Minimal compact operators, subdifferential of the maximum eigenvalue and semi-definite programming

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Main Authors: Bottazzi, Tamara, Varela, Alejandro
Format: Preprint
Published: 2024
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author Bottazzi, Tamara
Varela, Alejandro
author_facet Bottazzi, Tamara
Varela, Alejandro
contents We formulate the issue of minimality of self-adjoint operators on a Hilbert space as a semi-definite problem, linking the work by Overton in [1] to the characterization of minimal hermitian matrices. This motivates us to investigate the relationship between minimal self-adjoint operators and the subdifferential of the maximum eigenvalue, initially for matrices and subsequently for compact operators. In order to do it we obtain new formulas of subdifferentials of maximum eigenvalues of compact operators that become useful in these optimization problems. Additionally, we provide formulas for the minimizing diagonals of rank one self-adjoint operators, a result that might be applied for numerical large-scale eigenvalue optimization. [1] On minimizing the maximum eigenvalue of a symmetric matrix, SIAM J. Matrix Anal. Appl.9 (1988), no 4, 905-918
format Preprint
id arxiv_https___arxiv_org_abs_2405_08923
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Minimal compact operators, subdifferential of the maximum eigenvalue and semi-definite programming
Bottazzi, Tamara
Varela, Alejandro
Functional Analysis
Operator Algebras
Primary: 15A60, 47A12, 47B15. Secondary: 47A05, 47A30, 51M15
We formulate the issue of minimality of self-adjoint operators on a Hilbert space as a semi-definite problem, linking the work by Overton in [1] to the characterization of minimal hermitian matrices. This motivates us to investigate the relationship between minimal self-adjoint operators and the subdifferential of the maximum eigenvalue, initially for matrices and subsequently for compact operators. In order to do it we obtain new formulas of subdifferentials of maximum eigenvalues of compact operators that become useful in these optimization problems. Additionally, we provide formulas for the minimizing diagonals of rank one self-adjoint operators, a result that might be applied for numerical large-scale eigenvalue optimization. [1] On minimizing the maximum eigenvalue of a symmetric matrix, SIAM J. Matrix Anal. Appl.9 (1988), no 4, 905-918
title Minimal compact operators, subdifferential of the maximum eigenvalue and semi-definite programming
topic Functional Analysis
Operator Algebras
Primary: 15A60, 47A12, 47B15. Secondary: 47A05, 47A30, 51M15
url https://arxiv.org/abs/2405.08923