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Variational constraints on perturbed eigenvalues and their perturbation expansions

The Journal of Chemical Physics, 1977
The variational principle, in the form of the minimum principle, the Hellmann–Feynman theorem, the curvature theorem, and the virial theorem, is used to derive a number of variational constraints on perturbed exact and variational eigenvalues and on their respective Rayleigh–Schrödinger (RS) and perturbational–variational (PV) perturbation expansions ...
Jeremiah N. Silverman, Jon C. van Leuven
openaire   +2 more sources

Eigenvalues of the real generalized eigenvalue equation perturbed by a low-rank perturbation

Journal of Mathematical Chemistry, 1992
The low-rank perturbation (LRP) method solves the perturbed eigenvalue equation (B +V)Ψ k = ɛ k (C +P)Ψ k , where the eigenvalues and the eigenstates of the related unperturbed eigenvalue equationBΦ i = λ i CΦ i are known. The method is designed for arbitraryn-by-n matricesB, V, C, andP, with the only restriction that the eigenstates Φ i of the ...
openaire   +2 more sources

Summation of the eigenvalue perturbation series by multi-valued Pade approximants: application to resonance problems and double wells

, 1995
Quadratic Pade approximants are used to obtain energy levels both for the anharmonic oscillator x2/2- lambda x4 and for the double well -x2/2+ lambda x4.
A. V. Sergeev
semanticscholar   +1 more source

Perturbation of Partitioned Hermitian Definite Generalized Eigenvalue Problems

SIAM Journal on Matrix Analysis and Applications, 2011
This paper is concerned with the Hermitian definite generalized eigenvalue problem A− λB for block diagonal matrices A 1⁄4 diagðA11; A22Þ and B 1⁄4 diagðB11; B22Þ. Both A and B are Hermitian, and B is positive definite. Bounds on how its eigenvalues vary
Ren-Cang Li   +3 more
semanticscholar   +1 more source

Sensitivity of Repeated Eigenvalues to Perturbations

AIAA Journal, 2005
Two methods for calculating the derivatives of a repeated eigenvalue of viscously damped vibrating systems with respect to a parameter are given. The first method implements the subspace spanned by the eigenvectors corresponding to the repeated eigenvalue. The second method is based on an explicit formula that uses the characteristic equation directly,
Su-Seng Pang   +2 more
openaire   +2 more sources

Perturbation Finite Element Transfer Matrix Method for Random Eigenvalue Problems of Uncertain Structures

, 2012
The rapid computation of random eigenvalue problems of uncertain structures is the key point in structural dynamics, and it is prerequisite to the efficient dynamic analysis and optimal design of structures.
B. Rong, X. Rui, L. Tao
semanticscholar   +1 more source

Numerical Methods for Large Eigenvalue Problems

, 2011
Preface to the Classics Edition Preface 1. Background in matrix theory and linear algebra 2. Sparse matrices 3. Perturbation theory and error analysis 4. The tools of spectral approximation 5. Subspace iteration 6. Krylov subspace methods 7.
Y. Saad
semanticscholar   +1 more source

Location and perturbation of eigenvalues

1985
Introduction The eigenvalues of a diagonal matrix are very easy to locate, and the eigenvalues of a matrix are continuous functions of the entries, so it is natural to ask whether one can say anything useful about the eigenvalues of a matrix whose off-diagonal elements are “small” relative to the main diagonal entries.
Roger A. Horn, Charles R. Johnson
openaire   +2 more sources

Eigenvalue problems for perturbed p‐Laplacians

AIP Conference Proceedings, 2010
This main subject of this paper is the problem of the existence of eigenvectors and a dispersion analysis of a class of multi parameter eiegen‐value problems for perturbed p‐Laplacians. This paper is particularly, devoted to the problems of describing the eigen‐parameters.
openaire   +3 more sources

Eigenvalue perturbation theory

Spectra and Pseudospectra, 2020
Raphael Ducatez
semanticscholar   +1 more source

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