Computing the eigenvalues of symmetric H2-matrices by slicing the spectrum
classification
🧮 math.NA
keywords
eigenvaluesalphamatricesslicingspectrumsymmetricadvantagealgorithm
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The computation of eigenvalues of large-scale matrices arising from finite element discretizations has gained significant interest in the last decade. Here we present a new algorithm based on slicing the spectrum that takes advantage of the rank structure of resolvent matrices in order to compute m eigenvalues of the generalized symmetric eigenvalue problem in $\mathcal{O}(n m \log^\alpha n)$ operations, where $\alpha>0$ is a small constant.
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