Princeton University Machine Learning in Physics

In this talk, I will discuss our work on using models inspired by natural language processing in the realm of many-body physics. Specifically, I will demonstrate their utility in reconstructing quantum states and simulating the real-time dynamics of open quantum systems. Finally, I will show the efficacy of using these models for combinatorial optimization, yielding solutions of high accuracy compared to traditional simulated and simulated quantum annealing methods.