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arXiv · 2404.11093

Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States

Long Cao·Liwei Ge·Daochi Zhang·Xiang Li·Yao Wang·Rui-Xue Xu·YiJing Yan·Xiao Zheng
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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.

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Long Cao, Liwei Ge, Daochi Zhang, Xiang Li, Yao Wang, Rui-Xue Xu, YiJing Yan, Xiao Zheng. 2024-04-17. Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States. https://arxiv.org/abs/2404.11093

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