\right) \]
                  14. *-commutativeN/A

                    \[\leadsto \mathsf{fma}\left(\cos \left(K \cdot \frac{-1}{2}\right) \cdot \color{blue}{\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right)}, J, U\right) \]
                  15. lower-*.f64N/A

                    \[\leadsto \mathsf{fma}\left(\cos \left(K \cdot \frac{-1}{2}\right) \cdot \color{blue}{\left(\left(2 + \frac{1}{3} \cdot {\ell}^{2}\right) \cdot \ell\right)}, J, U\right) \]
                7. Applied rewrites86.5%

                  \[\leadsto \mathsf{fma}\left(\color{blue}{\cos \left(K \cdot -0.5\right) \cdot \left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right)}, J, U\right) \]

                if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                1. Initial program 83.5%

                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                2. Add Preprocessing
                3. Step-by-step derivation
                  1. lift-+.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                  2. lift-*.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                  3. lift-*.f64N/A

                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                  4. associate-*l*N/A

                    \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                  5. *-commutativeN/A

                    \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                  6. lower-fma.f64N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                4. Applied rewrites100.0%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                5. Taylor expanded in K around 0

                  \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                6. Step-by-step derivation
                  1. Applied rewrites99.2%

                    \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                7. Recombined 2 regimes into one program.
                8. Final simplification94.4%

                  \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot \ell\right) \cdot \cos \left(-0.5 \cdot K\right), J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
                9. Add Preprocessing

                Alternative 8: 93.3% accurate, 1.3× speedup?

                \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
                (FPCore (J l K U)
                 :precision binary64
                 (if (<= (cos (/ K 2.0)) 0.72)
                   (fma (* (* (fma (* l l) 0.3333333333333333 2.0) J) (cos (* 0.5 K))) l U)
                   (fma (* 1.0 (* 2.0 (sinh l))) J U)))
                double code(double J, double l, double K, double U) {
                	double tmp;
                	if (cos((K / 2.0)) <= 0.72) {
                		tmp = fma(((fma((l * l), 0.3333333333333333, 2.0) * J) * cos((0.5 * K))), l, U);
                	} else {
                		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
                	}
                	return tmp;
                }
                
                function code(J, l, K, U)
                	tmp = 0.0
                	if (cos(Float64(K / 2.0)) <= 0.72)
                		tmp = fma(Float64(Float64(fma(Float64(l * l), 0.3333333333333333, 2.0) * J) * cos(Float64(0.5 * K))), l, U);
                	else
                		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
                	end
                	return tmp
                end
                
                code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], 0.72], N[(N[(N[(N[(N[(l * l), $MachinePrecision] * 0.3333333333333333 + 2.0), $MachinePrecision] * J), $MachinePrecision] * N[Cos[N[(0.5 * K), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * l + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
                
                \begin{array}{l}
                
                \\
                \begin{array}{l}
                \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\
                \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), \ell, U\right)\\
                
                \mathbf{else}:\\
                \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < 0.71999999999999997

                  1. Initial program 85.4%

                    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  2. Add Preprocessing
                  3. Taylor expanded in l around 0

                    \[\leadsto \color{blue}{U + \ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot \left({\ell}^{2} \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                  4. Step-by-step derivation
                    1. +-commutativeN/A

                      \[\leadsto \color{blue}{\ell \cdot \left(\frac{1}{3} \cdot \left(J \cdot \left({\ell}^{2} \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                    2. *-commutativeN/A

                      \[\leadsto \color{blue}{\left(\frac{1}{3} \cdot \left(J \cdot \left({\ell}^{2} \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \ell} + U \]
                    3. associate-*r*N/A

                      \[\leadsto \left(\color{blue}{\left(\frac{1}{3} \cdot J\right) \cdot \left({\ell}^{2} \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \ell + U \]
                    4. *-commutativeN/A

                      \[\leadsto \left(\left(\frac{1}{3} \cdot J\right) \cdot \color{blue}{\left(\cos \left(\frac{1}{2} \cdot K\right) \cdot {\ell}^{2}\right)} + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \ell + U \]
                    5. associate-*r*N/A

                      \[\leadsto \left(\color{blue}{\left(\left(\frac{1}{3} \cdot J\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right) \cdot {\ell}^{2}} + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \ell + U \]
                    6. associate-*r*N/A

                      \[\leadsto \left(\color{blue}{\left(\frac{1}{3} \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \cdot {\ell}^{2} + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \ell + U \]
                    7. lower-fma.f64N/A

                      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\frac{1}{3} \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot {\ell}^{2} + 2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right), \ell, U\right)} \]
                  5. Applied rewrites85.5%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot 0.5\right) \cdot \left(J \cdot \mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right)\right), \ell, U\right)} \]

                  if 0.71999999999999997 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                  1. Initial program 83.5%

                    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                  2. Add Preprocessing
                  3. Step-by-step derivation
                    1. lift-+.f64N/A

                      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                    2. lift-*.f64N/A

                      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                    3. lift-*.f64N/A

                      \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                    4. associate-*l*N/A

                      \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                    5. *-commutativeN/A

                      \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                    6. lower-fma.f64N/A

                      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                  4. Applied rewrites100.0%

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                  5. Taylor expanded in K around 0

                    \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                  6. Step-by-step derivation
                    1. Applied rewrites99.2%

                      \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                  7. Recombined 2 regimes into one program.
                  8. Final simplification94.0%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq 0.72:\\ \;\;\;\;\mathsf{fma}\left(\left(\mathsf{fma}\left(\ell \cdot \ell, 0.3333333333333333, 2\right) \cdot J\right) \cdot \cos \left(0.5 \cdot K\right), \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
                  9. Add Preprocessing

                  Alternative 9: 87.6% accurate, 1.3× speedup?

                  \[\begin{array}{l} \\ \begin{array}{l} t_0 := 2 \cdot \sinh \ell\\ \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot t\_0, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot t\_0, J, U\right)\\ \end{array} \end{array} \]
                  (FPCore (J l K U)
                   :precision binary64
                   (let* ((t_0 (* 2.0 (sinh l))))
                     (if (<= (cos (/ K 2.0)) -0.005)
                       (fma (* (fma (* K K) -0.125 1.0) t_0) J U)
                       (fma (* 1.0 t_0) J U))))
                  double code(double J, double l, double K, double U) {
                  	double t_0 = 2.0 * sinh(l);
                  	double tmp;
                  	if (cos((K / 2.0)) <= -0.005) {
                  		tmp = fma((fma((K * K), -0.125, 1.0) * t_0), J, U);
                  	} else {
                  		tmp = fma((1.0 * t_0), J, U);
                  	}
                  	return tmp;
                  }
                  
                  function code(J, l, K, U)
                  	t_0 = Float64(2.0 * sinh(l))
                  	tmp = 0.0
                  	if (cos(Float64(K / 2.0)) <= -0.005)
                  		tmp = fma(Float64(fma(Float64(K * K), -0.125, 1.0) * t_0), J, U);
                  	else
                  		tmp = fma(Float64(1.0 * t_0), J, U);
                  	end
                  	return tmp
                  end
                  
                  code[J_, l_, K_, U_] := Block[{t$95$0 = N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.005], N[(N[(N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision] * t$95$0), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(1.0 * t$95$0), $MachinePrecision] * J + U), $MachinePrecision]]]
                  
                  \begin{array}{l}
                  
                  \\
                  \begin{array}{l}
                  t_0 := 2 \cdot \sinh \ell\\
                  \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\
                  \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot t\_0, J, U\right)\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;\mathsf{fma}\left(1 \cdot t\_0, J, U\right)\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.0050000000000000001

                    1. Initial program 89.9%

                      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                    2. Add Preprocessing
                    3. Step-by-step derivation
                      1. lift-+.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                      2. lift-*.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                      3. lift-*.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                      4. associate-*l*N/A

                        \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                      5. *-commutativeN/A

                        \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                      6. lower-fma.f64N/A

                        \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                    4. Applied rewrites99.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                    5. Taylor expanded in K around 0

                      \[\leadsto \mathsf{fma}\left(\color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                    6. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\frac{-1}{8} \cdot {K}^{2} + 1\right)} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      2. *-commutativeN/A

                        \[\leadsto \mathsf{fma}\left(\left(\color{blue}{{K}^{2} \cdot \frac{-1}{8}} + 1\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      3. lower-fma.f64N/A

                        \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right)} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      4. unpow2N/A

                        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, \frac{-1}{8}, 1\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      5. lower-*.f6464.0

                        \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, -0.125, 1\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                    7. Applied rewrites64.0%

                      \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]

                    if -0.0050000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                    1. Initial program 82.5%

                      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                    2. Add Preprocessing
                    3. Step-by-step derivation
                      1. lift-+.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                      2. lift-*.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                      3. lift-*.f64N/A

                        \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                      4. associate-*l*N/A

                        \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                      5. *-commutativeN/A

                        \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                      6. lower-fma.f64N/A

                        \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                    4. Applied rewrites100.0%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                    5. Taylor expanded in K around 0

                      \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                    6. Step-by-step derivation
                      1. Applied rewrites95.6%

                        \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                    7. Recombined 2 regimes into one program.
                    8. Final simplification88.3%

                      \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
                    9. Add Preprocessing

                    Alternative 10: 87.1% accurate, 1.4× speedup?

                    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \end{array} \]
                    (FPCore (J l K U)
                     :precision binary64
                     (if (<= (cos (/ K 2.0)) -0.005)
                       (fma
                        (* (fma (* K K) -0.125 1.0) J)
                        (*
                         (fma
                          (fma
                           (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
                           (* l l)
                           0.3333333333333333)
                          (* l l)
                          2.0)
                         l)
                        U)
                       (fma (* 1.0 (* 2.0 (sinh l))) J U)))
                    double code(double J, double l, double K, double U) {
                    	double tmp;
                    	if (cos((K / 2.0)) <= -0.005) {
                    		tmp = fma((fma((K * K), -0.125, 1.0) * J), (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l), U);
                    	} else {
                    		tmp = fma((1.0 * (2.0 * sinh(l))), J, U);
                    	}
                    	return tmp;
                    }
                    
                    function code(J, l, K, U)
                    	tmp = 0.0
                    	if (cos(Float64(K / 2.0)) <= -0.005)
                    		tmp = fma(Float64(fma(Float64(K * K), -0.125, 1.0) * J), Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l), U);
                    	else
                    		tmp = fma(Float64(1.0 * Float64(2.0 * sinh(l))), J, U);
                    	end
                    	return tmp
                    end
                    
                    code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.005], N[(N[(N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision] * J), $MachinePrecision] * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] + U), $MachinePrecision], N[(N[(1.0 * N[(2.0 * N[Sinh[l], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * J + U), $MachinePrecision]]
                    
                    \begin{array}{l}
                    
                    \\
                    \begin{array}{l}
                    \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\
                    \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\
                    
                    \mathbf{else}:\\
                    \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\
                    
                    
                    \end{array}
                    \end{array}
                    
                    Derivation
                    1. Split input into 2 regimes
                    2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.0050000000000000001

                      1. Initial program 89.9%

                        \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                      2. Add Preprocessing
                      3. Taylor expanded in l around 0

                        \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                      4. Step-by-step derivation
                        1. *-commutativeN/A

                          \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        2. lower-*.f64N/A

                          \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        3. +-commutativeN/A

                          \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        4. *-commutativeN/A

                          \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        5. lower-fma.f64N/A

                          \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        6. +-commutativeN/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        7. *-commutativeN/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        8. lower-fma.f64N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        9. +-commutativeN/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        10. lower-fma.f64N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        11. unpow2N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        12. lower-*.f64N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        13. unpow2N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        14. lower-*.f64N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        15. unpow2N/A

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        16. lower-*.f6493.0

                          \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                      5. Applied rewrites93.0%

                        \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                      6. Step-by-step derivation
                        1. lift-+.f64N/A

                          \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                      7. Applied rewrites92.9%

                        \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)} \]
                      8. Taylor expanded in K around 0

                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                      9. Step-by-step derivation
                        1. +-commutativeN/A

                          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\frac{-1}{8} \cdot {K}^{2} + 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        2. *-commutativeN/A

                          \[\leadsto \mathsf{fma}\left(\left(\color{blue}{{K}^{2} \cdot \frac{-1}{8}} + 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        3. lower-fma.f64N/A

                          \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        4. unpow2N/A

                          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, \frac{-1}{8}, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        5. lower-*.f6464.0

                          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, -0.125, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                      10. Applied rewrites64.0%

                        \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]

                      if -0.0050000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                      1. Initial program 82.5%

                        \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                      2. Add Preprocessing
                      3. Step-by-step derivation
                        1. lift-+.f64N/A

                          \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                        2. lift-*.f64N/A

                          \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                        3. lift-*.f64N/A

                          \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                        4. associate-*l*N/A

                          \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                        5. *-commutativeN/A

                          \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                        6. lower-fma.f64N/A

                          \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                      4. Applied rewrites100.0%

                        \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                      5. Taylor expanded in K around 0

                        \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      6. Step-by-step derivation
                        1. Applied rewrites95.6%

                          \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot \left(\sinh \ell \cdot 2\right), J, U\right) \]
                      7. Recombined 2 regimes into one program.
                      8. Final simplification88.3%

                        \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot \left(2 \cdot \sinh \ell\right), J, U\right)\\ \end{array} \]
                      9. Add Preprocessing

                      Alternative 11: 83.5% accurate, 1.9× speedup?

                      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\\ \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot J, t\_0, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot J, t\_0, U\right)\\ \end{array} \end{array} \]
                      (FPCore (J l K U)
                       :precision binary64
                       (let* ((t_0
                               (*
                                (fma
                                 (fma
                                  (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
                                  (* l l)
                                  0.3333333333333333)
                                 (* l l)
                                 2.0)
                                l)))
                         (if (<= (cos (/ K 2.0)) -0.005)
                           (fma (* (fma (* K K) -0.125 1.0) J) t_0 U)
                           (fma (* 1.0 J) t_0 U))))
                      double code(double J, double l, double K, double U) {
                      	double t_0 = fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l;
                      	double tmp;
                      	if (cos((K / 2.0)) <= -0.005) {
                      		tmp = fma((fma((K * K), -0.125, 1.0) * J), t_0, U);
                      	} else {
                      		tmp = fma((1.0 * J), t_0, U);
                      	}
                      	return tmp;
                      }
                      
                      function code(J, l, K, U)
                      	t_0 = Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l)
                      	tmp = 0.0
                      	if (cos(Float64(K / 2.0)) <= -0.005)
                      		tmp = fma(Float64(fma(Float64(K * K), -0.125, 1.0) * J), t_0, U);
                      	else
                      		tmp = fma(Float64(1.0 * J), t_0, U);
                      	end
                      	return tmp
                      end
                      
                      code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision]}, If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.005], N[(N[(N[(N[(K * K), $MachinePrecision] * -0.125 + 1.0), $MachinePrecision] * J), $MachinePrecision] * t$95$0 + U), $MachinePrecision], N[(N[(1.0 * J), $MachinePrecision] * t$95$0 + U), $MachinePrecision]]]
                      
                      \begin{array}{l}
                      
                      \\
                      \begin{array}{l}
                      t_0 := \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\\
                      \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\
                      \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.125, 1\right) \cdot J, t\_0, U\right)\\
                      
                      \mathbf{else}:\\
                      \;\;\;\;\mathsf{fma}\left(1 \cdot J, t\_0, U\right)\\
                      
                      
                      \end{array}
                      \end{array}
                      
                      Derivation
                      1. Split input into 2 regimes
                      2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.0050000000000000001

                        1. Initial program 89.9%

                          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        2. Add Preprocessing
                        3. Taylor expanded in l around 0

                          \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        4. Step-by-step derivation
                          1. *-commutativeN/A

                            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          2. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          3. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          4. *-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          5. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          6. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          7. *-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          8. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          9. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          10. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          11. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          12. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          13. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          14. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          15. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          16. lower-*.f6493.0

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        5. Applied rewrites93.0%

                          \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        6. Step-by-step derivation
                          1. lift-+.f64N/A

                            \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                        7. Applied rewrites92.9%

                          \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)} \]
                        8. Taylor expanded in K around 0

                          \[\leadsto \mathsf{fma}\left(\color{blue}{\left(1 + \frac{-1}{8} \cdot {K}^{2}\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        9. Step-by-step derivation
                          1. +-commutativeN/A

                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\frac{-1}{8} \cdot {K}^{2} + 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                          2. *-commutativeN/A

                            \[\leadsto \mathsf{fma}\left(\left(\color{blue}{{K}^{2} \cdot \frac{-1}{8}} + 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                          3. lower-fma.f64N/A

                            \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left({K}^{2}, \frac{-1}{8}, 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                          4. unpow2N/A

                            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, \frac{-1}{8}, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                          5. lower-*.f6464.0

                            \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{K \cdot K}, -0.125, 1\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        10. Applied rewrites64.0%

                          \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(K \cdot K, -0.125, 1\right)} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]

                        if -0.0050000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                        1. Initial program 82.5%

                          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        2. Add Preprocessing
                        3. Taylor expanded in l around 0

                          \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        4. Step-by-step derivation
                          1. *-commutativeN/A

                            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          2. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          3. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          4. *-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          5. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          6. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          7. *-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          8. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          9. +-commutativeN/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          10. lower-fma.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          11. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          12. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          13. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          14. lower-*.f64N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          15. unpow2N/A

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          16. lower-*.f6494.7

                            \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        5. Applied rewrites94.7%

                          \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                        6. Step-by-step derivation
                          1. lift-+.f64N/A

                            \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                        7. Applied rewrites94.6%

                          \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)} \]
                        8. Taylor expanded in K around 0

                          \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        9. Step-by-step derivation
                          1. Applied rewrites90.3%

                            \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                        10. Recombined 2 regimes into one program.
                        11. Add Preprocessing

                        Alternative 12: 82.1% accurate, 2.0× speedup?

                        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \end{array} \end{array} \]
                        (FPCore (J l K U)
                         :precision binary64
                         (if (<= (cos (/ K 2.0)) -0.005)
                           (fma (* (fma (* K K) -0.25 2.0) l) J U)
                           (fma
                            (* 1.0 J)
                            (*
                             (fma
                              (fma
                               (fma 0.0003968253968253968 (* l l) 0.016666666666666666)
                               (* l l)
                               0.3333333333333333)
                              (* l l)
                              2.0)
                             l)
                            U)))
                        double code(double J, double l, double K, double U) {
                        	double tmp;
                        	if (cos((K / 2.0)) <= -0.005) {
                        		tmp = fma((fma((K * K), -0.25, 2.0) * l), J, U);
                        	} else {
                        		tmp = fma((1.0 * J), (fma(fma(fma(0.0003968253968253968, (l * l), 0.016666666666666666), (l * l), 0.3333333333333333), (l * l), 2.0) * l), U);
                        	}
                        	return tmp;
                        }
                        
                        function code(J, l, K, U)
                        	tmp = 0.0
                        	if (cos(Float64(K / 2.0)) <= -0.005)
                        		tmp = fma(Float64(fma(Float64(K * K), -0.25, 2.0) * l), J, U);
                        	else
                        		tmp = fma(Float64(1.0 * J), Float64(fma(fma(fma(0.0003968253968253968, Float64(l * l), 0.016666666666666666), Float64(l * l), 0.3333333333333333), Float64(l * l), 2.0) * l), U);
                        	end
                        	return tmp
                        end
                        
                        code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.005], N[(N[(N[(N[(K * K), $MachinePrecision] * -0.25 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(1.0 * J), $MachinePrecision] * N[(N[(N[(N[(0.0003968253968253968 * N[(l * l), $MachinePrecision] + 0.016666666666666666), $MachinePrecision] * N[(l * l), $MachinePrecision] + 0.3333333333333333), $MachinePrecision] * N[(l * l), $MachinePrecision] + 2.0), $MachinePrecision] * l), $MachinePrecision] + U), $MachinePrecision]]
                        
                        \begin{array}{l}
                        
                        \\
                        \begin{array}{l}
                        \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\
                        \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\
                        
                        \mathbf{else}:\\
                        \;\;\;\;\mathsf{fma}\left(1 \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\
                        
                        
                        \end{array}
                        \end{array}
                        
                        Derivation
                        1. Split input into 2 regimes
                        2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.0050000000000000001

                          1. Initial program 89.9%

                            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                          2. Add Preprocessing
                          3. Step-by-step derivation
                            1. lift-+.f64N/A

                              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                            2. lift-*.f64N/A

                              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                            3. lift-*.f64N/A

                              \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                            4. associate-*l*N/A

                              \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                            5. *-commutativeN/A

                              \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                            6. lower-fma.f64N/A

                              \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                          4. Applied rewrites99.9%

                            \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                          5. Taylor expanded in l around 0

                            \[\leadsto \mathsf{fma}\left(\color{blue}{2 \cdot \left(\ell \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
                          6. Step-by-step derivation
                            1. associate-*r*N/A

                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                            2. lower-*.f64N/A

                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                            3. lower-*.f64N/A

                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot \cos \left(\frac{-1}{2} \cdot K\right), J, U\right) \]
                            4. lower-cos.f64N/A

                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \color{blue}{\cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                            5. *-commutativeN/A

                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)}, J, U\right) \]
                            6. lower-*.f6459.3

                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot -0.5\right)}, J, U\right) \]
                          7. Applied rewrites59.3%

                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(K \cdot -0.5\right)}, J, U\right) \]
                          8. Taylor expanded in K around 0

                            \[\leadsto \mathsf{fma}\left(\frac{-1}{4} \cdot \left({K}^{2} \cdot \ell\right) + \color{blue}{2 \cdot \ell}, J, U\right) \]
                          9. Step-by-step derivation
                            1. Applied rewrites59.3%

                              \[\leadsto \mathsf{fma}\left(\ell \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.25, 2\right)}, J, U\right) \]

                            if -0.0050000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                            1. Initial program 82.5%

                              \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                            2. Add Preprocessing
                            3. Taylor expanded in l around 0

                              \[\leadsto \left(J \cdot \color{blue}{\left(\ell \cdot \left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right)\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                            4. Step-by-step derivation
                              1. *-commutativeN/A

                                \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              2. lower-*.f64N/A

                                \[\leadsto \left(J \cdot \color{blue}{\left(\left(2 + {\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right)\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              3. +-commutativeN/A

                                \[\leadsto \left(J \cdot \left(\color{blue}{\left({\ell}^{2} \cdot \left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) + 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              4. *-commutativeN/A

                                \[\leadsto \left(J \cdot \left(\left(\color{blue}{\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right)\right) \cdot {\ell}^{2}} + 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              5. lower-fma.f64N/A

                                \[\leadsto \left(J \cdot \left(\color{blue}{\mathsf{fma}\left(\frac{1}{3} + {\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right), {\ell}^{2}, 2\right)} \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              6. +-commutativeN/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{{\ell}^{2} \cdot \left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) + \frac{1}{3}}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              7. *-commutativeN/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}\right) \cdot {\ell}^{2}} + \frac{1}{3}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              8. lower-fma.f64N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{60} + \frac{1}{2520} \cdot {\ell}^{2}, {\ell}^{2}, \frac{1}{3}\right)}, {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              9. +-commutativeN/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2520} \cdot {\ell}^{2} + \frac{1}{60}}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              10. lower-fma.f64N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{1}{2520}, {\ell}^{2}, \frac{1}{60}\right)}, {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              11. unpow2N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              12. lower-*.f64N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \color{blue}{\ell \cdot \ell}, \frac{1}{60}\right), {\ell}^{2}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              13. unpow2N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              14. lower-*.f64N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \color{blue}{\ell \cdot \ell}, \frac{1}{3}\right), {\ell}^{2}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              15. unpow2N/A

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              16. lower-*.f6494.7

                                \[\leadsto \left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \color{blue}{\ell \cdot \ell}, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                            5. Applied rewrites94.7%

                              \[\leadsto \left(J \cdot \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                            6. Step-by-step derivation
                              1. lift-+.f64N/A

                                \[\leadsto \color{blue}{\left(J \cdot \left(\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                            7. Applied rewrites94.6%

                              \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(0.5 \cdot K\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)} \]
                            8. Taylor expanded in K around 0

                              \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{2520}, \ell \cdot \ell, \frac{1}{60}\right), \ell \cdot \ell, \frac{1}{3}\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                            9. Step-by-step derivation
                              1. Applied rewrites90.3%

                                \[\leadsto \mathsf{fma}\left(\color{blue}{1} \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right) \]
                            10. Recombined 2 regimes into one program.
                            11. Final simplification83.1%

                              \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(1 \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.0003968253968253968, \ell \cdot \ell, 0.016666666666666666\right), \ell \cdot \ell, 0.3333333333333333\right), \ell \cdot \ell, 2\right) \cdot \ell, U\right)\\ \end{array} \]
                            12. Add Preprocessing

                            Alternative 13: 63.6% accurate, 2.3× speedup?

                            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\frac{J \cdot \ell}{U}, 2, 1\right) \cdot U\\ \end{array} \end{array} \]
                            (FPCore (J l K U)
                             :precision binary64
                             (if (<= (cos (/ K 2.0)) -0.005)
                               (fma (* (fma (* K K) -0.25 2.0) l) J U)
                               (* (fma (/ (* J l) U) 2.0 1.0) U)))
                            double code(double J, double l, double K, double U) {
                            	double tmp;
                            	if (cos((K / 2.0)) <= -0.005) {
                            		tmp = fma((fma((K * K), -0.25, 2.0) * l), J, U);
                            	} else {
                            		tmp = fma(((J * l) / U), 2.0, 1.0) * U;
                            	}
                            	return tmp;
                            }
                            
                            function code(J, l, K, U)
                            	tmp = 0.0
                            	if (cos(Float64(K / 2.0)) <= -0.005)
                            		tmp = fma(Float64(fma(Float64(K * K), -0.25, 2.0) * l), J, U);
                            	else
                            		tmp = Float64(fma(Float64(Float64(J * l) / U), 2.0, 1.0) * U);
                            	end
                            	return tmp
                            end
                            
                            code[J_, l_, K_, U_] := If[LessEqual[N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision], -0.005], N[(N[(N[(N[(K * K), $MachinePrecision] * -0.25 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J + U), $MachinePrecision], N[(N[(N[(N[(J * l), $MachinePrecision] / U), $MachinePrecision] * 2.0 + 1.0), $MachinePrecision] * U), $MachinePrecision]]
                            
                            \begin{array}{l}
                            
                            \\
                            \begin{array}{l}
                            \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\
                            \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\
                            
                            \mathbf{else}:\\
                            \;\;\;\;\mathsf{fma}\left(\frac{J \cdot \ell}{U}, 2, 1\right) \cdot U\\
                            
                            
                            \end{array}
                            \end{array}
                            
                            Derivation
                            1. Split input into 2 regimes
                            2. if (cos.f64 (/.f64 K #s(literal 2 binary64))) < -0.0050000000000000001

                              1. Initial program 89.9%

                                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                              2. Add Preprocessing
                              3. Step-by-step derivation
                                1. lift-+.f64N/A

                                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                                2. lift-*.f64N/A

                                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                                3. lift-*.f64N/A

                                  \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                                4. associate-*l*N/A

                                  \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                                5. *-commutativeN/A

                                  \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                                6. lower-fma.f64N/A

                                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                              4. Applied rewrites99.9%

                                \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                              5. Taylor expanded in l around 0

                                \[\leadsto \mathsf{fma}\left(\color{blue}{2 \cdot \left(\ell \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
                              6. Step-by-step derivation
                                1. associate-*r*N/A

                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                2. lower-*.f64N/A

                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                3. lower-*.f64N/A

                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot \cos \left(\frac{-1}{2} \cdot K\right), J, U\right) \]
                                4. lower-cos.f64N/A

                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \color{blue}{\cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                5. *-commutativeN/A

                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)}, J, U\right) \]
                                6. lower-*.f6459.3

                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot -0.5\right)}, J, U\right) \]
                              7. Applied rewrites59.3%

                                \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(K \cdot -0.5\right)}, J, U\right) \]
                              8. Taylor expanded in K around 0

                                \[\leadsto \mathsf{fma}\left(\frac{-1}{4} \cdot \left({K}^{2} \cdot \ell\right) + \color{blue}{2 \cdot \ell}, J, U\right) \]
                              9. Step-by-step derivation
                                1. Applied rewrites59.3%

                                  \[\leadsto \mathsf{fma}\left(\ell \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.25, 2\right)}, J, U\right) \]

                                if -0.0050000000000000001 < (cos.f64 (/.f64 K #s(literal 2 binary64)))

                                1. Initial program 82.5%

                                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                2. Add Preprocessing
                                3. Taylor expanded in l around 0

                                  \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                4. Step-by-step derivation
                                  1. +-commutativeN/A

                                    \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                  2. associate-*r*N/A

                                    \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                  3. associate-*r*N/A

                                    \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                  4. associate-*r*N/A

                                    \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                  5. *-commutativeN/A

                                    \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                  6. lower-fma.f64N/A

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

                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                  8. *-commutativeN/A

                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                  9. lower-*.f64N/A

                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                  10. lower-*.f64N/A

                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                  11. lower-cos.f64N/A

                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                  12. *-commutativeN/A

                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                  13. lower-*.f6466.0

                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                5. Applied rewrites66.0%

                                  \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                6. Taylor expanded in K around 0

                                  \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                7. Step-by-step derivation
                                  1. Applied rewrites61.6%

                                    \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                  2. Taylor expanded in U around inf

                                    \[\leadsto U \cdot \left(1 + \color{blue}{2 \cdot \frac{J \cdot \ell}{U}}\right) \]
                                  3. Step-by-step derivation
                                    1. Applied rewrites66.2%

                                      \[\leadsto \mathsf{fma}\left(\frac{\ell \cdot J}{U}, 2, 1\right) \cdot U \]
                                  4. Recombined 2 regimes into one program.
                                  5. Final simplification64.6%

                                    \[\leadsto \begin{array}{l} \mathbf{if}\;\cos \left(\frac{K}{2}\right) \leq -0.005:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\frac{J \cdot \ell}{U}, 2, 1\right) \cdot U\\ \end{array} \]
                                  6. Add Preprocessing

                                  Alternative 14: 61.4% accurate, 4.9× speedup?

                                  \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;\mathsf{fma}\left(\ell, \mathsf{fma}\left(-0.25, K \cdot K, 2\right), \frac{U}{J}\right) \cdot J\\ \mathbf{elif}\;\ell \leq 390:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{elif}\;\ell \leq 4.8 \cdot 10^{+267}:\\ \;\;\;\;\frac{\mathsf{fma}\left(-4, \left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot J, U \cdot U\right)}{\mathsf{fma}\left(-2, J \cdot \ell, U\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(0.0026041666666666665, K \cdot K, -0.125\right), K \cdot K, 1\right), U\right)\\ \end{array} \end{array} \]
                                  (FPCore (J l K U)
                                   :precision binary64
                                   (if (<= l -2.8e-5)
                                     (* (fma l (fma -0.25 (* K K) 2.0) (/ U J)) J)
                                     (if (<= l 390.0)
                                       (fma (* J l) 2.0 U)
                                       (if (<= l 4.8e+267)
                                         (/ (fma -4.0 (* (* (* l l) J) J) (* U U)) (fma -2.0 (* J l) U))
                                         (fma
                                          (* (* 2.0 l) J)
                                          (fma (fma 0.0026041666666666665 (* K K) -0.125) (* K K) 1.0)
                                          U)))))
                                  double code(double J, double l, double K, double U) {
                                  	double tmp;
                                  	if (l <= -2.8e-5) {
                                  		tmp = fma(l, fma(-0.25, (K * K), 2.0), (U / J)) * J;
                                  	} else if (l <= 390.0) {
                                  		tmp = fma((J * l), 2.0, U);
                                  	} else if (l <= 4.8e+267) {
                                  		tmp = fma(-4.0, (((l * l) * J) * J), (U * U)) / fma(-2.0, (J * l), U);
                                  	} else {
                                  		tmp = fma(((2.0 * l) * J), fma(fma(0.0026041666666666665, (K * K), -0.125), (K * K), 1.0), U);
                                  	}
                                  	return tmp;
                                  }
                                  
                                  function code(J, l, K, U)
                                  	tmp = 0.0
                                  	if (l <= -2.8e-5)
                                  		tmp = Float64(fma(l, fma(-0.25, Float64(K * K), 2.0), Float64(U / J)) * J);
                                  	elseif (l <= 390.0)
                                  		tmp = fma(Float64(J * l), 2.0, U);
                                  	elseif (l <= 4.8e+267)
                                  		tmp = Float64(fma(-4.0, Float64(Float64(Float64(l * l) * J) * J), Float64(U * U)) / fma(-2.0, Float64(J * l), U));
                                  	else
                                  		tmp = fma(Float64(Float64(2.0 * l) * J), fma(fma(0.0026041666666666665, Float64(K * K), -0.125), Float64(K * K), 1.0), U);
                                  	end
                                  	return tmp
                                  end
                                  
                                  code[J_, l_, K_, U_] := If[LessEqual[l, -2.8e-5], N[(N[(l * N[(-0.25 * N[(K * K), $MachinePrecision] + 2.0), $MachinePrecision] + N[(U / J), $MachinePrecision]), $MachinePrecision] * J), $MachinePrecision], If[LessEqual[l, 390.0], N[(N[(J * l), $MachinePrecision] * 2.0 + U), $MachinePrecision], If[LessEqual[l, 4.8e+267], N[(N[(-4.0 * N[(N[(N[(l * l), $MachinePrecision] * J), $MachinePrecision] * J), $MachinePrecision] + N[(U * U), $MachinePrecision]), $MachinePrecision] / N[(-2.0 * N[(J * l), $MachinePrecision] + U), $MachinePrecision]), $MachinePrecision], N[(N[(N[(2.0 * l), $MachinePrecision] * J), $MachinePrecision] * N[(N[(0.0026041666666666665 * N[(K * K), $MachinePrecision] + -0.125), $MachinePrecision] * N[(K * K), $MachinePrecision] + 1.0), $MachinePrecision] + U), $MachinePrecision]]]]
                                  
                                  \begin{array}{l}
                                  
                                  \\
                                  \begin{array}{l}
                                  \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\
                                  \;\;\;\;\mathsf{fma}\left(\ell, \mathsf{fma}\left(-0.25, K \cdot K, 2\right), \frac{U}{J}\right) \cdot J\\
                                  
                                  \mathbf{elif}\;\ell \leq 390:\\
                                  \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\
                                  
                                  \mathbf{elif}\;\ell \leq 4.8 \cdot 10^{+267}:\\
                                  \;\;\;\;\frac{\mathsf{fma}\left(-4, \left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot J, U \cdot U\right)}{\mathsf{fma}\left(-2, J \cdot \ell, U\right)}\\
                                  
                                  \mathbf{else}:\\
                                  \;\;\;\;\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(0.0026041666666666665, K \cdot K, -0.125\right), K \cdot K, 1\right), U\right)\\
                                  
                                  
                                  \end{array}
                                  \end{array}
                                  
                                  Derivation
                                  1. Split input into 4 regimes
                                  2. if l < -2.79999999999999996e-5

                                    1. Initial program 99.7%

                                      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                    2. Add Preprocessing
                                    3. Taylor expanded in l around 0

                                      \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                    4. Step-by-step derivation
                                      1. +-commutativeN/A

                                        \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                      2. associate-*r*N/A

                                        \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                      3. associate-*r*N/A

                                        \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                      4. associate-*r*N/A

                                        \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                      5. *-commutativeN/A

                                        \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                      6. lower-fma.f64N/A

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

                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                      8. *-commutativeN/A

                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                      9. lower-*.f64N/A

                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                      10. lower-*.f64N/A

                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                      11. lower-cos.f64N/A

                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                      12. *-commutativeN/A

                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                      13. lower-*.f6425.1

                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                    5. Applied rewrites25.1%

                                      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                    6. Taylor expanded in J around inf

                                      \[\leadsto J \cdot \color{blue}{\left(2 \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right) + \frac{U}{J}\right)} \]
                                    7. Step-by-step derivation
                                      1. Applied rewrites34.1%

                                        \[\leadsto \mathsf{fma}\left(2 \cdot \ell, \cos \left(0.5 \cdot K\right), \frac{U}{J}\right) \cdot \color{blue}{J} \]
                                      2. Taylor expanded in K around 0

                                        \[\leadsto \left(\frac{-1}{4} \cdot \left({K}^{2} \cdot \ell\right) + \left(2 \cdot \ell + \frac{U}{J}\right)\right) \cdot J \]
                                      3. Step-by-step derivation
                                        1. Applied rewrites42.7%

                                          \[\leadsto \mathsf{fma}\left(\ell, \mathsf{fma}\left(-0.25, K \cdot K, 2\right), \frac{U}{J}\right) \cdot J \]

                                        if -2.79999999999999996e-5 < l < 390

                                        1. Initial program 70.2%

                                          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                        2. Add Preprocessing
                                        3. Taylor expanded in l around 0

                                          \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                        4. Step-by-step derivation
                                          1. +-commutativeN/A

                                            \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                          2. associate-*r*N/A

                                            \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                          3. associate-*r*N/A

                                            \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                          4. associate-*r*N/A

                                            \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                          5. *-commutativeN/A

                                            \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                          6. lower-fma.f64N/A

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

                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                          8. *-commutativeN/A

                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                          9. lower-*.f64N/A

                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                          10. lower-*.f64N/A

                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                          11. lower-cos.f64N/A

                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                          12. *-commutativeN/A

                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                          13. lower-*.f6499.9

                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                        5. Applied rewrites99.9%

                                          \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                        6. Taylor expanded in K around 0

                                          \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                        7. Step-by-step derivation
                                          1. Applied rewrites89.1%

                                            \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]

                                          if 390 < l < 4.79999999999999969e267

                                          1. Initial program 100.0%

                                            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                          2. Add Preprocessing
                                          3. Taylor expanded in l around 0

                                            \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                          4. Step-by-step derivation
                                            1. +-commutativeN/A

                                              \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                            2. associate-*r*N/A

                                              \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                            3. associate-*r*N/A

                                              \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                            4. associate-*r*N/A

                                              \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                            5. *-commutativeN/A

                                              \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                            6. lower-fma.f64N/A

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

                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                            8. *-commutativeN/A

                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                            9. lower-*.f64N/A

                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                            10. lower-*.f64N/A

                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                            11. lower-cos.f64N/A

                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                            12. *-commutativeN/A

                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                            13. lower-*.f6419.0

                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                          5. Applied rewrites19.0%

                                            \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                          6. Taylor expanded in K around 0

                                            \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                          7. Step-by-step derivation
                                            1. Applied rewrites12.2%

                                              \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                            2. Step-by-step derivation
                                              1. Applied rewrites12.2%

                                                \[\leadsto \frac{1}{\frac{1}{\color{blue}{\mathsf{fma}\left(\ell \cdot J, 2, U\right)}}} \]
                                              2. Applied rewrites45.1%

                                                \[\leadsto \frac{\mathsf{fma}\left(-4, \left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot J, U \cdot U\right)}{\mathsf{fma}\left(-2, \color{blue}{\ell \cdot J}, U\right)} \]

                                              if 4.79999999999999969e267 < l

                                              1. Initial program 100.0%

                                                \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                              2. Add Preprocessing
                                              3. Taylor expanded in l around 0

                                                \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                              4. Step-by-step derivation
                                                1. +-commutativeN/A

                                                  \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                2. associate-*r*N/A

                                                  \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                3. associate-*r*N/A

                                                  \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                4. associate-*r*N/A

                                                  \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                5. *-commutativeN/A

                                                  \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                6. lower-fma.f64N/A

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

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                8. *-commutativeN/A

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                9. lower-*.f64N/A

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                10. lower-*.f64N/A

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                11. lower-cos.f64N/A

                                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                12. *-commutativeN/A

                                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                13. lower-*.f6448.4

                                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                              5. Applied rewrites48.4%

                                                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                              6. Taylor expanded in K around 0

                                                \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, 1 + \color{blue}{{K}^{2} \cdot \left(\frac{1}{384} \cdot {K}^{2} - \frac{1}{8}\right)}, U\right) \]
                                              7. Step-by-step derivation
                                                1. Applied rewrites64.6%

                                                  \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(0.0026041666666666665, K \cdot K, -0.125\right), \color{blue}{K \cdot K}, 1\right), U\right) \]
                                              8. Recombined 4 regimes into one program.
                                              9. Final simplification68.5%

                                                \[\leadsto \begin{array}{l} \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;\mathsf{fma}\left(\ell, \mathsf{fma}\left(-0.25, K \cdot K, 2\right), \frac{U}{J}\right) \cdot J\\ \mathbf{elif}\;\ell \leq 390:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{elif}\;\ell \leq 4.8 \cdot 10^{+267}:\\ \;\;\;\;\frac{\mathsf{fma}\left(-4, \left(\left(\ell \cdot \ell\right) \cdot J\right) \cdot J, U \cdot U\right)}{\mathsf{fma}\left(-2, J \cdot \ell, U\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \mathsf{fma}\left(\mathsf{fma}\left(0.0026041666666666665, K \cdot K, -0.125\right), K \cdot K, 1\right), U\right)\\ \end{array} \]
                                              10. Add Preprocessing

                                              Alternative 15: 61.9% accurate, 9.4× speedup?

                                              \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;\ell \leq 4.1 \cdot 10^{+15}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
                                              (FPCore (J l K U)
                                               :precision binary64
                                               (let* ((t_0 (fma (* (fma (* K K) -0.25 2.0) l) J U)))
                                                 (if (<= l -2.8e-5) t_0 (if (<= l 4.1e+15) (fma (* J l) 2.0 U) t_0))))
                                              double code(double J, double l, double K, double U) {
                                              	double t_0 = fma((fma((K * K), -0.25, 2.0) * l), J, U);
                                              	double tmp;
                                              	if (l <= -2.8e-5) {
                                              		tmp = t_0;
                                              	} else if (l <= 4.1e+15) {
                                              		tmp = fma((J * l), 2.0, U);
                                              	} else {
                                              		tmp = t_0;
                                              	}
                                              	return tmp;
                                              }
                                              
                                              function code(J, l, K, U)
                                              	t_0 = fma(Float64(fma(Float64(K * K), -0.25, 2.0) * l), J, U)
                                              	tmp = 0.0
                                              	if (l <= -2.8e-5)
                                              		tmp = t_0;
                                              	elseif (l <= 4.1e+15)
                                              		tmp = fma(Float64(J * l), 2.0, U);
                                              	else
                                              		tmp = t_0;
                                              	end
                                              	return tmp
                                              end
                                              
                                              code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[(N[(N[(K * K), $MachinePrecision] * -0.25 + 2.0), $MachinePrecision] * l), $MachinePrecision] * J + U), $MachinePrecision]}, If[LessEqual[l, -2.8e-5], t$95$0, If[LessEqual[l, 4.1e+15], N[(N[(J * l), $MachinePrecision] * 2.0 + U), $MachinePrecision], t$95$0]]]
                                              
                                              \begin{array}{l}
                                              
                                              \\
                                              \begin{array}{l}
                                              t_0 := \mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\
                                              \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\
                                              \;\;\;\;t\_0\\
                                              
                                              \mathbf{elif}\;\ell \leq 4.1 \cdot 10^{+15}:\\
                                              \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\
                                              
                                              \mathbf{else}:\\
                                              \;\;\;\;t\_0\\
                                              
                                              
                                              \end{array}
                                              \end{array}
                                              
                                              Derivation
                                              1. Split input into 2 regimes
                                              2. if l < -2.79999999999999996e-5 or 4.1e15 < l

                                                1. Initial program 99.8%

                                                  \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                2. Add Preprocessing
                                                3. Step-by-step derivation
                                                  1. lift-+.f64N/A

                                                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U} \]
                                                  2. lift-*.f64N/A

                                                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right) \cdot \cos \left(\frac{K}{2}\right)} + U \]
                                                  3. lift-*.f64N/A

                                                    \[\leadsto \color{blue}{\left(J \cdot \left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right)\right)} \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                  4. associate-*l*N/A

                                                    \[\leadsto \color{blue}{J \cdot \left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right)} + U \]
                                                  5. *-commutativeN/A

                                                    \[\leadsto \color{blue}{\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot J} + U \]
                                                  6. lower-fma.f64N/A

                                                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(e^{\ell} - e^{\mathsf{neg}\left(\ell\right)}\right) \cdot \cos \left(\frac{K}{2}\right), J, U\right)} \]
                                                4. Applied rewrites100.0%

                                                  \[\leadsto \color{blue}{\mathsf{fma}\left(\cos \left(K \cdot -0.5\right) \cdot \left(\sinh \ell \cdot 2\right), J, U\right)} \]
                                                5. Taylor expanded in l around 0

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{2 \cdot \left(\ell \cdot \cos \left(\frac{-1}{2} \cdot K\right)\right)}, J, U\right) \]
                                                6. Step-by-step derivation
                                                  1. associate-*r*N/A

                                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                                  2. lower-*.f64N/A

                                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                                  3. lower-*.f64N/A

                                                    \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot \cos \left(\frac{-1}{2} \cdot K\right), J, U\right) \]
                                                  4. lower-cos.f64N/A

                                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \color{blue}{\cos \left(\frac{-1}{2} \cdot K\right)}, J, U\right) \]
                                                  5. *-commutativeN/A

                                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot \frac{-1}{2}\right)}, J, U\right) \]
                                                  6. lower-*.f6425.3

                                                    \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot \cos \color{blue}{\left(K \cdot -0.5\right)}, J, U\right) \]
                                                7. Applied rewrites25.3%

                                                  \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot \cos \left(K \cdot -0.5\right)}, J, U\right) \]
                                                8. Taylor expanded in K around 0

                                                  \[\leadsto \mathsf{fma}\left(\frac{-1}{4} \cdot \left({K}^{2} \cdot \ell\right) + \color{blue}{2 \cdot \ell}, J, U\right) \]
                                                9. Step-by-step derivation
                                                  1. Applied rewrites35.6%

                                                    \[\leadsto \mathsf{fma}\left(\ell \cdot \color{blue}{\mathsf{fma}\left(K \cdot K, -0.25, 2\right)}, J, U\right) \]

                                                  if -2.79999999999999996e-5 < l < 4.1e15

                                                  1. Initial program 70.6%

                                                    \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                  2. Add Preprocessing
                                                  3. Taylor expanded in l around 0

                                                    \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                  4. Step-by-step derivation
                                                    1. +-commutativeN/A

                                                      \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                    2. associate-*r*N/A

                                                      \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                    3. associate-*r*N/A

                                                      \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                    4. associate-*r*N/A

                                                      \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                    5. *-commutativeN/A

                                                      \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                    6. lower-fma.f64N/A

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

                                                      \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                    8. *-commutativeN/A

                                                      \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                    9. lower-*.f64N/A

                                                      \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                    10. lower-*.f64N/A

                                                      \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                    11. lower-cos.f64N/A

                                                      \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                    12. *-commutativeN/A

                                                      \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                    13. lower-*.f6498.4

                                                      \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                                  5. Applied rewrites98.4%

                                                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                                  6. Taylor expanded in K around 0

                                                    \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                                  7. Step-by-step derivation
                                                    1. Applied rewrites87.8%

                                                      \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                                  8. Recombined 2 regimes into one program.
                                                  9. Final simplification63.6%

                                                    \[\leadsto \begin{array}{l} \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \mathbf{elif}\;\ell \leq 4.1 \cdot 10^{+15}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(K \cdot K, -0.25, 2\right) \cdot \ell, J, U\right)\\ \end{array} \]
                                                  10. Add Preprocessing

                                                  Alternative 16: 60.7% accurate, 9.7× speedup?

                                                  \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(J \cdot \ell\right) \cdot \mathsf{fma}\left(-0.25, K \cdot K, 2\right)\\ \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;\ell \leq 3.6 \cdot 10^{+29}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
                                                  (FPCore (J l K U)
                                                   :precision binary64
                                                   (let* ((t_0 (* (* J l) (fma -0.25 (* K K) 2.0))))
                                                     (if (<= l -2.8e-5) t_0 (if (<= l 3.6e+29) (fma (* J l) 2.0 U) t_0))))
                                                  double code(double J, double l, double K, double U) {
                                                  	double t_0 = (J * l) * fma(-0.25, (K * K), 2.0);
                                                  	double tmp;
                                                  	if (l <= -2.8e-5) {
                                                  		tmp = t_0;
                                                  	} else if (l <= 3.6e+29) {
                                                  		tmp = fma((J * l), 2.0, U);
                                                  	} else {
                                                  		tmp = t_0;
                                                  	}
                                                  	return tmp;
                                                  }
                                                  
                                                  function code(J, l, K, U)
                                                  	t_0 = Float64(Float64(J * l) * fma(-0.25, Float64(K * K), 2.0))
                                                  	tmp = 0.0
                                                  	if (l <= -2.8e-5)
                                                  		tmp = t_0;
                                                  	elseif (l <= 3.6e+29)
                                                  		tmp = fma(Float64(J * l), 2.0, U);
                                                  	else
                                                  		tmp = t_0;
                                                  	end
                                                  	return tmp
                                                  end
                                                  
                                                  code[J_, l_, K_, U_] := Block[{t$95$0 = N[(N[(J * l), $MachinePrecision] * N[(-0.25 * N[(K * K), $MachinePrecision] + 2.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[l, -2.8e-5], t$95$0, If[LessEqual[l, 3.6e+29], N[(N[(J * l), $MachinePrecision] * 2.0 + U), $MachinePrecision], t$95$0]]]
                                                  
                                                  \begin{array}{l}
                                                  
                                                  \\
                                                  \begin{array}{l}
                                                  t_0 := \left(J \cdot \ell\right) \cdot \mathsf{fma}\left(-0.25, K \cdot K, 2\right)\\
                                                  \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\
                                                  \;\;\;\;t\_0\\
                                                  
                                                  \mathbf{elif}\;\ell \leq 3.6 \cdot 10^{+29}:\\
                                                  \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\
                                                  
                                                  \mathbf{else}:\\
                                                  \;\;\;\;t\_0\\
                                                  
                                                  
                                                  \end{array}
                                                  \end{array}
                                                  
                                                  Derivation
                                                  1. Split input into 2 regimes
                                                  2. if l < -2.79999999999999996e-5 or 3.59999999999999976e29 < l

                                                    1. Initial program 99.8%

                                                      \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                    2. Add Preprocessing
                                                    3. Taylor expanded in l around 0

                                                      \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                    4. Step-by-step derivation
                                                      1. +-commutativeN/A

                                                        \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                      2. associate-*r*N/A

                                                        \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                      3. associate-*r*N/A

                                                        \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                      4. associate-*r*N/A

                                                        \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                      5. *-commutativeN/A

                                                        \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                      6. lower-fma.f64N/A

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

                                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                      8. *-commutativeN/A

                                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                      9. lower-*.f64N/A

                                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                      10. lower-*.f64N/A

                                                        \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                      11. lower-cos.f64N/A

                                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                      12. *-commutativeN/A

                                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                      13. lower-*.f6425.8

                                                        \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                                    5. Applied rewrites25.8%

                                                      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                                    6. Taylor expanded in U around 0

                                                      \[\leadsto 2 \cdot \color{blue}{\left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                    7. Step-by-step derivation
                                                      1. Applied rewrites25.7%

                                                        \[\leadsto \left(\left(\ell \cdot J\right) \cdot 2\right) \cdot \color{blue}{\cos \left(0.5 \cdot K\right)} \]
                                                      2. Taylor expanded in K around 0

                                                        \[\leadsto \frac{-1}{4} \cdot \left(J \cdot \left({K}^{2} \cdot \ell\right)\right) + 2 \cdot \color{blue}{\left(J \cdot \ell\right)} \]
                                                      3. Step-by-step derivation
                                                        1. Applied rewrites32.9%

                                                          \[\leadsto \left(\ell \cdot J\right) \cdot \mathsf{fma}\left(-0.25, \color{blue}{K \cdot K}, 2\right) \]

                                                        if -2.79999999999999996e-5 < l < 3.59999999999999976e29

                                                        1. Initial program 71.3%

                                                          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                        2. Add Preprocessing
                                                        3. Taylor expanded in l around 0

                                                          \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                        4. Step-by-step derivation
                                                          1. +-commutativeN/A

                                                            \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                          2. associate-*r*N/A

                                                            \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                          3. associate-*r*N/A

                                                            \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                          4. associate-*r*N/A

                                                            \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                          5. *-commutativeN/A

                                                            \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                          6. lower-fma.f64N/A

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

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          8. *-commutativeN/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          9. lower-*.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          10. lower-*.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          11. lower-cos.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                          12. *-commutativeN/A

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                          13. lower-*.f6496.4

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                                        5. Applied rewrites96.4%

                                                          \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                                        6. Taylor expanded in K around 0

                                                          \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                                        7. Step-by-step derivation
                                                          1. Applied rewrites86.1%

                                                            \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                                        8. Recombined 2 regimes into one program.
                                                        9. Final simplification62.0%

                                                          \[\leadsto \begin{array}{l} \mathbf{if}\;\ell \leq -2.8 \cdot 10^{-5}:\\ \;\;\;\;\left(J \cdot \ell\right) \cdot \mathsf{fma}\left(-0.25, K \cdot K, 2\right)\\ \mathbf{elif}\;\ell \leq 3.6 \cdot 10^{+29}:\\ \;\;\;\;\mathsf{fma}\left(J \cdot \ell, 2, U\right)\\ \mathbf{else}:\\ \;\;\;\;\left(J \cdot \ell\right) \cdot \mathsf{fma}\left(-0.25, K \cdot K, 2\right)\\ \end{array} \]
                                                        10. Add Preprocessing

                                                        Alternative 17: 55.2% accurate, 27.5× speedup?

                                                        \[\begin{array}{l} \\ \mathsf{fma}\left(J \cdot \ell, 2, U\right) \end{array} \]
                                                        (FPCore (J l K U) :precision binary64 (fma (* J l) 2.0 U))
                                                        double code(double J, double l, double K, double U) {
                                                        	return fma((J * l), 2.0, U);
                                                        }
                                                        
                                                        function code(J, l, K, U)
                                                        	return fma(Float64(J * l), 2.0, U)
                                                        end
                                                        
                                                        code[J_, l_, K_, U_] := N[(N[(J * l), $MachinePrecision] * 2.0 + U), $MachinePrecision]
                                                        
                                                        \begin{array}{l}
                                                        
                                                        \\
                                                        \mathsf{fma}\left(J \cdot \ell, 2, U\right)
                                                        \end{array}
                                                        
                                                        Derivation
                                                        1. Initial program 84.2%

                                                          \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                        2. Add Preprocessing
                                                        3. Taylor expanded in l around 0

                                                          \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                        4. Step-by-step derivation
                                                          1. +-commutativeN/A

                                                            \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                          2. associate-*r*N/A

                                                            \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                          3. associate-*r*N/A

                                                            \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                          4. associate-*r*N/A

                                                            \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                          5. *-commutativeN/A

                                                            \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                          6. lower-fma.f64N/A

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

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          8. *-commutativeN/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          9. lower-*.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          10. lower-*.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                          11. lower-cos.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                          12. *-commutativeN/A

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                          13. lower-*.f6464.4

                                                            \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                                        5. Applied rewrites64.4%

                                                          \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                                        6. Taylor expanded in K around 0

                                                          \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                                        7. Step-by-step derivation
                                                          1. Applied rewrites55.0%

                                                            \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                                          2. Final simplification55.0%

                                                            \[\leadsto \mathsf{fma}\left(J \cdot \ell, 2, U\right) \]
                                                          3. Add Preprocessing

                                                          Alternative 18: 19.9% accurate, 30.0× speedup?

                                                          \[\begin{array}{l} \\ \left(2 \cdot \ell\right) \cdot J \end{array} \]
                                                          (FPCore (J l K U) :precision binary64 (* (* 2.0 l) J))
                                                          double code(double J, double l, double K, double U) {
                                                          	return (2.0 * l) * J;
                                                          }
                                                          
                                                          real(8) function code(j, l, k, u)
                                                              real(8), intent (in) :: j
                                                              real(8), intent (in) :: l
                                                              real(8), intent (in) :: k
                                                              real(8), intent (in) :: u
                                                              code = (2.0d0 * l) * j
                                                          end function
                                                          
                                                          public static double code(double J, double l, double K, double U) {
                                                          	return (2.0 * l) * J;
                                                          }
                                                          
                                                          def code(J, l, K, U):
                                                          	return (2.0 * l) * J
                                                          
                                                          function code(J, l, K, U)
                                                          	return Float64(Float64(2.0 * l) * J)
                                                          end
                                                          
                                                          function tmp = code(J, l, K, U)
                                                          	tmp = (2.0 * l) * J;
                                                          end
                                                          
                                                          code[J_, l_, K_, U_] := N[(N[(2.0 * l), $MachinePrecision] * J), $MachinePrecision]
                                                          
                                                          \begin{array}{l}
                                                          
                                                          \\
                                                          \left(2 \cdot \ell\right) \cdot J
                                                          \end{array}
                                                          
                                                          Derivation
                                                          1. Initial program 84.2%

                                                            \[\left(J \cdot \left(e^{\ell} - e^{-\ell}\right)\right) \cdot \cos \left(\frac{K}{2}\right) + U \]
                                                          2. Add Preprocessing
                                                          3. Taylor expanded in l around 0

                                                            \[\leadsto \color{blue}{U + 2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \]
                                                          4. Step-by-step derivation
                                                            1. +-commutativeN/A

                                                              \[\leadsto \color{blue}{2 \cdot \left(J \cdot \left(\ell \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) + U} \]
                                                            2. associate-*r*N/A

                                                              \[\leadsto 2 \cdot \color{blue}{\left(\left(J \cdot \ell\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)} + U \]
                                                            3. associate-*r*N/A

                                                              \[\leadsto \color{blue}{\left(2 \cdot \left(J \cdot \ell\right)\right) \cdot \cos \left(\frac{1}{2} \cdot K\right)} + U \]
                                                            4. associate-*r*N/A

                                                              \[\leadsto \color{blue}{\left(\left(2 \cdot J\right) \cdot \ell\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                            5. *-commutativeN/A

                                                              \[\leadsto \color{blue}{\left(\ell \cdot \left(2 \cdot J\right)\right)} \cdot \cos \left(\frac{1}{2} \cdot K\right) + U \]
                                                            6. lower-fma.f64N/A

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

                                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\ell \cdot 2\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                            8. *-commutativeN/A

                                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                            9. lower-*.f64N/A

                                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right) \cdot J}, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                            10. lower-*.f64N/A

                                                              \[\leadsto \mathsf{fma}\left(\color{blue}{\left(2 \cdot \ell\right)} \cdot J, \cos \left(\frac{1}{2} \cdot K\right), U\right) \]
                                                            11. lower-cos.f64N/A

                                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \color{blue}{\cos \left(\frac{1}{2} \cdot K\right)}, U\right) \]
                                                            12. *-commutativeN/A

                                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}, U\right) \]
                                                            13. lower-*.f6464.4

                                                              \[\leadsto \mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \color{blue}{\left(K \cdot 0.5\right)}, U\right) \]
                                                          5. Applied rewrites64.4%

                                                            \[\leadsto \color{blue}{\mathsf{fma}\left(\left(2 \cdot \ell\right) \cdot J, \cos \left(K \cdot 0.5\right), U\right)} \]
                                                          6. Taylor expanded in K around 0

                                                            \[\leadsto U + \color{blue}{2 \cdot \left(J \cdot \ell\right)} \]
                                                          7. Step-by-step derivation
                                                            1. Applied rewrites55.0%

                                                              \[\leadsto \mathsf{fma}\left(\ell \cdot J, \color{blue}{2}, U\right) \]
                                                            2. Taylor expanded in U around 0

                                                              \[\leadsto 2 \cdot \left(J \cdot \color{blue}{\ell}\right) \]
                                                            3. Step-by-step derivation
                                                              1. Applied rewrites21.0%

                                                                \[\leadsto \left(\ell \cdot J\right) \cdot 2 \]
                                                              2. Step-by-step derivation
                                                                1. Applied rewrites21.0%

                                                                  \[\leadsto \color{blue}{\left(2 \cdot \ell\right) \cdot J} \]
                                                                2. Add Preprocessing

                                                                Reproduce

                                                                ?
                                                                herbie shell --seed 2024240 
                                                                (FPCore (J l K U)
                                                                  :name "Maksimov and Kolovsky, Equation (4)"
                                                                  :precision binary64
                                                                  (+ (* (* J (- (exp l) (exp (- l)))) (cos (/ K 2.0))) U))