Simulating many-body open quantum systems by harnessing the power of artificial intelligence and quantum computing

Simulating many-body open quantum systems (OQSs) is challenging due to the intricate interplay between the system and its environment, resulting in strong quantum correlations in both space and time. This Perspective presents an overview of recently developed theoretical methods using artificial intelligence (AI) and quantum computing (QC) to simulate the dynamics of these systems. We briefly introduce the dissipaton-embedded quantum master equation in second quantization, which provides a single master equation suitable for representation by neural quantum states or quantum circuits. The promising performance of AI- and QC-based approaches is demonstrated through preliminary research on simulating the quantum dissipative dynamics of many-body OQSs. We also discuss the limitations and future developments of these methods, which hold promise for overcoming the computational challenges associated with many-body OQS dynamics.

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Institutions

Publication Details

Journal
The Journal of Chemical Physics
Published
2025-03-24
DOI
https://doi.org/10.1063/5.0242648
Citations
3
Primary Topic
Quantum many-body systems
Type
article
Field-Weighted Citation Impact
3.74

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article

Simulating many-body open quantum systems by harnessing the power of artificial intelligence and quantum computing

Yao Wang, Xiao Zheng, Lyuzhou Ye
3 citations
The Journal of Chemical Physics
Quantum many-body systems
3.74
article

Simulating many-body open quantum systems by harnessing the power of artificial intelligence and quantum computing

Yao Wang, Xiao Zheng, Lyuzhou Ye
article en
3 citations

Abstract

Simulating many-body open quantum systems (OQSs) is challenging due to the intricate interplay between the system and its environment, resulting in strong quantum correlations in both space and time. This Perspective presents an overview of recently developed theoretical methods using artificial intelligence (AI) and quantum computing (QC) to simulate the dynamics of these systems. We briefly introduce the dissipaton-embedded quantum master equation in second quantization, which provides a single master equation suitable for representation by neural quantum states or quantum circuits. The promising performance of AI- and QC-based approaches is demonstrated through preliminary research on simulating the quantum dissipative dynamics of many-body OQSs. We also discuss the limitations and future developments of these methods, which hold promise for overcoming the computational challenges associated with many-body OQS dynamics.

The Journal of Chemical PhysicsVol. 162(12)
University of Science and Technology of China (CN), Fudan University (CN), Hefei University (CN), Hefei National Center for Physical Sciences at Nanoscale (CN)
National Natural Science Foundation of China
Partnerships for the goals
Openalex Percentile: Top 8%
Quantum many-body systems
3.74
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