Maksimov and Kolovsky, Equation (3)

Percentage Accurate: 73.1% → 99.7%
Time: 12.6s
Alternatives: 10
Speedup: 0.4×

Specification

?
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot t\_0}\right)}^{2}} \end{array} \end{array} \]
(FPCore (J K U)
 :precision binary64
 (let* ((t_0 (cos (/ K 2.0))))
   (* (* (* -2.0 J) t_0) (sqrt (+ 1.0 (pow (/ U (* (* 2.0 J) t_0)) 2.0))))))
double code(double J, double K, double U) {
	double t_0 = cos((K / 2.0));
	return ((-2.0 * J) * t_0) * sqrt((1.0 + pow((U / ((2.0 * J) * t_0)), 2.0)));
}
real(8) function code(j, k, u)
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    real(8) :: t_0
    t_0 = cos((k / 2.0d0))
    code = (((-2.0d0) * j) * t_0) * sqrt((1.0d0 + ((u / ((2.0d0 * j) * t_0)) ** 2.0d0)))
end function
public static double code(double J, double K, double U) {
	double t_0 = Math.cos((K / 2.0));
	return ((-2.0 * J) * t_0) * Math.sqrt((1.0 + Math.pow((U / ((2.0 * J) * t_0)), 2.0)));
}
def code(J, K, U):
	t_0 = math.cos((K / 2.0))
	return ((-2.0 * J) * t_0) * math.sqrt((1.0 + math.pow((U / ((2.0 * J) * t_0)), 2.0)))
function code(J, K, U)
	t_0 = cos(Float64(K / 2.0))
	return Float64(Float64(Float64(-2.0 * J) * t_0) * sqrt(Float64(1.0 + (Float64(U / Float64(Float64(2.0 * J) * t_0)) ^ 2.0))))
end
function tmp = code(J, K, U)
	t_0 = cos((K / 2.0));
	tmp = ((-2.0 * J) * t_0) * sqrt((1.0 + ((U / ((2.0 * J) * t_0)) ^ 2.0)));
end
code[J_, K_, U_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[(-2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sqrt[N[(1.0 + N[Power[N[(U / N[(N[(2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \cos \left(\frac{K}{2}\right)\\
\left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot t\_0}\right)}^{2}}
\end{array}
\end{array}

Sampling outcomes in binary64 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 10 alternatives:

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

Initial Program: 73.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot t\_0}\right)}^{2}} \end{array} \end{array} \]
(FPCore (J K U)
 :precision binary64
 (let* ((t_0 (cos (/ K 2.0))))
   (* (* (* -2.0 J) t_0) (sqrt (+ 1.0 (pow (/ U (* (* 2.0 J) t_0)) 2.0))))))
double code(double J, double K, double U) {
	double t_0 = cos((K / 2.0));
	return ((-2.0 * J) * t_0) * sqrt((1.0 + pow((U / ((2.0 * J) * t_0)), 2.0)));
}
real(8) function code(j, k, u)
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: u
    real(8) :: t_0
    t_0 = cos((k / 2.0d0))
    code = (((-2.0d0) * j) * t_0) * sqrt((1.0d0 + ((u / ((2.0d0 * j) * t_0)) ** 2.0d0)))
end function
public static double code(double J, double K, double U) {
	double t_0 = Math.cos((K / 2.0));
	return ((-2.0 * J) * t_0) * Math.sqrt((1.0 + Math.pow((U / ((2.0 * J) * t_0)), 2.0)));
}
def code(J, K, U):
	t_0 = math.cos((K / 2.0))
	return ((-2.0 * J) * t_0) * math.sqrt((1.0 + math.pow((U / ((2.0 * J) * t_0)), 2.0)))
function code(J, K, U)
	t_0 = cos(Float64(K / 2.0))
	return Float64(Float64(Float64(-2.0 * J) * t_0) * sqrt(Float64(1.0 + (Float64(U / Float64(Float64(2.0 * J) * t_0)) ^ 2.0))))
end
function tmp = code(J, K, U)
	t_0 = cos((K / 2.0));
	tmp = ((-2.0 * J) * t_0) * sqrt((1.0 + ((U / ((2.0 * J) * t_0)) ^ 2.0)));
end
code[J_, K_, U_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[(-2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sqrt[N[(1.0 + N[Power[N[(U / N[(N[(2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \cos \left(\frac{K}{2}\right)\\
\left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot t\_0}\right)}^{2}}
\end{array}
\end{array}

Alternative 1: 99.7% accurate, 0.3× speedup?

\[\begin{array}{l} U_m = \left|U\right| \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ t_1 := \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{{\left(\frac{U\_m}{t\_0 \cdot \left(J \cdot 2\right)}\right)}^{2} + 1}\\ t_2 := \cos \left(K \cdot 0.5\right)\\ \mathbf{if}\;t\_1 \leq -\infty:\\ \;\;\;\;-U\_m\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+307}:\\ \;\;\;\;\left(-2 \cdot \left(J \cdot t\_2\right)\right) \cdot \sqrt{{\left(\frac{U\_m}{\left(J \cdot 2\right) \cdot t\_2}\right)}^{2} + 1}\\ \mathbf{else}:\\ \;\;\;\;U\_m\\ \end{array} \end{array} \]
U_m = (fabs.f64 U)
(FPCore (J K U_m)
 :precision binary64
 (let* ((t_0 (cos (/ K 2.0)))
        (t_1
         (*
          (* (* -2.0 J) t_0)
          (sqrt (+ (pow (/ U_m (* t_0 (* J 2.0))) 2.0) 1.0))))
        (t_2 (cos (* K 0.5))))
   (if (<= t_1 (- INFINITY))
     (- U_m)
     (if (<= t_1 2e+307)
       (*
        (* -2.0 (* J t_2))
        (sqrt (+ (pow (/ U_m (* (* J 2.0) t_2)) 2.0) 1.0)))
       U_m))))
U_m = fabs(U);
double code(double J, double K, double U_m) {
	double t_0 = cos((K / 2.0));
	double t_1 = ((-2.0 * J) * t_0) * sqrt((pow((U_m / (t_0 * (J * 2.0))), 2.0) + 1.0));
	double t_2 = cos((K * 0.5));
	double tmp;
	if (t_1 <= -((double) INFINITY)) {
		tmp = -U_m;
	} else if (t_1 <= 2e+307) {
		tmp = (-2.0 * (J * t_2)) * sqrt((pow((U_m / ((J * 2.0) * t_2)), 2.0) + 1.0));
	} else {
		tmp = U_m;
	}
	return tmp;
}
U_m = Math.abs(U);
public static double code(double J, double K, double U_m) {
	double t_0 = Math.cos((K / 2.0));
	double t_1 = ((-2.0 * J) * t_0) * Math.sqrt((Math.pow((U_m / (t_0 * (J * 2.0))), 2.0) + 1.0));
	double t_2 = Math.cos((K * 0.5));
	double tmp;
	if (t_1 <= -Double.POSITIVE_INFINITY) {
		tmp = -U_m;
	} else if (t_1 <= 2e+307) {
		tmp = (-2.0 * (J * t_2)) * Math.sqrt((Math.pow((U_m / ((J * 2.0) * t_2)), 2.0) + 1.0));
	} else {
		tmp = U_m;
	}
	return tmp;
}
U_m = math.fabs(U)
def code(J, K, U_m):
	t_0 = math.cos((K / 2.0))
	t_1 = ((-2.0 * J) * t_0) * math.sqrt((math.pow((U_m / (t_0 * (J * 2.0))), 2.0) + 1.0))
	t_2 = math.cos((K * 0.5))
	tmp = 0
	if t_1 <= -math.inf:
		tmp = -U_m
	elif t_1 <= 2e+307:
		tmp = (-2.0 * (J * t_2)) * math.sqrt((math.pow((U_m / ((J * 2.0) * t_2)), 2.0) + 1.0))
	else:
		tmp = U_m
	return tmp
U_m = abs(U)
function code(J, K, U_m)
	t_0 = cos(Float64(K / 2.0))
	t_1 = Float64(Float64(Float64(-2.0 * J) * t_0) * sqrt(Float64((Float64(U_m / Float64(t_0 * Float64(J * 2.0))) ^ 2.0) + 1.0)))
	t_2 = cos(Float64(K * 0.5))
	tmp = 0.0
	if (t_1 <= Float64(-Inf))
		tmp = Float64(-U_m);
	elseif (t_1 <= 2e+307)
		tmp = Float64(Float64(-2.0 * Float64(J * t_2)) * sqrt(Float64((Float64(U_m / Float64(Float64(J * 2.0) * t_2)) ^ 2.0) + 1.0)));
	else
		tmp = U_m;
	end
	return tmp
end
U_m = abs(U);
function tmp_2 = code(J, K, U_m)
	t_0 = cos((K / 2.0));
	t_1 = ((-2.0 * J) * t_0) * sqrt((((U_m / (t_0 * (J * 2.0))) ^ 2.0) + 1.0));
	t_2 = cos((K * 0.5));
	tmp = 0.0;
	if (t_1 <= -Inf)
		tmp = -U_m;
	elseif (t_1 <= 2e+307)
		tmp = (-2.0 * (J * t_2)) * sqrt((((U_m / ((J * 2.0) * t_2)) ^ 2.0) + 1.0));
	else
		tmp = U_m;
	end
	tmp_2 = tmp;
end
U_m = N[Abs[U], $MachinePrecision]
code[J_, K_, U$95$m_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(-2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sqrt[N[(N[Power[N[(U$95$m / N[(t$95$0 * N[(J * 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(K * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$1, (-Infinity)], (-U$95$m), If[LessEqual[t$95$1, 2e+307], N[(N[(-2.0 * N[(J * t$95$2), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(N[Power[N[(U$95$m / N[(N[(J * 2.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], U$95$m]]]]]
\begin{array}{l}
U_m = \left|U\right|

\\
\begin{array}{l}
t_0 := \cos \left(\frac{K}{2}\right)\\
t_1 := \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{{\left(\frac{U\_m}{t\_0 \cdot \left(J \cdot 2\right)}\right)}^{2} + 1}\\
t_2 := \cos \left(K \cdot 0.5\right)\\
\mathbf{if}\;t\_1 \leq -\infty:\\
\;\;\;\;-U\_m\\

\mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+307}:\\
\;\;\;\;\left(-2 \cdot \left(J \cdot t\_2\right)\right) \cdot \sqrt{{\left(\frac{U\_m}{\left(J \cdot 2\right) \cdot t\_2}\right)}^{2} + 1}\\

\mathbf{else}:\\
\;\;\;\;U\_m\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < -inf.0

    1. Initial program 5.4%

      \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
    2. Add Preprocessing
    3. Taylor expanded in J around 0

      \[\leadsto \color{blue}{-1 \cdot U} \]
    4. Step-by-step derivation
      1. mul-1-negN/A

        \[\leadsto \color{blue}{\mathsf{neg}\left(U\right)} \]
      2. lower-neg.f64100.0

        \[\leadsto \color{blue}{-U} \]
    5. Simplified100.0%

      \[\leadsto \color{blue}{-U} \]

    if -inf.0 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < 1.99999999999999997e307

    1. Initial program 99.8%

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

        \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \color{blue}{\left(\frac{K}{2}\right)}\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. lift-cos.f64N/A

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

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

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

        \[\leadsto \color{blue}{\left(\left(J \cdot \cos \left(\frac{K}{2}\right)\right) \cdot -2\right)} \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      6. lower-*.f6499.8

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

        \[\leadsto \left(\left(J \cdot \cos \color{blue}{\left(\frac{K}{2}\right)}\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      8. div-invN/A

        \[\leadsto \left(\left(J \cdot \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      9. metadata-evalN/A

        \[\leadsto \left(\left(J \cdot \cos \left(K \cdot \color{blue}{\frac{1}{2}}\right)\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      10. lower-*.f6499.8

        \[\leadsto \left(\left(J \cdot \cos \color{blue}{\left(K \cdot 0.5\right)}\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
    4. Applied egg-rr99.8%

      \[\leadsto \color{blue}{\left(\left(J \cdot \cos \left(K \cdot 0.5\right)\right) \cdot -2\right)} \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
    5. Step-by-step derivation
      1. div-invN/A

        \[\leadsto \left(\left(J \cdot \cos \left(K \cdot \frac{1}{2}\right)\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}}\right)}^{2}} \]
      2. metadata-evalN/A

        \[\leadsto \left(\left(J \cdot \cos \left(K \cdot \frac{1}{2}\right)\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(K \cdot \color{blue}{\frac{1}{2}}\right)}\right)}^{2}} \]
      3. lift-*.f6499.8

        \[\leadsto \left(\left(J \cdot \cos \left(K \cdot 0.5\right)\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \color{blue}{\left(K \cdot 0.5\right)}}\right)}^{2}} \]
    6. Applied egg-rr99.8%

      \[\leadsto \left(\left(J \cdot \cos \left(K \cdot 0.5\right)\right) \cdot -2\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \color{blue}{\left(K \cdot 0.5\right)}}\right)}^{2}} \]

    if 1.99999999999999997e307 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64)))))

    1. Initial program 5.7%

      \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
    2. Add Preprocessing
    3. Taylor expanded in U around -inf

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

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

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

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

        \[\leadsto \color{blue}{\left(\mathsf{neg}\left(U\right)\right)} \cdot \left(-2 \cdot \frac{{J}^{2} \cdot {\cos \left(\frac{1}{2} \cdot K\right)}^{2}}{{U}^{2}} - 1\right) \]
      5. sub-negN/A

        \[\leadsto \left(\mathsf{neg}\left(U\right)\right) \cdot \color{blue}{\left(-2 \cdot \frac{{J}^{2} \cdot {\cos \left(\frac{1}{2} \cdot K\right)}^{2}}{{U}^{2}} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
      6. metadata-evalN/A

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \left(\mathsf{neg}\left(U\right)\right) \cdot \mathsf{fma}\left(-2, {\cos \left(\frac{1}{2} \cdot K\right)}^{2} \cdot \frac{J \cdot J}{\color{blue}{U \cdot U}}, -1\right) \]
      18. lower-*.f64100.0

        \[\leadsto \left(-U\right) \cdot \mathsf{fma}\left(-2, {\cos \left(0.5 \cdot K\right)}^{2} \cdot \frac{J \cdot J}{\color{blue}{U \cdot U}}, -1\right) \]
    5. Simplified100.0%

      \[\leadsto \color{blue}{\left(-U\right) \cdot \mathsf{fma}\left(-2, {\cos \left(0.5 \cdot K\right)}^{2} \cdot \frac{J \cdot J}{U \cdot U}, -1\right)} \]
    6. Taylor expanded in J around 0

      \[\leadsto \left(\mathsf{neg}\left(U\right)\right) \cdot \color{blue}{-1} \]
    7. Step-by-step derivation
      1. Simplified100.0%

        \[\leadsto \left(-U\right) \cdot \color{blue}{-1} \]
      2. Step-by-step derivation
        1. lift-neg.f64N/A

          \[\leadsto \color{blue}{\left(\mathsf{neg}\left(U\right)\right)} \cdot -1 \]
        2. *-commutativeN/A

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

          \[\leadsto \color{blue}{\mathsf{neg}\left(\left(\mathsf{neg}\left(U\right)\right)\right)} \]
        4. lower-neg.f64100.0

          \[\leadsto \color{blue}{-\left(-U\right)} \]
      3. Applied egg-rr100.0%

        \[\leadsto \color{blue}{-\left(-U\right)} \]
    8. Recombined 3 regimes into one program.
    9. Final simplification99.8%

      \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq -\infty:\\ \;\;\;\;-U\\ \mathbf{elif}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq 2 \cdot 10^{+307}:\\ \;\;\;\;\left(-2 \cdot \left(J \cdot \cos \left(K \cdot 0.5\right)\right)\right) \cdot \sqrt{{\left(\frac{U}{\left(J \cdot 2\right) \cdot \cos \left(K \cdot 0.5\right)}\right)}^{2} + 1}\\ \mathbf{else}:\\ \;\;\;\;U\\ \end{array} \]
    10. Add Preprocessing

    Alternative 2: 83.6% accurate, 0.2× speedup?

    \[\begin{array}{l} U_m = \left|U\right| \\ \begin{array}{l} t_0 := \cos \left(\frac{K}{2}\right)\\ t_1 := \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{{\left(\frac{U\_m}{t\_0 \cdot \left(J \cdot 2\right)}\right)}^{2} + 1}\\ t_2 := \cos \left(K \cdot 0.5\right)\\ \mathbf{if}\;t\_1 \leq -\infty:\\ \;\;\;\;-U\_m\\ \mathbf{elif}\;t\_1 \leq -5 \cdot 10^{+158}:\\ \;\;\;\;-2 \cdot \left(\left(J \cdot t\_2\right) \cdot \sqrt{\mathsf{fma}\left(U\_m \cdot 0.25, \frac{U\_m}{J \cdot J}, 1\right)}\right)\\ \mathbf{elif}\;t\_1 \leq -2 \cdot 10^{-119}:\\ \;\;\;\;J \cdot \left(\left(-2 \cdot t\_2\right) \cdot \sqrt{\mathsf{fma}\left(U\_m \cdot U\_m, \frac{0.25}{\left(J \cdot J\right) \cdot \mathsf{fma}\left(0.5, \cos K, 0.5\right)}, 1\right)}\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+307}:\\ \;\;\;\;\left(-2 \cdot J\right) \cdot t\_2\\ \mathbf{else}:\\ \;\;\;\;U\_m\\ \end{array} \end{array} \]
    U_m = (fabs.f64 U)
    (FPCore (J K U_m)
     :precision binary64
     (let* ((t_0 (cos (/ K 2.0)))
            (t_1
             (*
              (* (* -2.0 J) t_0)
              (sqrt (+ (pow (/ U_m (* t_0 (* J 2.0))) 2.0) 1.0))))
            (t_2 (cos (* K 0.5))))
       (if (<= t_1 (- INFINITY))
         (- U_m)
         (if (<= t_1 -5e+158)
           (* -2.0 (* (* J t_2) (sqrt (fma (* U_m 0.25) (/ U_m (* J J)) 1.0))))
           (if (<= t_1 -2e-119)
             (*
              J
              (*
               (* -2.0 t_2)
               (sqrt
                (fma (* U_m U_m) (/ 0.25 (* (* J J) (fma 0.5 (cos K) 0.5))) 1.0))))
             (if (<= t_1 2e+307) (* (* -2.0 J) t_2) U_m))))))
    U_m = fabs(U);
    double code(double J, double K, double U_m) {
    	double t_0 = cos((K / 2.0));
    	double t_1 = ((-2.0 * J) * t_0) * sqrt((pow((U_m / (t_0 * (J * 2.0))), 2.0) + 1.0));
    	double t_2 = cos((K * 0.5));
    	double tmp;
    	if (t_1 <= -((double) INFINITY)) {
    		tmp = -U_m;
    	} else if (t_1 <= -5e+158) {
    		tmp = -2.0 * ((J * t_2) * sqrt(fma((U_m * 0.25), (U_m / (J * J)), 1.0)));
    	} else if (t_1 <= -2e-119) {
    		tmp = J * ((-2.0 * t_2) * sqrt(fma((U_m * U_m), (0.25 / ((J * J) * fma(0.5, cos(K), 0.5))), 1.0)));
    	} else if (t_1 <= 2e+307) {
    		tmp = (-2.0 * J) * t_2;
    	} else {
    		tmp = U_m;
    	}
    	return tmp;
    }
    
    U_m = abs(U)
    function code(J, K, U_m)
    	t_0 = cos(Float64(K / 2.0))
    	t_1 = Float64(Float64(Float64(-2.0 * J) * t_0) * sqrt(Float64((Float64(U_m / Float64(t_0 * Float64(J * 2.0))) ^ 2.0) + 1.0)))
    	t_2 = cos(Float64(K * 0.5))
    	tmp = 0.0
    	if (t_1 <= Float64(-Inf))
    		tmp = Float64(-U_m);
    	elseif (t_1 <= -5e+158)
    		tmp = Float64(-2.0 * Float64(Float64(J * t_2) * sqrt(fma(Float64(U_m * 0.25), Float64(U_m / Float64(J * J)), 1.0))));
    	elseif (t_1 <= -2e-119)
    		tmp = Float64(J * Float64(Float64(-2.0 * t_2) * sqrt(fma(Float64(U_m * U_m), Float64(0.25 / Float64(Float64(J * J) * fma(0.5, cos(K), 0.5))), 1.0))));
    	elseif (t_1 <= 2e+307)
    		tmp = Float64(Float64(-2.0 * J) * t_2);
    	else
    		tmp = U_m;
    	end
    	return tmp
    end
    
    U_m = N[Abs[U], $MachinePrecision]
    code[J_, K_, U$95$m_] := Block[{t$95$0 = N[Cos[N[(K / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(-2.0 * J), $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sqrt[N[(N[Power[N[(U$95$m / N[(t$95$0 * N[(J * 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(K * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$1, (-Infinity)], (-U$95$m), If[LessEqual[t$95$1, -5e+158], N[(-2.0 * N[(N[(J * t$95$2), $MachinePrecision] * N[Sqrt[N[(N[(U$95$m * 0.25), $MachinePrecision] * N[(U$95$m / N[(J * J), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e-119], N[(J * N[(N[(-2.0 * t$95$2), $MachinePrecision] * N[Sqrt[N[(N[(U$95$m * U$95$m), $MachinePrecision] * N[(0.25 / N[(N[(J * J), $MachinePrecision] * N[(0.5 * N[Cos[K], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+307], N[(N[(-2.0 * J), $MachinePrecision] * t$95$2), $MachinePrecision], U$95$m]]]]]]]
    
    \begin{array}{l}
    U_m = \left|U\right|
    
    \\
    \begin{array}{l}
    t_0 := \cos \left(\frac{K}{2}\right)\\
    t_1 := \left(\left(-2 \cdot J\right) \cdot t\_0\right) \cdot \sqrt{{\left(\frac{U\_m}{t\_0 \cdot \left(J \cdot 2\right)}\right)}^{2} + 1}\\
    t_2 := \cos \left(K \cdot 0.5\right)\\
    \mathbf{if}\;t\_1 \leq -\infty:\\
    \;\;\;\;-U\_m\\
    
    \mathbf{elif}\;t\_1 \leq -5 \cdot 10^{+158}:\\
    \;\;\;\;-2 \cdot \left(\left(J \cdot t\_2\right) \cdot \sqrt{\mathsf{fma}\left(U\_m \cdot 0.25, \frac{U\_m}{J \cdot J}, 1\right)}\right)\\
    
    \mathbf{elif}\;t\_1 \leq -2 \cdot 10^{-119}:\\
    \;\;\;\;J \cdot \left(\left(-2 \cdot t\_2\right) \cdot \sqrt{\mathsf{fma}\left(U\_m \cdot U\_m, \frac{0.25}{\left(J \cdot J\right) \cdot \mathsf{fma}\left(0.5, \cos K, 0.5\right)}, 1\right)}\right)\\
    
    \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+307}:\\
    \;\;\;\;\left(-2 \cdot J\right) \cdot t\_2\\
    
    \mathbf{else}:\\
    \;\;\;\;U\_m\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 5 regimes
    2. if (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < -inf.0

      1. Initial program 5.8%

        \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. Add Preprocessing
      3. Taylor expanded in J around 0

        \[\leadsto \color{blue}{-1 \cdot U} \]
      4. Step-by-step derivation
        1. mul-1-negN/A

          \[\leadsto \color{blue}{\mathsf{neg}\left(U\right)} \]
        2. lower-neg.f6499.7

          \[\leadsto \color{blue}{-U} \]
      5. Simplified99.7%

        \[\leadsto \color{blue}{-U} \]

      if -inf.0 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < -4.9999999999999996e158

      1. Initial program 99.8%

        \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. Add Preprocessing
      3. Taylor expanded in K around 0

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

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

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

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

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

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

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

          \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(\frac{1}{4}, \frac{U \cdot U}{\color{blue}{J \cdot J}}, 1\right)} \]
        8. lower-*.f6466.1

          \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(0.25, \frac{U \cdot U}{\color{blue}{J \cdot J}}, 1\right)} \]
      5. Simplified66.1%

        \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \color{blue}{\sqrt{\mathsf{fma}\left(0.25, \frac{U \cdot U}{J \cdot J}, 1\right)}} \]
      6. Step-by-step derivation
        1. div-invN/A

          \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \color{blue}{\left(K \cdot \frac{1}{2}\right)}\right) \cdot \sqrt{\frac{1}{4} \cdot \frac{U \cdot U}{J \cdot J} + 1} \]
        2. metadata-evalN/A

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

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

          \[\leadsto \left(\left(-2 \cdot J\right) \cdot \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)}\right) \cdot \sqrt{\frac{1}{4} \cdot \frac{U \cdot U}{J \cdot J} + 1} \]
        5. lift-cos.f64N/A

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

          \[\leadsto \color{blue}{\left(-2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right)} \cdot \sqrt{\frac{1}{4} \cdot \frac{U \cdot U}{J \cdot J} + 1} \]
        7. lift-*.f64N/A

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

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

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

          \[\leadsto \left(-2 \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot \sqrt{\frac{1}{4} \cdot \color{blue}{\frac{U \cdot U}{J \cdot J}} + 1} \]
        11. lift-fma.f64N/A

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

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

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

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

          \[\leadsto \color{blue}{\left(\sqrt{\mathsf{fma}\left(\frac{1}{4}, \frac{U \cdot U}{J \cdot J}, 1\right)} \cdot \left(J \cdot \cos \left(\frac{1}{2} \cdot K\right)\right)\right) \cdot -2} \]
      7. Applied egg-rr84.1%

        \[\leadsto \color{blue}{\left(\sqrt{\mathsf{fma}\left(0.25 \cdot U, \frac{U}{J \cdot J}, 1\right)} \cdot \left(J \cdot \cos \left(K \cdot 0.5\right)\right)\right) \cdot -2} \]

      if -4.9999999999999996e158 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < -2.00000000000000003e-119

      1. Initial program 99.8%

        \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. Add Preprocessing
      3. Applied egg-rr94.4%

        \[\leadsto \color{blue}{\left(\sqrt{\mathsf{fma}\left(U, \frac{U}{\left(0.5 + 0.5 \cdot \cos \left(2 \cdot \left(K \cdot 0.5\right)\right)\right) \cdot \left(\left(J \cdot 2\right) \cdot \left(J \cdot 2\right)\right)}, 1\right)} \cdot \left(-2 \cdot \cos \left(K \cdot 0.5\right)\right)\right) \cdot J} \]
      4. Taylor expanded in K around inf

        \[\leadsto \left(\color{blue}{\sqrt{1 + \frac{1}{4} \cdot \frac{{U}^{2}}{{J}^{2} \cdot \left(\frac{1}{2} + \frac{1}{2} \cdot \cos K\right)}}} \cdot \left(-2 \cdot \cos \left(K \cdot \frac{1}{2}\right)\right)\right) \cdot J \]
      5. Step-by-step derivation
        1. lower-sqrt.f64N/A

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

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

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

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

          \[\leadsto \left(\sqrt{\color{blue}{{U}^{2} \cdot \frac{\frac{1}{4}}{{J}^{2} \cdot \left(\frac{1}{2} + \frac{1}{2} \cdot \cos K\right)}} + 1} \cdot \left(-2 \cdot \cos \left(K \cdot \frac{1}{2}\right)\right)\right) \cdot J \]
        6. metadata-evalN/A

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

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

          \[\leadsto \left(\sqrt{\color{blue}{\mathsf{fma}\left({U}^{2}, \frac{1}{4} \cdot \frac{1}{{J}^{2} \cdot \left(\frac{1}{2} + \frac{1}{2} \cdot \cos K\right)}, 1\right)}} \cdot \left(-2 \cdot \cos \left(K \cdot \frac{1}{2}\right)\right)\right) \cdot J \]
      6. Simplified93.5%

        \[\leadsto \left(\color{blue}{\sqrt{\mathsf{fma}\left(U \cdot U, \frac{0.25}{\left(J \cdot J\right) \cdot \mathsf{fma}\left(0.5, \cos K, 0.5\right)}, 1\right)}} \cdot \left(-2 \cdot \cos \left(K \cdot 0.5\right)\right)\right) \cdot J \]

      if -2.00000000000000003e-119 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64))))) < 1.99999999999999997e307

      1. Initial program 99.8%

        \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. Add Preprocessing
      3. Taylor expanded in J around inf

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

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

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

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

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

          \[\leadsto \cos \color{blue}{\left(\frac{1}{2} \cdot K\right)} \cdot \left(-2 \cdot J\right) \]
        6. lower-*.f6467.6

          \[\leadsto \cos \left(0.5 \cdot K\right) \cdot \color{blue}{\left(-2 \cdot J\right)} \]
      5. Simplified67.6%

        \[\leadsto \color{blue}{\cos \left(0.5 \cdot K\right) \cdot \left(-2 \cdot J\right)} \]

      if 1.99999999999999997e307 < (*.f64 (*.f64 (*.f64 #s(literal -2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64)))) (sqrt.f64 (+.f64 #s(literal 1 binary64) (pow.f64 (/.f64 U (*.f64 (*.f64 #s(literal 2 binary64) J) (cos.f64 (/.f64 K #s(literal 2 binary64))))) #s(literal 2 binary64)))))

      1. Initial program 6.5%

        \[\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{1 + {\left(\frac{U}{\left(2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)}\right)}^{2}} \]
      2. Add Preprocessing
      3. Taylor expanded in U around -inf

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

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

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

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

          \[\leadsto \color{blue}{\left(\mathsf{neg}\left(U\right)\right)} \cdot \left(-2 \cdot \frac{{J}^{2} \cdot {\cos \left(\frac{1}{2} \cdot K\right)}^{2}}{{U}^{2}} - 1\right) \]
        5. sub-negN/A

          \[\leadsto \left(\mathsf{neg}\left(U\right)\right) \cdot \color{blue}{\left(-2 \cdot \frac{{J}^{2} \cdot {\cos \left(\frac{1}{2} \cdot K\right)}^{2}}{{U}^{2}} + \left(\mathsf{neg}\left(1\right)\right)\right)} \]
        6. metadata-evalN/A

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \left(-U\right) \cdot \mathsf{fma}\left(-2, {\cos \left(0.5 \cdot K\right)}^{2} \cdot \frac{J \cdot J}{\color{blue}{U \cdot U}}, -1\right) \]
      5. Simplified99.1%

        \[\leadsto \color{blue}{\left(-U\right) \cdot \mathsf{fma}\left(-2, {\cos \left(0.5 \cdot K\right)}^{2} \cdot \frac{J \cdot J}{U \cdot U}, -1\right)} \]
      6. Taylor expanded in J around 0

        \[\leadsto \left(\mathsf{neg}\left(U\right)\right) \cdot \color{blue}{-1} \]
      7. Step-by-step derivation
        1. Simplified99.2%

          \[\leadsto \left(-U\right) \cdot \color{blue}{-1} \]
        2. Step-by-step derivation
          1. lift-neg.f64N/A

            \[\leadsto \color{blue}{\left(\mathsf{neg}\left(U\right)\right)} \cdot -1 \]
          2. *-commutativeN/A

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

            \[\leadsto \color{blue}{\mathsf{neg}\left(\left(\mathsf{neg}\left(U\right)\right)\right)} \]
          4. lower-neg.f6499.2

            \[\leadsto \color{blue}{-\left(-U\right)} \]
        3. Applied egg-rr99.2%

          \[\leadsto \color{blue}{-\left(-U\right)} \]
      8. Recombined 5 regimes into one program.
      9. Final simplification83.6%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq -\infty:\\ \;\;\;\;-U\\ \mathbf{elif}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq -5 \cdot 10^{+158}:\\ \;\;\;\;-2 \cdot \left(\left(J \cdot \cos \left(K \cdot 0.5\right)\right) \cdot \sqrt{\mathsf{fma}\left(U \cdot 0.25, \frac{U}{J \cdot J}, 1\right)}\right)\\ \mathbf{elif}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq -2 \cdot 10^{-119}:\\ \;\;\;\;J \cdot \left(\left(-2 \cdot \cos \left(K \cdot 0.5\right)\right) \cdot \sqrt{\mathsf{fma}\left(U \cdot U, \frac{0.25}{\left(J \cdot J\right) \cdot \mathsf{fma}\left(0.5, \cos K, 0.5\right)}, 1\right)}\right)\\ \mathbf{elif}\;\left(\left(-2 \cdot J\right) \cdot \cos \left(\frac{K}{2}\right)\right) \cdot \sqrt{{\left(\frac{U}{\cos \left(\frac{K}{2}\right) \cdot \left(J \cdot 2\right)}\right)}^{2} + 1} \leq 2 \cdot 10^{+307}:\\ \;\;\;\;\left(-2 \cdot J\right) \cdot \cos \left(K \cdot 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;U\\ \end{array} \]
      10. Add Preprocessing

      Reproduce

      ?
      herbie shell --seed 2024218 
      (FPCore (J K U)
        :name "Maksimov and Kolovsky, Equation (3)"
        :precision binary64
        (* (* (* -2.0 J) (cos (/ K 2.0))) (sqrt (+ 1.0 (pow (/ U (* (* 2.0 J) (cos (/ K 2.0)))) 2.0)))))