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.
Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method.SIAM journal on scientific computing, 23(2):517–541, 2001
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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.