Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States
Abstract
Reducing computational scaling for simulating non-Markovian dissipative dynamics using artificial neural networks is both a major focus and formidable challenge in open quantum systems. To enable neural quantum states (NQSs), we encode environmental memory in dissipatons (quasiparticles with characteristic lifetimes), yielding the dissipaton-embedded quantum master equation (DQME). The resulting NQS-DQME framework achieves compact representation of many-body correlations and non-Markovian memory. Benchmarking against numerically exact hierarchical equations of motion confirms NQS-DQME maintains comparable accuracy while enhancing scalability and interpretability. This methodology opens new paths to explore non-Markovian open quantum dynamics in previously intractable systems.
Cite
@article{arxiv.2404.11093,
title = {Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States},
author = {Long Cao and Liwei Ge and Daochi Zhang and Xiang Li and Yao Wang and Rui-Xue Xu and YiJing Yan and Xiao Zheng},
journal= {arXiv preprint arXiv:2404.11093},
year = {2026}
}