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# scipy.optimize.broyden2

`scipy.optimize.``broyden2`(F, xin, iter=10, alpha=0.40000000000000002, verbose=False)

  Broyden’s second method.

  Updates inverse Jacobian by an optimal formula. There is NxN matrix multiplication in every iteration.

  The best norm |F(x)|=0.003 achieved in ~20 iterations.

  Recommended.

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