Computing the lowest eigenvalues of the Fermion matrix by subspace iterations

Details Computing the lowest eigenvalues of the Fermion matrix by subspace iterations Computing the lowest eigenvalues of the Fermion matrix by subspace iterations

1996-08-21

arxiv.org/abs/hep-lat/9608109v1

Nucl.Phys.Proc.Suppl. 53 (1997) 987-989

Physics

High Energy Physics

High Energy Physics - Lattice

Talk presented at LATTICE96(algorithms), 3 pages, 2 Postscript figures, uses epsf.sty, espcrc2.sty

Scientific paper

10.1016/S0920-5632(96)00835-3

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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