Quantum states from normalizing flows

Fuente: arXiv
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Main Authors: Lawrence, Scott, Shelby, Arlee, Yamauchi, Yukari
Format: Preprint
Published: 2024
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author Lawrence, Scott
Shelby, Arlee
Yamauchi, Yukari
author_facet Lawrence, Scott
Shelby, Arlee
Yamauchi, Yukari
contents We introduce an architecture for neural quantum states for many-body quantum-mechanical systems, based on normalizing flows. The use of normalizing flows enables efficient uncorrelated sampling of configurations from the probability distribution defined by the wavefunction, mitigating a major cost of using neural states in simulation. We demonstrate the use of this architecture for both ground-state preparation (for self-interacting particles in a harmonic trap) and real-time evolution (for one-dimensional tunneling). Finally, we detail a procedure for obtaining rigorous estimates of the systematic error when using neural states to approximate quantum evolution.
format Preprint
id arxiv_https___arxiv_org_abs_2406_02451
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum states from normalizing flows
Lawrence, Scott
Shelby, Arlee
Yamauchi, Yukari
Quantum Physics
Nuclear Theory
Computational Physics
We introduce an architecture for neural quantum states for many-body quantum-mechanical systems, based on normalizing flows. The use of normalizing flows enables efficient uncorrelated sampling of configurations from the probability distribution defined by the wavefunction, mitigating a major cost of using neural states in simulation. We demonstrate the use of this architecture for both ground-state preparation (for self-interacting particles in a harmonic trap) and real-time evolution (for one-dimensional tunneling). Finally, we detail a procedure for obtaining rigorous estimates of the systematic error when using neural states to approximate quantum evolution.
title Quantum states from normalizing flows
topic Quantum Physics
Nuclear Theory
Computational Physics
url https://arxiv.org/abs/2406.02451