AI-enhanced Quantum Simulation of Schwinger Model

The Schwinger Model from Quantum Electrodynamics (QED) has long served as a valuable simplified model for exploring key physical phenomena in Quantum Chromodynamics (QCD)-a field rich with fundamental insights but is substantially more complex. While the phase diagram of the Schwinger Model bears extraordinary significance and remains challenging to investigate, recent progress on the model mainly focuses on detailed case studies. Here, we propose a model that we refer as the Neural Network Facilitated Implicit Quantum Simulation (NN-IQS) model as a solution. After training on limited discrete data points on the Schwinger Model phase diagram, the NN-IQS model allows quick generation of extra sample points over a continuous domain. The model can even generalize beyond its training range, maintaining robust performance in previously unexplored parameter space and system sizes.

Publication Details

Journal
ArXiv.org
Published
2025-09-24
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
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article

AI-enhanced Quantum Simulation of Schwinger Model

ArXiv.org
Image Processing and 3D Reconstruction
article

AI-enhanced Quantum Simulation of Schwinger Model

article en

Abstract

The Schwinger Model from Quantum Electrodynamics (QED) has long served as a valuable simplified model for exploring key physical phenomena in Quantum Chromodynamics (QCD)-a field rich with fundamental insights but is substantially more complex. While the phase diagram of the Schwinger Model bears extraordinary significance and remains challenging to investigate, recent progress on the model mainly focuses on detailed case studies. Here, we propose a model that we refer as the Neural Network Facilitated Implicit Quantum Simulation (NN-IQS) model as a solution. After training on limited discrete data points on the Schwinger Model phase diagram, the NN-IQS model allows quick generation of extra sample points over a continuous domain. The model can even generalize beyond its training range, maintaining robust performance in previously unexplored parameter space and system sizes.

ArXiv.org
Openalex Percentile: Top 46%
Image Processing and 3D Reconstruction
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AI-enhanced Quantum Simulation of Schwinger Model · ArXiv.org (2025) | TGRS Research Map | TGRS