chevron-down--small
Simons Foundation chevron-down--small
CCQ
CCQ

Machine Learning and Quantum Many-Body Physics

  • Organized by
  • Portrait photo of Giuseppe CarleoGiuseppe Carleo, Ph.D.Assistant Professor, École Polytechnique
    Research Scientist, CCQ (2018-2020), Flatiron Institute
  • Portrait photo of Miles StoudenmireMiles Stoudenmire, Ph.D.Research Scientist, CCQ, Flatiron Institute
Date & Time


This workshop brings together a small number of researchers from quantum physics; condensed matter physics; machine learning; and computer science to discuss applications of machine learning tools and methods to challenging problems in many-body physics, and how ideas from quantum many-body could be applied to machine learning.

  • Thursday, April 26

    8:00 - 9:00 AM
    		Breakfast
    9:00 - 9:10 AMGiuseppe Carleo, Miles StoudenmireWelcome and Introduction
    Morning Session
    9:15 - 9:40 AMRoger Melko (University of Waterloo)Research at Perimeter’s Quantum Intelligence Lab
    9:40 - 10:05 AMLei Wang (Chinese Academy of Science)Neural Network Renormalization Group
    10:05 - 10:30 AMIvan Glasser (Max Planck Institute of Quantum Optics)Duality between neural networks and tensor networks with applications to chiral topological states and supervised learning
    10:30 - 11:00 AMBreak
    11:00 - 11:30 AMDiscussion
    11:30 - 11:55 AMDries Sels (Boston University)Reinforcement learning quantum optimal control
    11:55 - 12:20 PMDong Ling Deng (University of Maryland)Measuring Quantum Entanglement Entropy through Restricted Boltzmann Machine
    12:20- 12:45 PMTitus Neupert (University of Zurich)Neural networks for quantum many-body calculations: Including Symmetries and reaching excited states
    12:45 - 2:45 PM Lunch and Discussion
    Afternoon Session
    2:45 - 3:10 PMMasatoshi Imada (University of Tokyo)Boltzmann machine for quantum ground states and hidden-structure analyses of experimental data
    3:10 - 3:35 PMGiacomo Torlai (University of Waterloo)Neural-network quantum state tomography
    3:35 - 4:00 PMMarkus Heyl (Max Planck Inst. for the Physics of Complex Systems)Quantum dynamics with classical networks and machine learning
    4:00- 4:45 PMBreak and Discussion
    4:45 - 5:30 PMHot Topics- Jan Budich Lode Pollet, Steven Clark, Andrea Rocchetto
    5:30 - 6:30 PMPosters

    Friday, April 27

    8:00 - 9:00 AM
    		Breakfast
    Morning Session
    9:00 - 9:25 AMSimon Trebst (University of Cologne)Quantum phase recognition
    9:25 - 9:50 AMEun-Ah Kim (Cornell University)Learning Quantum Emergence with AI
    9:50 - 10:15 AMKyle Cranmer (New York University)Quantum Inference
    10:15 - 11:15 AMBreak and Discussion
    11:15 - 11:40 PMYoav Levine (The Hebrew University of Jerusalem)Bridging Many-Body Physics and Deep Learning via Tensor Networks
    11:40 - 12:05 PMEvert van Nieuwenberg (California Institute of Technology)Learning a phase diagram from dynamics
    12:05 - 12:30 PMJuan Carrasquilla (Vector Institute)Toward learning quantum states with generative models
    12:30 - 3:00 PMLunch, Discussion and Departure
Advancing Research in Basic Science and MathematicsSubscribe to Flatiron Institute announcements and other foundation updates