2013
DOI: 10.1515/cmam-2013-0013
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A Short Theory of the Rayleigh–Ritz Method

Abstract: -We present some new error estimates for the eigenvalues and eigenfunctions obtained by the Rayleigh-Ritz method, the common variational method to solve eigenproblems. The errors are bounded in terms of the error of the best approximation of the eigenfunction under consideration by functions in the ansatz space. In contrast to the classical theory, the approximation error of eigenfunctions other than the given one does not enter into these estimates. The estimates are based on a bound for the norm of a certain… Show more

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Cited by 11 publications
(9 citation statements)
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“…In that paper an error analysis of the Rayleigh-Ritz method without penalization or consistency errors is presented that shows how the error in an eigenvector (and eigenvalue) approximation can be bounded in terms of its best approximation in the ansatz space, in the same spirit as the more general results in [23]. We generalize the results of [43] in the sense that we allow penalization and consistency errors, i.e., we generalize the analysis of [43] to the abstract setting presented in section 4.1.…”
Section: Thus We Getmentioning
confidence: 76%
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“…In that paper an error analysis of the Rayleigh-Ritz method without penalization or consistency errors is presented that shows how the error in an eigenvector (and eigenvalue) approximation can be bounded in terms of its best approximation in the ansatz space, in the same spirit as the more general results in [23]. We generalize the results of [43] in the sense that we allow penalization and consistency errors, i.e., we generalize the analysis of [43] to the abstract setting presented in section 4.1.…”
Section: Thus We Getmentioning
confidence: 76%
“…Remark 6.2. Even for the conforming case d λ (•, •) = 0, the bound in Theorem 6.3 differs from the one derived in [43]. In that paper stability (i.e., uniform boundedness) of the b h -orthogonal projection Q h in the energy norm is assumed.…”
Section: And Is Given Bymentioning
confidence: 86%
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“…In every example, the Algorithm 1 is compared with the iterative Rayleigh–Ritz procedure . In the Rayleigh–Ritz procedure, m smallest eigenvectors are computed as well, and the size of the projected problem is the same as the size of the corresponding projected problem in the Algorithm 1, which is m + n .…”
Section: Numerical Examplesmentioning
confidence: 99%