About: Newton–Krylov method

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Newton–Krylov methods are numerical methods for solving non-linear problems using Krylov subspace linear solvers. The Newton method, when generalised to systems of multiple variables, includes the inverse of a Jacobian matrix in the iteration formula. Calculation of the inverse of the Jacobian matrix is bypassed by employing a Krylov subspace method, e.g. the Generalized minimal residual method (GMRES), to solve the iteration formula.

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  • Newton–Krylov methods are numerical methods for solving non-linear problems using Krylov subspace linear solvers. The Newton method, when generalised to systems of multiple variables, includes the inverse of a Jacobian matrix in the iteration formula. Calculation of the inverse of the Jacobian matrix is bypassed by employing a Krylov subspace method, e.g. the Generalized minimal residual method (GMRES), to solve the iteration formula. (en)
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  • Newton–Krylov methods are numerical methods for solving non-linear problems using Krylov subspace linear solvers. The Newton method, when generalised to systems of multiple variables, includes the inverse of a Jacobian matrix in the iteration formula. Calculation of the inverse of the Jacobian matrix is bypassed by employing a Krylov subspace method, e.g. the Generalized minimal residual method (GMRES), to solve the iteration formula. (en)
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  • Newton–Krylov method (en)
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