Simulating many-body open quantum systems eases with computational advances

Simulating many-body open quantum systems (OQSs), which show up in physics, biology, chemistry, and materials science, is immensely challenging due to complex spatial and temporal quantum correlations. Yet these simulations are essential for understanding molecules in condensed phases and are key to advancing important technologies such as thermoelectric transport in nanodevices, molecular spectroscopies, quantum computing, and quantum sensing.

Ye et al. discussed simulating OQSs with artificial intelligence and quantum computing with the aim of encouraging more researchers to explore and advance the field’s frontier. With the advancement of AI and quantum computing, researchers now have the tools to overcome OQS’s “exponential wall problem”, where the computational cost of simulating such systems grows exponentially with the size of the system and the complexity of the environment.

“I am particularly excited about the future of this field due to the emergence of new theoretical methods driven by advancing technologies,” said author Xiao Zheng. “Looking ahead to the next decade, if AI and quantum computers become more widely applied, we will have the opportunity to explore systems that were previously inaccessible and address scientific problems that have long been challenging.”

The authors covered new trends in simulating OQSs and comprehensively reviewed literature on the topic. They also discussed recent simulation developments and approaches, including a theoretical framework called the dissipation-embedded quantum master equation, which can model quantum states by using neural networks or qubits.

The authors hope to bring more attention to the topic as well as help researchers tackle challenging problems involving both many-body correlations and system-environment interactions.

Source: “Simulating many-body open quantum systems by harnessing the power of artificial intelligence and quantum computing,” by Lyuzhou Ye, Yao Wang, and Xiao Zheng, Journal of Chemical Physics (2025). The article can be accessed at https://doi.org/10.1063/5.0242648 .