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ARPACK: Solving large scale eigenvalue problems

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ARPACK: Solving large scale eigenvalue problems

Postby owlice » Sat Nov 30, 2013 10:28 pm

ARPACK: Solving large scale eigenvalue problems

Abstract: ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute a few eigenvalues and corresponding eigenvectors of a general n by n matrix A. It is most appropriate for large sparse or structured matrices A where structured means that a matrix-vector product w <- Av requires order n rather than the usual order n2 floating point operations. This software is based upon an algorithmic variant of the Arnoldi process called the Implicitly Restarted Arnoldi Method (IRAM). When the matrix A is symmetric it reduces to a variant of the Lanczos process called the Implicitly Restarted Lanczos Method (IRLM). These variants may be viewed as a synthesis of the Arnoldi/Lanczos process with the Implicitly Shifted QR technique that is suitable for large scale problems. For many standard problems, a matrix factorization is not required; only the action of the matrix on a vector is needed. ARPACK is capable of solving large scale symmetric, nonsymmetric, and generalized eigenproblems from significant application areas.

Credit: Lehoucq, Rich; Maschhoff, Kristi; Sorensen, Danny; Yang, Chao

Site: https://www.caam.rice.edu/software/ARPACK/
http://adsabs.harvard.edu/abs/2000APS..MARM19003T

Bibcode: 2013ascl.soft11010L

ID: ascl:1311.010
Last edited by Ada Coda on Sun Feb 03, 2019 7:12 pm, edited 1 time in total.
Reason: Updated code entry.
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