An algorithm for identifying eigenvectors exhibiting strong spatial localization
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- by Jeffrey S. Ovall and Robyn Reid;
- Math. Comp. 92 (2023), 1005-1031
- DOI: https://doi.org/10.1090/mcom/3734
- Published electronically: January 6, 2023
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Abstract:
We introduce an approach for exploring eigenvector localization phenomena for a class of (unbounded) selfadjoint operators. More specifically, given a target region and a tolerance, the algorithm identifies candidate eigenpairs for which the eigenvector is expected to be localized in the target region to within that tolerance. Theoretical results, together with detailed numerical illustrations of them, are provided that support our algorithm. A partial realization of the algorithm is described and tested, providing a proof of concept for the approach.References
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Bibliographic Information
- Jeffrey S. Ovall
- Affiliation: Fariborz Maseeh Department of Mathematics and Statistics, Portland State University, Portland, Oregon 97201
- MR Author ID: 728623
- Email: jovall@pdx.edu
- Robyn Reid
- Affiliation: Fariborz Maseeh Department of Mathematics and Statistics, Portland State University, Portland, Oregon 97201
- Email: reid3@pdx.edu
- Received by editor(s): May 29, 2021
- Received by editor(s) in revised form: September 14, 2022
- Published electronically: January 6, 2023
- Additional Notes: This material is based upon work supported by the National Science Foundation under Grant No. DMS-2208056.
- © Copyright 2023 American Mathematical Society
- Journal: Math. Comp. 92 (2023), 1005-1031
- MSC (2000): Primary 65N25; Secondary 35P15, 47A75
- DOI: https://doi.org/10.1090/mcom/3734
- MathSciNet review: 4550318