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Estimation of pure quantum states in high dimension at the limit of quantum accuracy through complex optimization and statistical inference.
Zambrano, Leonardo; Pereira, Luciano; Niklitschek, Sebastián; Delgado, Aldo.
Afiliação
  • Zambrano L; Instituto Milenio de Investigación en Óptica, Universidad de Concepción, Concepción, Chile.
  • Pereira L; Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Concepción, Chile.
  • Niklitschek S; Instituto Milenio de Investigación en Óptica, Universidad de Concepción, Concepción, Chile.
  • Delgado A; Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Concepción, Chile.
Sci Rep ; 10(1): 12781, 2020 Jul 29.
Article em En | MEDLINE | ID: mdl-32728142
Quantum tomography has become a key tool for the assessment of quantum states, processes, and devices. This drives the search for tomographic methods that achieve greater accuracy. In the case of mixed states of a single 2-dimensional quantum system adaptive methods have been recently introduced that achieve the theoretical accuracy limit deduced by Hayashi and Gill and Massar. However, accurate estimation of higher-dimensional quantum states remains poorly understood. This is mainly due to the existence of incompatible observables, which makes multiparameter estimation difficult. Here we present an adaptive tomographic method and show through numerical simulations that, after a few iterations, it is asymptotically approaching the fundamental Gill-Massar lower bound for the estimation accuracy of pure quantum states in high dimension. The method is based on a combination of stochastic optimization on the field of the complex numbers and statistical inference, exceeds the accuracy of any mixed-state tomographic method, and can be demonstrated with current experimental capabilities. The proposed method may lead to new developments in quantum metrology.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chile País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chile País de publicação: Reino Unido