- Organized by
Giuseppe Carleo, Ph.D.Research Scientist, CCQ, Flatiron Institute
Andrew Millis, Ph.D.CCQ Co-Director, Flatiron Institute
David Ceperley, Ph.D.University of Illinois at Urbana-Champaign
This virtual conference brings together the fast-growing community of researchers from condensed matter physics, quantum computing, quantum chemistry, and computer science working on the development of machine learning methods to study challenging problems in many-body quantum science.
Topics will include: Neural-network quantum states; Dynamics of many-body quantum systems; Tomography and characterization of quantum machines; Variational Algorithms on Quantum Hardware; Stochastic Optimization in Quantum Monte Carlo methods; ML-enhanced Density Functional Theory. The conference will also feature a session introducing the open-source NetKet software and selected applications.
Current list of confirmed speakers. More will be added at a later time.
Ryan Babbush Federico Becca University of Trieste George Booth King's College London Roberto Car Princeton University Juan Felipe Carrasquilla Vector Institute Kenny Choo University of Zurich Weinan E Princeton University Sophia Economou Virginia Tech Markus Heyl Max-Planck-Institute for the Physics of Complex Systems Markus Holzmann Laboratoire de Physique Théorique de la Matière Condensée Antonio Mezzacapo IBM Frank Noe Freie Universitaet Berlin Marivi Fernandez Serra Stony Brook University Sandro Sorella Scuola Internazionale Superiore di Studi Avanzati James Spencer DeepMind Frank Verstraete University of Vienna Nobuyuki Yoshioka University of Tokyo Pan Zhang Chinese Academy of Sciences