Average Error: 52.4 → 1.5
Time: 4.5s
Precision: binary64
\[\left(\left(4.930380657631324 \cdot 10^{-32} < a \land a < 2.028240960365167 \cdot 10^{+31}\right) \land \left(4.930380657631324 \cdot 10^{-32} < b \land b < 2.028240960365167 \cdot 10^{+31}\right)\right) \land \left(4.930380657631324 \cdot 10^{-32} < c \land c < 2.028240960365167 \cdot 10^{+31}\right)\]
\[\frac{\left(-b\right) + \sqrt{b \cdot b - \left(3 \cdot a\right) \cdot c}}{3 \cdot a} \]
\[\mathsf{fma}\left(-0.16666666666666666, {a}^{3} \cdot \frac{{c}^{4} \cdot 6.328125}{{b}^{7}}, \mathsf{fma}\left(-0.5, \frac{c}{b}, \mathsf{fma}\left(-0.375, \left(c \cdot c\right) \cdot \frac{a}{{b}^{3}}, -0.5625 \cdot \left({c}^{3} \cdot \frac{a \cdot a}{{b}^{5}}\right)\right)\right)\right) \]
(FPCore (a b c)
 :precision binary64
 (/ (+ (- b) (sqrt (- (* b b) (* (* 3.0 a) c)))) (* 3.0 a)))
(FPCore (a b c)
 :precision binary64
 (fma
  -0.16666666666666666
  (* (pow a 3.0) (/ (* (pow c 4.0) 6.328125) (pow b 7.0)))
  (fma
   -0.5
   (/ c b)
   (fma
    -0.375
    (* (* c c) (/ a (pow b 3.0)))
    (* -0.5625 (* (pow c 3.0) (/ (* a a) (pow b 5.0))))))))
double code(double a, double b, double c) {
	return (-b + sqrt(((b * b) - ((3.0 * a) * c)))) / (3.0 * a);
}
double code(double a, double b, double c) {
	return fma(-0.16666666666666666, (pow(a, 3.0) * ((pow(c, 4.0) * 6.328125) / pow(b, 7.0))), fma(-0.5, (c / b), fma(-0.375, ((c * c) * (a / pow(b, 3.0))), (-0.5625 * (pow(c, 3.0) * ((a * a) / pow(b, 5.0)))))));
}
function code(a, b, c)
	return Float64(Float64(Float64(-b) + sqrt(Float64(Float64(b * b) - Float64(Float64(3.0 * a) * c)))) / Float64(3.0 * a))
end
function code(a, b, c)
	return fma(-0.16666666666666666, Float64((a ^ 3.0) * Float64(Float64((c ^ 4.0) * 6.328125) / (b ^ 7.0))), fma(-0.5, Float64(c / b), fma(-0.375, Float64(Float64(c * c) * Float64(a / (b ^ 3.0))), Float64(-0.5625 * Float64((c ^ 3.0) * Float64(Float64(a * a) / (b ^ 5.0)))))))
end
code[a_, b_, c_] := N[(N[((-b) + N[Sqrt[N[(N[(b * b), $MachinePrecision] - N[(N[(3.0 * a), $MachinePrecision] * c), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(3.0 * a), $MachinePrecision]), $MachinePrecision]
code[a_, b_, c_] := N[(-0.16666666666666666 * N[(N[Power[a, 3.0], $MachinePrecision] * N[(N[(N[Power[c, 4.0], $MachinePrecision] * 6.328125), $MachinePrecision] / N[Power[b, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.5 * N[(c / b), $MachinePrecision] + N[(-0.375 * N[(N[(c * c), $MachinePrecision] * N[(a / N[Power[b, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.5625 * N[(N[Power[c, 3.0], $MachinePrecision] * N[(N[(a * a), $MachinePrecision] / N[Power[b, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{\left(-b\right) + \sqrt{b \cdot b - \left(3 \cdot a\right) \cdot c}}{3 \cdot a}
\mathsf{fma}\left(-0.16666666666666666, {a}^{3} \cdot \frac{{c}^{4} \cdot 6.328125}{{b}^{7}}, \mathsf{fma}\left(-0.5, \frac{c}{b}, \mathsf{fma}\left(-0.375, \left(c \cdot c\right) \cdot \frac{a}{{b}^{3}}, -0.5625 \cdot \left({c}^{3} \cdot \frac{a \cdot a}{{b}^{5}}\right)\right)\right)\right)

Error

Derivation

  1. Initial program 52.4

    \[\frac{\left(-b\right) + \sqrt{b \cdot b - \left(3 \cdot a\right) \cdot c}}{3 \cdot a} \]
  2. Simplified52.4

    \[\leadsto \color{blue}{\left(\sqrt{\mathsf{fma}\left(b, b, c \cdot \left(a \cdot -3\right)\right)} - b\right) \cdot \frac{0.3333333333333333}{a}} \]
  3. Taylor expanded in b around inf 2.0

    \[\leadsto \color{blue}{\left(-0.5 \cdot \frac{{\left(-1.125 \cdot \left({c}^{2} \cdot {a}^{2}\right)\right)}^{2} + 5.0625 \cdot \left({c}^{4} \cdot {a}^{4}\right)}{{b}^{7}} + \left(-1.125 \cdot \frac{{c}^{2} \cdot {a}^{2}}{{b}^{3}} + \left(-1.5 \cdot \frac{c \cdot a}{b} + -1.6875 \cdot \frac{{c}^{3} \cdot {a}^{3}}{{b}^{5}}\right)\right)\right)} \cdot \frac{0.3333333333333333}{a} \]
  4. Simplified2.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(-1.125, \left(c \cdot c\right) \cdot \left(a \cdot \frac{a}{{b}^{3}}\right), \mathsf{fma}\left(-0.5, \frac{\mathsf{fma}\left(5.0625, {c}^{4} \cdot {a}^{4}, {\left(-1.125 \cdot \left(a \cdot \left(c \cdot \left(c \cdot a\right)\right)\right)\right)}^{2}\right)}{{b}^{7}}, \mathsf{fma}\left(-1.5, c \cdot \frac{a}{b}, -1.6875 \cdot \left({c}^{3} \cdot \frac{{a}^{3}}{{b}^{5}}\right)\right)\right)\right)} \cdot \frac{0.3333333333333333}{a} \]
  5. Taylor expanded in a around 0 1.5

    \[\leadsto \color{blue}{-0.16666666666666666 \cdot \frac{\left(5.0625 \cdot {c}^{4} + 1.265625 \cdot {c}^{4}\right) \cdot {a}^{3}}{{b}^{7}} + \left(-0.5625 \cdot \frac{{c}^{3} \cdot {a}^{2}}{{b}^{5}} + \left(-0.5 \cdot \frac{c}{b} + -0.375 \cdot \frac{{c}^{2} \cdot a}{{b}^{3}}\right)\right)} \]
  6. Simplified1.5

    \[\leadsto \color{blue}{\mathsf{fma}\left(-0.16666666666666666, {a}^{3} \cdot \frac{{c}^{4} \cdot 6.328125}{{b}^{7}}, \mathsf{fma}\left(-0.5, \frac{c}{b}, \mathsf{fma}\left(-0.375, \left(c \cdot c\right) \cdot \frac{a}{{b}^{3}}, -0.5625 \cdot \left({c}^{3} \cdot \frac{a \cdot a}{{b}^{5}}\right)\right)\right)\right)} \]
  7. Final simplification1.5

    \[\leadsto \mathsf{fma}\left(-0.16666666666666666, {a}^{3} \cdot \frac{{c}^{4} \cdot 6.328125}{{b}^{7}}, \mathsf{fma}\left(-0.5, \frac{c}{b}, \mathsf{fma}\left(-0.375, \left(c \cdot c\right) \cdot \frac{a}{{b}^{3}}, -0.5625 \cdot \left({c}^{3} \cdot \frac{a \cdot a}{{b}^{5}}\right)\right)\right)\right) \]

Reproduce

herbie shell --seed 2022203 
(FPCore (a b c)
  :name "Cubic critical, wide range"
  :precision binary64
  :pre (and (and (and (< 4.930380657631324e-32 a) (< a 2.028240960365167e+31)) (and (< 4.930380657631324e-32 b) (< b 2.028240960365167e+31))) (and (< 4.930380657631324e-32 c) (< c 2.028240960365167e+31)))
  (/ (+ (- b) (sqrt (- (* b b) (* (* 3.0 a) c)))) (* 3.0 a)))