scipy.optimize.broyden_generalized(F, xin, iter=10, alpha=0.10000000000000001, M=5, verbose=False)

Generalized Broyden’s method.

Computes an approximation to the inverse Jacobian from the last M interations. Avoids NxN matrix multiplication, it only has MxM matrix multiplication and inversion.

M=0 .... linear mixing M=1 .... Anderson mixing with 2 iterations M=2 .... Anderson mixing with 3 iterations etc. optimal is M=5

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