Victor E. Colussi, Fabio Caleffi, Chiara Menotti, Alessio Recati
SciPost Phys. 12, 111 (2022) ·
published 29 March 2022
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We study the effects of quantum fluctuations in the two-component
Bose-Hubbard model generalizing to mixtures the quantum Gutzwiller approach
introduced recently in [Phys. Rev. Research 2, 033276 (2020)]. As a basis for
our study, we analyze the mean-field ground-state phase diagram and spectrum of
elementary excitations, with particular emphasis on the quantum phase
transitions of the model. Within the quantum critical regimes, we address both
the superfluid transport properties and the linear response dynamics to density
and spin probes of direct experimental relevance. Crucially, we find that
quantum fluctuations have a dramatic effect on the drag between the superfluid
species of the system, particularly in the vicinity of the paired and
antipaired phases absent in the usual one-component Bose-Hubbard model.
Additionally, we analyse the contributions of quantum corrections to the
one-body coherence and density/spin fluctuations from the perspective of the
collective modes of the system, providing results for the few-body correlations
in all the regimes of the phase diagram.
SciPost Phys. 12, 107 (2022) ·
published 25 March 2022
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The detection of phase transitions in quantum many-body systems with lowest
possible prior knowledge of their details is among the most rousing goals of
the flourishing application of machine-learning techniques to physical
questions. Here, we train a Generative Adversarial Network (GAN) with the
Entanglement Spectrum of a system bipartition, as extracted by means of Matrix
Product States ans\"atze. We are able to identify gapless-to-gapped phase
transitions in different one-dimensional models by looking at the machine
inability to reconstruct outsider data with respect to the training set. We
foresee that GAN-based methods will become instrumental in anomaly detection
schemes applied to the determination of phase-diagrams.
