COMPUTING THE LOWEST EIGENVALUES OF THE FERMION MATRIX BY SUBSPACE ITERATIONS

Subspace iterations are used to minimise a generalised Ritz functional of a large, sparse Hermitean matrix. In this way, the lowest m eigenv alues are determined. Tests with 1 less than or equal to m less than o r equal to 32 demonstrate that the computational cost (no. of matrix m ultiplies) does not increase substantially with m. This implies that, as compared to the case of a m=1, the additional eigenvalues are obtai ned for free.