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Master's Dissertation
DOI
https://doi.org/10.11606/D.43.2011.tde-27022012-085711
Document
Author
Full name
Karine Piacentini Coelho da Costa
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2011
Supervisor
Committee
Gammal, Arnaldo (President)
Martinelli, Marcelo
Yamashita, Marcelo Takeshi
Title in Portuguese
Estudo do modelo de Bose-Hubbard usando o algoritmo Worm
Keywords in Portuguese
Condensados de Bose-Einstein em redes óticas
Modelo de Bose-Hubbard
Transição superfluido - isolante de Mott
Abstract in Portuguese
Nesta dissertação estudaremos sistemas de bósons ultrafrios armadilhados em uma rede ótica quadrada bidimensional sem levar em consideração o confinamento harmônico. A dinâmica desses sistemas é bem descrita pelo modelo de Bose-Hubbard, que prevê uma transição de fase quântica de um superfluido para um isolante de Mott a temperaturas baixas, e pode ser induzida variando a profundidade do potencial da rede ótica. Apresentaremos o diagrama de fases dessa transição construído a partir de uma aproximação de campo médio e também com um cálculo numérico usando um algoritmo de Monte Carlo Quântico, denominado algoritmo Worm. Encontramos o ponto crítico para o primeiro lobo de Mott em ambos os casos, concordando com trabalhos anteriores.
Title in English
Study of the Bose-Hubbard model using the Worm algorithm
Keywords in English
Bose-Einstein Condensation in a square optical lattice
Bose-Hubbard model
Superfluid to Mott-insulator phase transition
Abstract in English
This work study the two-dimensional ultracold bosonic atoms loaded in a square optical lattice, without harmonic confinement. The dynamics of this system is described by the Bose-Hubbard model, which predicts a quantum phase transition from a superfluid to a Mott-insulator at low temperatures that can be induced by varying the depth of the optical potential. We present here the phase diagram of this transition built from a mean field approach and from a numerical calculation using a Quantum Monte Carlo algorithm, namely the Worm algorithm. We found the critical transition point for the first Mott lobe in both cases, in agreement with the standard literature.
 
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CostaKarine.pdf (840.55 Kbytes)
Publishing Date
2012-05-21
 
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