Condensed Matter Seminar: "Neural network based machine learning approach to quantum condensed matter"
(sign-up)Eun-Ah Kim, Cornell University
Physics - Condensed Matter
There is rapidly growing interest in using neural network based machine learning to extract physical information out of fluctuating data, be it numerical or experimental. In this talk I will discuss our recent works demonstrating the how one can use neural network based machine learning to speed up acquisition of quantum phase diagram with topological order as well as non-equilibrium phase diagram with many-body localized phases. I will also discuss our recent results on detecting universal features from scanning tunneling microscopy data using neural network based machine learning.
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