Juan Carrasquilla: "Simulating quantum dynamics with neural machine translation"
Machine Learning for Physics and the Physics of Learning 2019
Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics
"Simulating quantum dynamics with neural machine translation"
Juan Carrasquilla - Vector Institute
Abstract: I will present a heuristic to simulate quantum circuits based on a probabilistic representation of the quantum state as the outcome distribution of a positive operator valued measure. In this language, unitary evolution translates into evolution of probability distributions subject to "somewhat" stochastic matrices, which are a generalization of stochastic matrices. I approximate the evolution of the quantum state using recurrent neural networks and transformers and provide a proof-of-principle demonstration of the approach on simple quantum circuits.
Institute for Pure and Applied Mathematics, UCLA
September 27, 2019
For more information: http://www.ipam.ucla.edu/mlpws1
