QIQB Seminar (15:00~ 9th Oct): Prof. Titus Neupert "Applications of machine learning in condensed matter physics"
Machine learning is not only prominent in big data processing, affecting many aspects of our daily life, it also becomes an increasingly popular addition to the toolbox of scientists. In my talk I will discuss several applications of ideas from machine learning to condensed matter and (quantum) statistical physics by ways of examples. I will start with more conventional supervised classification approaches and show how they can be enriched by unsupervised elements to detect phases of matter, based on experimental or numerical data. In the second part of my talk, I will introduce the concept of neural network quantum states as trail wave functions to variationally solve quantum many-body problems. As benchmark examples I will discuss the one-dimensional Heisenberg and Bose-Hubbard models as well as the J1-J2 model on the two-dimensional square lattice. I will close with a brief mention of machine learning applications for the IBM quantum computer.