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| Preprint | FZJ-2014-00586 |
; ;
2013
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Please use a persistent id in citations: http://hdl.handle.net/2128/5812
Abstract: Estimating the number of eigenvalues located in a given interval of a large sparse Hermitian matrix is an important problem in certain applications and it is a prerequisite of eigensolvers based on a divide-and-conquer paradigm. Often an exact count is not necessary and methods based on stochastic estimates can be utilized to yield rough approximations. This paper examines a number of techniques tailored to this specific task. It reviews standard approaches and explores new ones based on polynomial and rational approximation filtering combined with stochastic procedure.
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