Local solutions of maximum likelihood estimation in quantum state tomography

Douglas S. Gonçalves, Márcia A. Gomes-Ruggiero, Carlile Lavor, Osvaldo Jiménez Farías, P. H. Souto Ribeiro

Producció científica: Article en revista indexadaArticleAvaluat per experts

12 Cites (Scopus)


Maximum likelihood estimation is one of the most used methods in quantum state tomography, where the aim is to reconstruct the density matrix of a physical system from measurement results. One strategy to deal with positivity and unit trace constraints is to parameterize the matrix to be reconstructed in order to ensure that it is physical. In this case, the negative log-likelihood function in terms of the parameters, may have several local minima. In various papers in the field, a source of errors in this process has been associated to the possibility that most of these local minima are not global, so that optimization methods could be trapped in the wrong minimum, leading to a wrong density matrix. Here we show that, for convex negative log-likelihood functions, all local minima of the unconstrained parameterized problem are global, thus any minimizer leads to the maximum likelihood estimation for the density matrix. We also discuss some practical sources of errors.

Idioma originalAnglès
Pàgines (de-a)775-790
Nombre de pàgines16
RevistaQuantum Information and Computation
Estat de la publicacióPublicada - 1 de set. 2012
Publicat externament


Navegar pels temes de recerca de 'Local solutions of maximum likelihood estimation in quantum state tomography'. Junts formen un fingerprint únic.

Com citar-ho