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Harmonic analysis of large systems. I. Methodology

Brooks, Bernard R., Janežič, Dušanka, Karplus, Martin·1995·Journal of Computational Chemistry

Abstract

Methods have been developed for the determination of vibrational frequencies and normal modes of large systems in the full conformational space (including all degrees of freedom) and in a reduced conformational space (reducing the number of degrees of freedom). The computational method, which includes Hessian generation and storage, full and iterative diagonalization techniques, and the refinement of the results, is presented. A method is given for the quasiharmonic analysis and the reduced basis quasiharmonic analysis. The underlying principle is that from the atomic fluctuations, an effective harmonic force field can be determined relative to the dynamic average structure. Normal mode analysis tools can be used to characterize quasiharmonic modes of vibration. These correspond to conventional normal modes except that anharmonic effects are included. Numerous techniques for the analyses of vibrational frequencies and normal modes are described. Criteria for the analysis of the similarity of low‐frequency normal modes is presented. The approach to determining the natural frequencies and normal modes of vibration described here is general and applicable to any large system. © 1995 John Wiley & Sons, Inc.This article is a U.S. Government work and, as such, is in the public domain in the United States of America.

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Metadata

Authors
Brooks, B. R., Janežič, D., & Karplus, M.
Venue
Journal of Computational Chemistry
Publisher
Wiley
Published
1995-12
Volume
16
Issue
12
Pages
1522-1542
ISSN
  • 0192-8651 (ISSN-L)
  • 1096-987X
OpenAlex
W2093151204
Cited by
489
References
22
FWCI
2.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Harmonic analysis of large systems. I. Methodology. https://app.cochat.ai/papers/10.1002/jcc.540161209
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Brooks, B. R., Janežič, D., & Karplus, M. (1995). Harmonic analysis of large systems. I. Methodology. Journal of Computational Chemistry. https://doi.org/10.1002/jcc.540161209

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