Average Error: 0.0 → 0.0
Time: 3.1s
Precision: 64
\[x.re \cdot y.re - x.im \cdot y.im\]
↓
\[\mathsf{fma}\left(x.re \cdot 1, y.re, -y.im \cdot x.im\right)\]
x.re \cdot y.re - x.im \cdot y.im
↓
\mathsf{fma}\left(x.re \cdot 1, y.re, -y.im \cdot x.im\right)
double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((double) (((double) (x_46_re * y_46_re)) - ((double) (x_46_im * y_46_im))));
}
↓
double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((double) fma(((double) (x_46_re * 1.0)), y_46_re, ((double) -(((double) (y_46_im * x_46_im))))));
}

Error

Bits error versus x.re

Bits error versus x.im

Bits error versus y.re

Bits error versus y.im

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[x.re \cdot y.re - x.im \cdot y.im\]
  2. Using strategy rm

  3. Applied *-un-lft-identity0.0

    \[\leadsto x.re \cdot \color{blue}{\left(1 \cdot y.re\right)} - x.im \cdot y.im\]

  4. Applied associate-*r*0.0

    \[\leadsto \color{blue}{\left(x.re \cdot 1\right) \cdot y.re} - x.im \cdot y.im\]

  5. Applied fma-neg0.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(x.re \cdot 1, y.re, -x.im \cdot y.im\right)}\]

  6. Simplified0.0

    \[\leadsto \mathsf{fma}\left(x.re \cdot 1, y.re, \color{blue}{-y.im \cdot x.im}\right)\]

  7. Final simplification0.0

    \[\leadsto \mathsf{fma}\left(x.re \cdot 1, y.re, -y.im \cdot x.im\right)\]

Reproduce

herbie shell --seed 2020113 +o rules:numerics
(FPCore (x.re x.im y.re y.im)
  :name "_multiplyComplex, real part"
  :precision binary64
  (- (* x.re y.re) (* x.im y.im)))