Reduced basis approximation of parametric eigenvalue problems in presence of clusters and intersections
In this paper we discuss reduced order models for the approximation of parametric eigenvalue problems. In particular, we are interested in the presence of intersections or clusters of eigenvalues. The singularities originating by these phenomena make it hard a straightforward generalization of well...
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Zusammenfassung: | In this paper we discuss reduced order models for the approximation of
parametric eigenvalue problems. In particular, we are interested in the
presence of intersections or clusters of eigenvalues. The singularities
originating by these phenomena make it hard a straightforward generalization of
well known strategies normally used for standards PDEs. We investigate how the
known results extend (or not) to higher order frequencies. |
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DOI: | 10.48550/arxiv.2302.00898 |