Machine Learning for Quantum Simulation: Virtual Conference

  • 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
Date & Time



Conference Dates:

June 22-23, 2020 and

June 29-20, 2020

All participants are strongly encouraged to register.

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.

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  • Invited Speakersplus--large

    Current list of confirmed speakers. More will be added at a later time.

    Ryan BabbushGoogle
    Federico BeccaUniversity of Trieste
    George Booth King's College London
    Roberto CarPrinceton University
    Juan Felipe CarrasquillaVector Institute
    Kenny ChooUniversity of Zurich
    Weinan EPrinceton University
    Sophia EconomouVirginia Tech
    Markus HeylMax-Planck-Institute for the Physics of Complex Systems
    Markus HolzmannLaboratoire de Physique Théorique de la Matière Condensée
    Antonio MezzacapoIBM
    Frank NoeFreie Universitaet Berlin
    Marivi Fernandez Serra Stony Brook University
    Sandro SorellaScuola Internazionale Superiore di Studi Avanzati
    James SpencerDeepMind
    Frank VerstraeteUniversity of Vienna
    Nobuyuki YoshiokaUniversity of Tokyo
    Pan ZhangChinese Academy of Sciences
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