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

TL;DR

This paper introduces a neural quantum states approach to simulate large-scale many-body light-matter systems, capturing complex super- and sub-radiant dynamics beyond traditional methods.

Contribution

It is the first to apply neural quantum states to dissipative light-matter systems, enabling simulation of larger systems with complex quantum phenomena.

Findings

Successfully simulated ~40 atoms in dense arrays in 1D and 2D.

Captured prominent subradiant dynamics at late times.

Demonstrated the method's potential for quantum simulation of large systems.

Abstract

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.