Machine Learning for Quantum Many-body Physics

February 18, 2022

2022   ·   Quantum     ·   spring-2022  

Speaker

Di Luo Februaru 18, 2022.

Abstract

The study of quantum many-body physics is challenging due to the exponential growing nature of high dimensional Hilbert space. In this talk, I will present recent advancements for simulating quantum many-body physics with neural networks utilizing efficient representation and optimization techniques. Applications to condensed matter physics, high energy physics and quantum information science will be discussed.



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