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Sparse noncommutative polynomial optimizationKlep, Igor, matematik ; Magron, Victor ; Povh, Janez, 1973-This article focuses on optimization of polynomials in noncommuting variables, while taking into account sparsity in the input data. A converging hierarchy of semidefinite relaxations for eigenvalue ... and trace optimization is provided. This hierarchy is a noncommutative analogue of results due to Lasserre (SIAM J Optim 17(3):822-843, 2006) and Waki et al. (SIAM J Optim 17(1):218-242, 2006). The Gelfand-Naimark-Segal construction is applied to extract optimizers if flatness and irreducibility conditions are satisfied. Among the main techniques used are amalgamation results from operator algebra. The theoretical results are utilized to compute lower bounds on minimal eigenvalue of noncommutative polynomials from the literature.Source: Mathematical programming. - ISSN 0025-5610 (Vol. 193, iss. 2, June 2022, str. 789–829)Type of material - article, component part ; adult, seriousPublish date - 2022Language - englishCOBISS.SI-ID - 49537283
Author
Klep, Igor, matematik |
Magron, Victor |
Povh, Janez, 1973-
Topics
noncommutative polynomial |
sparsity pattern |
semialgebraic set |
semidefinite programming |
eigenvalue optimization |
trace optimization |
GNS construction |
nekomutativni polinom |
redki polinomi |
semialgebraična množica |
semidefinitno programiranje |
optimizacija lastnih vrednosti |
optimizacija sledi |
GNS postopek
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Klep, Igor, matematik | 22353 |
Magron, Victor | |
Povh, Janez, 1973- | 22649 |
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