Preprint FZJ-2014-00586

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Efficient estimation of eigenvalue counts in an interval

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2013

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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.


Note: 23 pages and 10 figures. Submitted to SIAM Journal of Matrix Analysis.

Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 411 - Computational Science and Mathematical Methods (POF2-411) (POF2-411)

Appears in the scientific report 2013
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 Record created 2014-01-21, last modified 2021-01-29