Gauge Equivariant Neural Networks for Quantum Lattice Gauge Theories

Gauge symmetries play a key role in physics appearing in areas such as quantum field theories of the fundamental particles and emergent degrees of freedom in quantum materials. Motivated by the desire to efficiently simulate many-body quantum systems with exact local gauge invariance, gauge equivariant neural-network quantum states are introduced, which exactly satisfy the local Hilbert space constraints necessary for the description of quantum lattice gauge theory with Z_{d} gauge group and non-Abelian Kitaev D(G) models on different geometries. Focusing on the special case of Z_{2} gauge group on a periodically identified square lattice, the equivariant architecture is analytically shown to contain the loop-gas solution as a special case. Gauge equivariant neural-network quantum states are used in combination with variational quantum Monte Carlo to obtain compact descriptions of the ground state wave function for the Z_{2} theory away from the exactly solvable limit, and to demonstrate the confining or deconfining phase transition of the Wilson loop order parameter.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:127

Enthalten in:

Physical review letters - 127(2021), 27 vom: 31. Dez., Seite 276402

Sprache:

Englisch

Beteiligte Personen:

Luo, Di [VerfasserIn]
Carleo, Giuseppe [VerfasserIn]
Clark, Bryan K [VerfasserIn]
Stokes, James [VerfasserIn]

Links:

Volltext

Themen:

Journal Article

Anmerkungen:

Date Revised 24.01.2022

published: Print

Citation Status PubMed-not-MEDLINE

doi:

10.1103/PhysRevLett.127.276402

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM335960286