Reduced-basis projections of parametric eigenvalue problems are proven to approximate eigenvalues and eigenspaces including repeated eigenvalue cases, with error bounds verified on 1D to 3D finite element examples.
Computational quantum chemistry: A primer
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Theory and numerics of subspace approximation of eigenvalue problems
Reduced-basis projections of parametric eigenvalue problems are proven to approximate eigenvalues and eigenspaces including repeated eigenvalue cases, with error bounds verified on 1D to 3D finite element examples.