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Computing the lowest eigenvalues of the Fermion matrix by subspace iterations

B. Bunk
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Abstract

Subspace iterations are used to minimise a generalised Ritz functional of a large, sparse Hermitean matrix. In this way, the lowest $m$ eigenvalues are determined. Tests with $1 \leq m \leq 32$ demonstrate that the computational cost (no. of matrix multiplies) does not increase substantially with $m$. This implies that, as compared to the case of a $m=1$, the additional eigenvalues are obtained for free.

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BibTeXRIS

B. Bunk. 1996-08-21. Computing the lowest eigenvalues of the Fermion matrix by subspace iterations. https://doi.org/10.1016/s0920-5632(96)00835-3

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