Quantum Phases and Collective Excitations in Bose-Hubbard Models with Staggered Magnetic Flux

We study the quantum phases of a Bose-Hubbard model with staggered magnetic flux in two dimensions, as has been realized recently [Aidelsburger {\it et al.}, PRL, {\bf 107}, 255301 (2011)]. Within mean field theory, we show how the structure of the condensates evolves from weak to strong coupling limit, exhibiting a tricritical point at the Mott-superfluid transition. Non-trivial topological structures (Dirac points) in the quasi-particle (hole) excitations in the Mott state are found within random phase approximation and we discuss how interaction modifies their structures. Excitation gap in the Mott state closes at different ${\bf k}$ points when approaching the superfluid states, which is consistent with the findings of mean field theory.Comment: 5 pages, 3 figure

A comparison of the accuracy of saddlepoint conditional cumulative distribution function approximations

Consider a model parameterized by a scalar parameter of interest and a nuisance parameter vector. Inference about the parameter of interest may be based on the signed root of the likelihood ratio statistic R. The standard normal approximation to the conditional distribution of R typically has error of order O(n^{-1/2}), where n is the sample size. There are several modifications for R, which reduce the order of error in the approximations. In this paper, we mainly investigate Barndorff-Nielsen's modified directed likelihood ratio statistic, Severini's empirical adjustment, and DiCiccio and Martin's two modifications, involving the Bayesian approach and the conditional likelihood ratio statistic. For each modification, two formats were employed to approximate the conditional cumulative distribution function; these are Barndorff-Nielson formats and the Lugannani and Rice formats. All approximations were applied to inference on the ratio of means for two independent exponential random variables. We constructed one and two-sided hypotheses tests and used the actual sizes of the tests as the measurements of accuracy to compare those approximations.Comment: Published at http://dx.doi.org/10.1214/074921707000000193 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org