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Monday, February 12, 2018 at 4:00pm to 5:00pm
Rockefeller Hall, Schwartz Auditorium
Central Campus
General Physics Colloquium, Professor Eun-Ah Kim, Cornell
Refreshments from 3:30-3:50 pm
Title: With AI, Learning Quantum Emergence
Host: Paul Ginsparg
Abstract: The application of artificial neural network based machine learning to central questions in the theory of quantum matter is a rapidly developing field. Efforts focus on representing many-body states compactly through artificial neural networks and on identifying and classifying different phases of matter. The driving insight here is that the problems of theoretical interests are primarily those of regression in which an exponentially large volume of data must be condensed into a more accessible or meaningful form, e.g., labeled with phases. In this talk, I will review the state of this rapidly developing field. I will then showcase how my group built and taught neural networks to recognize topological phases, different non-equilibrium phases and universal features from scanning tunneling microscopy data. I will then discuss new insights from the synergy between human intelligence and artificial intelligence: the key to our success.
Sue Sullivan
607/255-7562
Professor Eun-Ah Kim
Cornell University
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