NANAMar 8, 2010

An integral method for solving nonlinear eigenvalue problems

arXiv:1003.1580359 citationsh-index: 29
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This provides a robust, initialization-free method for solving nonlinear eigenvalue problems, particularly useful when the number of sought eigenvalues is much smaller than the matrix dimension.

The paper proposes a numerical method for computing all eigenvalues of a nonlinear holomorphic eigenvalue problem within a given contour, reducing it to a linear eigenvalue problem of dimension equal to the number of eigenvalues inside the contour, with exponential convergence of quadrature errors.

We propose a numerical method for computing all eigenvalues (and the corresponding eigenvectors) of a nonlinear holomorphic eigenvalue problem that lie within a given contour in the complex plane. The method uses complex integrals of the resolvent operator, applied to at least $k$ column vectors, where $k$ is the number of eigenvalues inside the contour. The theorem of Keldysh is employed to show that the original nonlinear eigenvalue problem reduces to a linear eigenvalue problem of dimension $k$. No initial approximations of eigenvalues and eigenvectors are needed. The method is particularly suitable for moderately large eigenvalue problems where $k$ is much smaller than the matrix dimension. We also give an extension of the method to the case where $k$ is larger than the matrix dimension. The quadrature errors caused by the trapezoid sum are discussed for the case of analytic closed contours. Using well known techniques it is shown that the error decays exponentially with an exponent given by the product of the number of quadrature points and the minimal distance of the eigenvalues to the contour.

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