Automatic Order Detection and Restoration Through Systematically Improvable Variational Wave Functions

Fuente: arXiv
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Main Authors: Levy, Ryan, Morales, Miguel A., Zhang, Shiwei
Format: Preprint
Published: 2023
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author Levy, Ryan
Morales, Miguel A.
Zhang, Shiwei
author_facet Levy, Ryan
Morales, Miguel A.
Zhang, Shiwei
contents Variational wave function ansatze are an invaluable tool to study the properties of strongly correlated systems. We propose such a wave function, based on the theory of auxiliary fields and combining aspects of auxiliary-field quantum Monte Carlo and modern variational optimization techniques including automatic differentiation. The resulting ansatz, consisting of several slices of optimized projectors, is highly expressive and systematically improvable. We benchmark this form on the two-dimensional Hubbard model, using both cylindrical and large, fully periodic supercells. The computed ground-state energies are competitive with the best variational results. Moreover, the optimized wave functions predict the correct ground-state order with near full symmetry restoration (i.e. translation invariance) despite initial states with incorrect orders. The ansatz can become a tool for local order prediction, leading to a new paradigm for variational studies of bulk systems. It can also be viewed as an approach to produce accurate and systematically improvable wave functions in a convenient form of non-orthogonal Slater determinants (e.g., for quantum chemistry) at polynomial computational cost.
format Preprint
id arxiv_https___arxiv_org_abs_2308_08594
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Automatic Order Detection and Restoration Through Systematically Improvable Variational Wave Functions
Levy, Ryan
Morales, Miguel A.
Zhang, Shiwei
Strongly Correlated Electrons
Computational Physics
Variational wave function ansatze are an invaluable tool to study the properties of strongly correlated systems. We propose such a wave function, based on the theory of auxiliary fields and combining aspects of auxiliary-field quantum Monte Carlo and modern variational optimization techniques including automatic differentiation. The resulting ansatz, consisting of several slices of optimized projectors, is highly expressive and systematically improvable. We benchmark this form on the two-dimensional Hubbard model, using both cylindrical and large, fully periodic supercells. The computed ground-state energies are competitive with the best variational results. Moreover, the optimized wave functions predict the correct ground-state order with near full symmetry restoration (i.e. translation invariance) despite initial states with incorrect orders. The ansatz can become a tool for local order prediction, leading to a new paradigm for variational studies of bulk systems. It can also be viewed as an approach to produce accurate and systematically improvable wave functions in a convenient form of non-orthogonal Slater determinants (e.g., for quantum chemistry) at polynomial computational cost.
title Automatic Order Detection and Restoration Through Systematically Improvable Variational Wave Functions
topic Strongly Correlated Electrons
Computational Physics
url https://arxiv.org/abs/2308.08594