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Bibliographic Details
Main Authors: Ahuja, Chahat, Chowdhury, Partha, Mohapatra, Subhashree
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.13409
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author Ahuja, Chahat
Chowdhury, Partha
Mohapatra, Subhashree
author_facet Ahuja, Chahat
Chowdhury, Partha
Mohapatra, Subhashree
contents This work presents a novel approach to compute the eigenvalues of non-Hermitian matrices using an enhanced shifted QR algorithm. The existing QR algorithms fail to converge early in the case of non-hermitian matrices, and our approach shows significant improvement in convergence rate while maintaining accuracy for all test cases. In this work, though our prior focus will be to address the results for a class mid- large sized non-Hermitian matrices, our algorithm has also produced significant improvements in the case of comparatively larger matrices such as 50 x 50 non-Hermitian matrices
format Preprint
id arxiv_https___arxiv_org_abs_2510_13409
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An Enhanced Shifted QR Algorithm for Efficient Eigenvalue Computation of Square Non-Hermitian Matrices
Ahuja, Chahat
Chowdhury, Partha
Mohapatra, Subhashree
Numerical Analysis
This work presents a novel approach to compute the eigenvalues of non-Hermitian matrices using an enhanced shifted QR algorithm. The existing QR algorithms fail to converge early in the case of non-hermitian matrices, and our approach shows significant improvement in convergence rate while maintaining accuracy for all test cases. In this work, though our prior focus will be to address the results for a class mid- large sized non-Hermitian matrices, our algorithm has also produced significant improvements in the case of comparatively larger matrices such as 50 x 50 non-Hermitian matrices
title An Enhanced Shifted QR Algorithm for Efficient Eigenvalue Computation of Square Non-Hermitian Matrices
topic Numerical Analysis
url https://arxiv.org/abs/2510.13409