Machine Learning Quantum Many-body Models

Presentations

• Quantum Loop Topography for Machine Learning Transport

  Invited

  March 4, 2019, 2:30 PM – March 4, 2019, 3:06 PM

  Presenters

  • Yi Zhang

    • Cornell University
    • Department of Physics, Cornell University

  Authors

  • Yi Zhang

    • Cornell University
    • Department of Physics, Cornell University

  • Carsten Bauer

    • Institute for Theoretical Physics, University of Cologne

  • Peter Broecker

    • Institute for Theoretical Physics, University of Cologne

  • Paul Ginsparg

    • Department of Physics, Cornell University

  • Simon Trebst

    • Institute for Theoretical Physics, University of Cologne, Germany
    • Institute for Theoretical Physics, University of Cologne
    • Univ Cologne
    • University of Cologne

  • Eun-Ah Kim

    • Cornell University
    • Department of Physics, Cornell University

  View abstract →

• Recent advances in the study of frustrated magnetism with Neural-Network quantum states

  ORAL

  March 4, 2019, 3:06 PM – March 4, 2019, 3:18 PM

  Presenters

  • Giuseppe Carleo

    • Center for Computational Quantum Physics, Flatiron Institute
    • CCQ, Flatiron Institute

  Authors

  • Kenny Choo

    • University of Zurich
    • Physik Institut, University of Zurich

  • Titus Neupert

    • University of Zurich
    • Physics, University of Zurich
    • Physik Institut, University of Zurich

  • Giuseppe Carleo

    • Center for Computational Quantum Physics, Flatiron Institute
    • CCQ, Flatiron Institute

  View abstract →

• Symmetries and Many-Body Excitations with Neural-Network Quantum States

  ORAL

  March 4, 2019, 3:18 PM – March 4, 2019, 3:30 PM

  Presenters

  • Kenny Choo

    • University of Zurich
    • Physik Institut, University of Zurich

  Authors

  • Kenny Choo

    • University of Zurich
    • Physik Institut, University of Zurich

  • Giuseppe Carleo

    • Center for Computational Quantum Physics, Flatiron Institute
    • CCQ, Flatiron Institute

  • Nicolas Regnault

    • Laboratoire Pierre Aigrain, Ecole normale superieure

  • Titus Neupert

    • University of Zurich
    • Physics, University of Zurich
    • Physik Institut, University of Zurich

  View abstract →

• Learning Quantum Models from Symmetries

  ORAL

  March 4, 2019, 3:30 PM – March 4, 2019, 3:42 PM

  Presenters

  • Eli Chertkov

    • University of Illinois at Urbana-Champaign

  Authors

  • Eli Chertkov

    • University of Illinois at Urbana-Champaign

  • Benjamin Villalonga

    • University of Illinois at Urbana-Champaign
    • University of Illinois at Urbana-Champaign - Quantum Artificial Intelligence Lab (QuAIL) @ NASA Ames - USRA Research Institute for Advanced Computer Science (RIACS)

  • Bryan Clark

    • University of Illinois at Urbana-Champaign
    • Physics, University of Illinois at Urbana Champaign
    • Physics, University of Illinois at Urbana-Champaign

  View abstract →

• Parent hamiltonians of restricted Boltzmann machine wavefunctions

  ORAL

  March 4, 2019, 3:42 PM – March 4, 2019, 3:54 PM

  Presenters

  • Samuel Lederer

    • Cornell University

  Authors

  • Samuel Lederer

    • Cornell University

  • Eun-Ah Kim

    • Cornell University
    • Department of Physics, Cornell University

  View abstract →

• Learning a local Hamiltonian from local measurements

  ORAL

  March 4, 2019, 3:54 PM – March 4, 2019, 4:06 PM

  Presenters

  • Eyal Bairey

    • Physics, Technion - Israel Institute of Technology

  Authors

  • Eyal Bairey

    • Physics, Technion - Israel Institute of Technology

  • Itai Arad

    • Physics, Technion - Israel Institute of Technology

  • Netanel Lindner

    • Physics Department, Technion - Israel Institute of Technology
    • Physics, Technion - Israel Institute of Technology
    • Technion - Israel Institute of Technology
    • Physics, Technion – Israel Institute of Technology

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• Accelerating Density Matrix Renormalization Group Computations with Machine Learning

  ORAL

  March 4, 2019, 4:06 PM – March 4, 2019, 4:18 PM

  Presenters

  • Jacob Marks

    • Physics, Stanford University

  Authors

  • Jacob Marks

    • Physics, Stanford University

  • Hong-Chen Jiang

    • Stanford Institute for Materials and Energy Sciences, SLAC and Stanford University
    • SIMES, SLAC, and Stanford University
    • SLAC National Accelerator Laboratory
    • Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory and Stanford University

  • Thomas Devereaux

    • Stanford University
    • Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory
    • SLAC National Accelerator Laboratory
    • Physics, Stanford University
    • SLAC and Stanford University
    • Institute for Materials and Energy Science, Stanford
    • SIMES, SLAC National Accelerator Lab
    • SLAC National Accelerator Laboratory and Stanford University, Stanford Institute for Materials and Energy Sciences
    • SLAC, Stanford
    • SIMES, SLAC, and Stanford University
    • Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory and Stanford University

  View abstract →

• Observation of topological phenomena in a programmable lattice of 1,800 qubits

  ORAL

  March 4, 2019, 4:18 PM – March 4, 2019, 4:30 PM

  Presenters

  • Juan Carrasquilla

    • Vector Institute for Artificial Intelligence, Toronto (Canada)
    • Vector Institute

  Authors

  • Juan Carrasquilla

    • Vector Institute for Artificial Intelligence, Toronto (Canada)
    • Vector Institute

  View abstract →

• Self-learning with neural networks in determinant quantum Monte Carlo studies of the Holstein model.

  ORAL

  March 4, 2019, 4:30 PM – March 4, 2019, 4:42 PM

  Presenters

  • Philip Dee

    • University of Tennessee

  Authors

  • Shaozhi Li

    • Department of Physics and Astronomy, University of Michigan
    • Physics, University of Michigan

  • Philip Dee

    • University of Tennessee

  • Ehsan Khatami

    • Department of Physics and Astronomy, San Jose State Unversity
    • San Jose State University
    • Physics, San Jose State University

  • Steven Johnston

    • Department of Physics and Astronomy, Univ of Tennessee, Knoxville
    • Department of Physics and Astronomy, University of Tennesse
    • Physics and Astronomy, University of Tennessee
    • University of Tennessee
    • Department of Physics and Astronomy, University of Tennessee
    • Department of Physics and Astronomy, University of Tennessee, Knoxville

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• Unsupervised manifold learning of ground state wave functions

  ORAL

  March 4, 2019, 4:42 PM – March 4, 2019, 4:54 PM

  Presenters

  • Michael Matty

    • Cornell University

  Authors

  • Michael Matty

    • Cornell University

  • Yi Zhang

    • Cornell University
    • Department of Physics, Cornell University

  • Senthil Todadri

    • Physics, MIT
    • Massachusetts Institute of Technology
    • Physics, Massachusetts Institute of Technology

  • Eun-Ah Kim

    • Cornell University
    • Department of Physics, Cornell University

  View abstract →

• Machinery representation of physics models via structured self-attention network

  ORAL

  March 4, 2019, 4:54 PM – March 4, 2019, 5:06 PM

  Presenters

  • Junwei Liu

    • Hong Kong University of Science and Technology
    • The Hong Kong University of Science and Technology
    • Department of Physics, Hong Kong University of Science and Technology

  Authors

  • Junwei Liu

    • Hong Kong University of Science and Technology
    • The Hong Kong University of Science and Technology
    • Department of Physics, Hong Kong University of Science and Technology

  • Yang Zhang

    • Max Planck Institute for Chemical Physics of Solids

  • Yujun zhao

    • Hong Kong University of Science and Technology

  View abstract →

• Neural Network Renormalization Group

  ORAL

  March 4, 2019, 5:06 PM – March 4, 2019, 5:18 PM

  Presenters

  • Shuo-Hui Li

    • Institute of Physics, Chinese Academy of Sciences
    • Institute of Physics

  Authors

  • Shuo-Hui Li

    • Institute of Physics, Chinese Academy of Sciences
    • Institute of Physics

  • Lei Wang

    • Institute of Physics
    • Institute of Physics, Chinese Academy of Sciences
    • Institute of Physics Chinese Academy of Sciences

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• Learning density functional theory mappings with extensive deep neural networks and deep convolutional inverse graphics networks

  ORAL

  March 4, 2019, 5:18 PM – March 4, 2019, 5:30 PM

  Presenters

  • Kevin Ryczko

    • Department of Physics, University of Ottawa

  Authors

  • Kevin Ryczko

    • Department of Physics, University of Ottawa

  • David Strubbe

    • University of California, Merced
    • Department of Physics, University of California, Merced
    • Physics, University of California, Merced

  • Isaac Tamblyn

    • University of Ontario Institute of Technology, University of Ottawa, and National Research Council of Canada
    • University of Ontario Institute of Technology, National Research Council of Canada
    • National Research Council of Canada

  View abstract →