Finite Temperature Auxiliary Field Quantum Monte Carlo in the Canonical Ensemble
Tong Shen, Yuan Liu, Yang Yu, Brenda Rubenstein

TL;DR
This paper introduces a recursive AFQMC method in the canonical ensemble that eliminates the need for chemical potential tuning, enabling more efficient and direct simulations of many-body quantum systems at fixed particle number.
Contribution
A new recursive approach for AFQMC in the canonical ensemble that does not require chemical potentials, improving efficiency and benchmarking capabilities.
Findings
Converges more quickly to the ground state than grand canonical AFQMC.
Accurately benchmarks Bose and Fermi Hubbard models.
Facilitates direct comparison with other canonical ensemble methods.
Abstract
Finite temperature auxiliary field-based Quantum Monte Carlo methods, including Determinant Quantum Monte Carlo (DQMC) and Auxiliary Field Quantum Monte Carlo (AFQMC), have historically assumed pivotal roles in the investigation of the finite temperature phase diagrams of a wide variety of multidimensional lattice models and materials. Despite their utility, however, these techniques are typically formulated in the grand canonical ensemble, which makes them difficult to apply to condensates like superfluids and difficult to benchmark against alternative methods that are formulated in the canonical ensemble. Working in the grand canonical ensemble is furthermore accompanied by the increased overhead associated with having to determine the chemical potentials that produce desired fillings. Given this backdrop, in this work, we present a new recursive approach for performing AFQMC…
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Taxonomy
TopicsTheoretical and Computational Physics · Quantum many-body systems
