Quantum mean-field approximation for lattice quantum models: truncating quantum correlations, and retaining classical ones
Daniele Malpetti, Tommaso Roscilde

TL;DR
This paper introduces the quantum mean-field (QMF) approximation for lattice quantum models, which selectively truncates quantum correlations while preserving classical correlations, enabling systematic semi-classical analysis of quantum many-body systems.
Contribution
The authors develop a novel quantum mean-field approach that isolates quantum correlations, providing a systematic, temperature-dependent approximation for lattice quantum models.
Findings
QMF captures thermal critical phenomena accurately at any cluster size.
Convergence of cQMF towards exact results is linear or sub-linear at low T, faster at higher T.
Systematic improvement of approximations enables semi-classical numerical methods.
Abstract
In a recent work [D. Malpetti and T. Roscilde, arXiv:1605.04223] we have shown that in quantum many-body systems at finite temperature, two-point correlations can be formally separated into a thermal part, and a quantum part -- and that generically quantum correlations decay exponentially at finite temperature, with a characteristic, temperature-dependent quantum coherence length. The existence of these two different forms of correlation in quantum many-body systems suggests the possibility of formulating an approximation which affects quantum correlations only, without preventing the correct description of classical fluctuations at all length scales. Focusing on lattice boson and quantum Ising models, we make use of the path-integral formulation of quantum statistical mechanics to introduce such an approximation -- that we dub \emph{quantum mean-field} (QMF) approach, and which can be…
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