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Original Articles

The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach

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Pages 936-945 | Published online: 10 Mar 2020
 

Abstract

The problem of determining DSn, the complex numbers that occur as an eigenvalue of an n-by-n doubly stochastic matrix, has been a target of study for some time. The Perfect-Mirsky region, PMn, is contained in DSn and is known to be exactly DSn for n4, but strictly contained within DSn for n = 5. Here, we present a Boundary Conjecture that asserts that the boundary of DSn is achieved by eigenvalues of convex combinations of pairs of (or single) permutation matrices. We present a method to efficiently compute a portion of DSn and obtain computational results that support the Boundary Conjecture. We also give evidence that DSn is equal to PMn for certain n > 5.

2010 AMS Subject Classification:

Acknowledgments

We would like to thank the anonymous reviewer for his suggestions on the manuscript. We would also like to thank Jamie Barsotti for assistance with bringing our attention to the relevant theory on G-sets, and for assistance in deriving the algorithm to compute the inequivalent pairs. Moreover, we would like to thank John Wilkes, who carried out initial work on this problem in his honors thesis at the College of William and Mary advised by Charles R. Johnson [Citation10].

This work was performed [in part] using computing facilities at the College of William and Mary, which were provided by contributions from the National Science Foundation, the Commonwealth of Virginia Equipment Trust Fund and the Office of Naval Research.

Declaration of Interest

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Science Foundation under Grant DMS #1757603.

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