Sparse noncommutative polynomial optimization
نویسندگان
چکیده
This article focuses on optimization of polynomials in noncommuting variables, while taking into account sparsity the input data. A converging hierarchy semidefinite relaxations for eigenvalue and trace is provided. a noncommutative analogue results due to Lasserre [SIAM J. Optim. 17(3) (2006), pp. 822--843] Waki et al. 17(1) 218--242]. The Gelfand-Naimark-Segal (GNS) construction applied extract optimizers if flatness irreducibility conditions are satisfied. Among main techniques used amalgamation from operator algebra. theoretical utilized compute lower bounds minimal literature.
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2021
ISSN: ['0025-5610', '1436-4646']
DOI: https://doi.org/10.1007/s10107-020-01610-1