The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach

被引:4
|
作者
Harlev, Amit [1 ]
Johnson, Charles R. [2 ]
Lim, Derek [3 ]
机构
[1] Harvey Mudd Univ, Dept Math, Claremont, CA USA
[2] Coll William & Mary, Dept Math, Williamsburg, VA 23185 USA
[3] Cornell Univ, Dept Math, White Hall, Ithaca, NY 14853 USA
基金
美国国家科学基金会;
关键词
Doubly stochastic matrix; Eigenvalue; Group representation; Permutation matrix; Single eigenvalue problem;
D O I
10.1080/10586458.2020.1727799
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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 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.
引用
收藏
页码:936 / 945
页数:10
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