Artículo
MaxEnt principle and reduced density matrix estimation
Fecha de publicación:
08/2022
Editorial:
Elsevier Science
Revista:
Physica A: Statistical Mechanics and its Applications
ISSN:
0378-4371
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
In this work we study the reduced density matrices of sublattices of fermionic, bosonic and spin lattice models. Firstly, we consider fermionic and bosonic lattice models, and we show that the reduced density matrix associated with a sublattice coincides with the state obtained by applying the maximum entropy principle under suitably chosen constraints. Secondly, for informationally incomplete scenarios, we considered spin lattice models. We study the performance of the MaxEnt method for estimating the reduced density matrix of sublattices of the lattice system. We find that the performance of the MaxEnt estimation improves not only with the number of measured observables (as expected), but also with the lattice length. In these cases, the MaxEnt solution can be considered, not as an exact solution, but as a good estimator.
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Articulos(CCT - CORDOBA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos(IFLP)
Articulos de INST.DE FISICA LA PLATA
Articulos de INST.DE FISICA LA PLATA
Citación
Losada, Marcelo Adrián; Penas, Victor Alejandro; Holik, Federico Hernán; Lamberti, Pedro Walter; MaxEnt principle and reduced density matrix estimation; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 600; 8-2022; 1-9
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