Title
FEAST As A Subspace Iteration Eigensolver Accelerated By Approximate Spectral Projection.
Abstract
The calculation of a segment of eigenvalues and their corresponding eigenvectors of a Hermitian matrix or matrix pencil has many applications. A new density-matrix-based algorithm has been proposed recently and a software package FEAST has been developed. The density-matrix approach allows FEAST's implementation to exploit a key strength of modern computer architectures, namely, multiple levels of parallelism. Consequently, the software package has been well received, especially in the electronic structure community. Nevertheless, theoretical analysis of FEAST has lagged. For instance, the FEAST algorithm has not been proven to converge. This paper offers a detailed numerical analysis of FEAST. In particular, we show that the FEAST algorithm can be understood as an accelerated subspace iteration algorithm in conjunction with the Rayleigh-Ritz procedure. The novelty of FEAST lies in its accelerator, which is a rational matrix function that approximates the spectral projector onto the eigenspace in question. Analysis of the numerical nature of this approximate spectral projector and the resulting subspaces generated in the FEAST algorithm establishes the algorithm's convergence. This paper shows that FEAST is resilient against rounding errors and establishes properties that can be leveraged to enhance the algorithm's robustness. Finally, we propose an extension of FEAST to handle non-Hermitian problems and suggest some future research directions.
Year
DOI
Venue
2014
10.1137/13090866X
SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS
Keywords
Field
DocType
generalized eigenvalue problem,subspace iteration,spectral projection
Convergence (routing),Mathematical optimization,Matrix pencil,Subspace topology,Algorithm,Robustness (computer science),Linear subspace,Rounding,Hermitian matrix,Mathematics,Eigenvalues and eigenvectors
Journal
Volume
Issue
ISSN
35
2
0895-4798
Citations 
PageRank 
References 
30
1.45
7
Authors
2
Name
Order
Citations
PageRank
Ping Tak Peter Tang116221.02
Eric Polizzi214812.54