Neural network modeling of many-body super- and sub-radiant dynamics

Fuente: arXiv
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Main Authors: Lagnese, Gianluca, Brunner, Laurin, Rossi, Lorenzo, Chang, Darrick, Schmitt, Markus, Lenarčič, Zala
Format: Preprint
Published: 2026
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author Lagnese, Gianluca
Brunner, Laurin
Rossi, Lorenzo
Chang, Darrick
Schmitt, Markus
Lenarčič, Zala
author_facet Lagnese, Gianluca
Brunner, Laurin
Rossi, Lorenzo
Chang, Darrick
Schmitt, Markus
Lenarčič, Zala
contents There is significant interest in exploring novel phenomena in quantum light-matter interfaces, which are driven by the combination of structured dissipation and long-range interactions that are typical in such systems. To this end, it is important to develop new general numerical simulation techniques, which can access large system sizes and are not based on semi-classical approaches. Here, we report the first application of neural quantum states to obtain the dissipative dynamics of light-matter-coupled systems beyond what is accessible with exact and tensor-network calculations. We specifically apply this method to simulate the many-body emission dynamics of approximately 40 atoms, arranged in dense arrays in one and two dimensions. These systems have been chosen because they can support prominent subradiant dynamics at late times and could be realized with cold atomic quantum simulators.
format Preprint
id arxiv_https___arxiv_org_abs_2605_04640
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Neural network modeling of many-body super- and sub-radiant dynamics
Lagnese, Gianluca
Brunner, Laurin
Rossi, Lorenzo
Chang, Darrick
Schmitt, Markus
Lenarčič, Zala
Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Strongly Correlated Electrons
There is significant interest in exploring novel phenomena in quantum light-matter interfaces, which are driven by the combination of structured dissipation and long-range interactions that are typical in such systems. To this end, it is important to develop new general numerical simulation techniques, which can access large system sizes and are not based on semi-classical approaches. Here, we report the first application of neural quantum states to obtain the dissipative dynamics of light-matter-coupled systems beyond what is accessible with exact and tensor-network calculations. We specifically apply this method to simulate the many-body emission dynamics of approximately 40 atoms, arranged in dense arrays in one and two dimensions. These systems have been chosen because they can support prominent subradiant dynamics at late times and could be realized with cold atomic quantum simulators.
title Neural network modeling of many-body super- and sub-radiant dynamics
topic Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Strongly Correlated Electrons
url https://arxiv.org/abs/2605.04640