Machine Learning for Quantum Matter I

Presentations

• Classifying Snapshots of the Doped Hubbard Model with Machine Learning

  Invited

  March 4, 2020, 8:00 AM – March 4, 2020, 8:36 AM

  Presenters

  • Annabelle Bohrdt

    • Tech Univ Muenchen
    • Department of Physics and Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany

  Authors

  • Annabelle Bohrdt

    • Tech Univ Muenchen
    • Department of Physics and Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany

  • Christie S. Chiu

    • Physics Department, Harvard University

  • Geoffrey Ji

    • Physics Department, Harvard University

  • Muqing Xu

    • Physics Department, Harvard University

  • Daniel Greif

    • Physics Department, Harvard University

  • Markus Greiner

    • Physics Department, Harvard University
    • Harvard University

  • Eugene Demler

    • Harvard University
    • Physics Department, Harvard University

  • Fabian Grusdt

    • Physics Department, Ludwig-Maximilians-Universität München
    • Tech Univ Muenchen
    • Department of Physics, Technical University Munich

  • Michael Knap

    • TU Munich
    • Department of Physics, Technical University of Munich
    • Technical University of Munich
    • Tech Univ Muenchen
    • Department of Physics and Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany

  View abstract →

• AI Assisted Discovery in Quantum Gas Microscope Images

  ORAL

  March 4, 2020, 8:36 AM – March 4, 2020, 8:48 AM

  Presenters

  • Ehsan Khatami

    • San Jose State University

  Authors

  • Elmer Guardado-Sanchez

    • Princeton University

  • Benjamin M Spar

    • Princeton University

  • Juan Carrasquilla

    • Vector Institute
    • Vector Institute for Artificial Intelligence

  • Richard Theodore Scalettar

    • University of California, Davis
    • Physics, UC Davis
    • UC Davis

  • Waseem S Bakr

    • Princeton University
    • Princeton

  • Ehsan Khatami

    • San Jose State University

  View abstract →

• Unsupervised machine learning of topological phase transitions

  ORAL

  March 4, 2020, 8:48 AM – March 4, 2020, 9:00 AM

  Presenters

  • Mathias Scheurer

    • Department of Physics, Harvard University, Cambridge, MA 02138, USA
    • Harvard University
    • Department of Physics, Harvard University

  Authors

  • Joaquin Rodriguez Nieva

    • Stanford University
    • Department of Physics, Harvard University

  • Mathias Scheurer

    • Department of Physics, Harvard University, Cambridge, MA 02138, USA
    • Harvard University
    • Department of Physics, Harvard University

  View abstract →

• Classification of optical quantum states using machine learning

  ORAL

  March 4, 2020, 9:00 AM – March 4, 2020, 9:12 AM

  Presenters

  • Shahnawaz Ahmed

    • MC2, Chalmers University of Technology

  Authors

  • Shahnawaz Ahmed

    • MC2, Chalmers University of Technology

  • Carlos Sánchez Muñoz

    • Physics, Oxford University
    • Oxford University

  • Franco Nori

    • RIKEN
    • Theoretical Quantum Physics, Riken

  • Anton Frisk Kockum

    • Chalmers Univ of Tech
    • Department of Microtechnology and Nanoscience, Chalmers University of Technology
    • MC2, Chalmers University of Technology

  View abstract →

• Unsupervised learning of quantum phase transitions using nonlinear dimension reduction methods

  ORAL

  March 4, 2020, 9:12 AM – March 4, 2020, 9:24 AM

  Presenters

  • Alexander Lidiak

    • Physics, Colorado School of Mines

  Authors

  • Alexander Lidiak

    • Physics, Colorado School of Mines

  • Zhexuan Gong

    • Physics, Colorado School of Mines
    • Colorado School of Mines

  View abstract →

• Machine learning the Mattis glass transformation

  ORAL

  March 4, 2020, 9:24 AM – March 4, 2020, 9:36 AM

  Presenters

  • Daniel Lozano-Gomez

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

  Authors

  • Daniel Lozano-Gomez

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

  • Darren Pereira

    • University of Waterloo

  • Michel J P Gingras

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

  View abstract →

• Augmenting machine learning algorithms with the addition of a physics based intelligence prior

  ORAL

  March 4, 2020, 9:36 AM – March 4, 2020, 9:48 AM

  Presenters

  • Christopher Singh

    • Binghamton University
    • Physics, Binghamton University
    • Physics, Applied Physics, and Astronomy, Binghamton University

  Authors

  • Christopher Singh

    • Binghamton University
    • Physics, Binghamton University
    • Physics, Applied Physics, and Astronomy, Binghamton University

  • Matthew Redell

    • Binghamton University
    • Physics, Binghamton University

  • Mohannad Elhamod

    • Virginia Tech
    • Computer Science, Virginia Tech

  • Jie Bu

    • Virginia Tech
    • Computer Science, Virginia Tech

  • Anuj Karpatne

    • Virginia Tech
    • Computer Science, Virginia Tech

  • Wei-Cheng Lee

    • Binghamton University
    • Physics, Binghamton University
    • Physics, Applied Physics, and Astronomy, Binghamton University

  View abstract →

• Adversarial machine learning for modeling the distribution of large-scale ultracold atom experiments

  ORAL

  March 4, 2020, 9:48 AM – March 4, 2020, 10:00 AM

  Presenters

  • Corneel Casert

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

  Authors

  • Corneel Casert

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

  • Kyle Mills

    • Ontario Tech University

  • Tom Vieijra

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

  • Jan Ryckebusch

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

  • Isaac Tamblyn

    • Natl Res Council
    • National Research Council of Canada

  View abstract →

• Using Convolutional Neural Networks to analyze phase transitions and calculate critical exponents

  ORAL

  March 4, 2020, 10:00 AM – March 4, 2020, 10:12 AM

  Presenters

  • Nishad Maskara

    • Physics, California Institute ot Technology

  Authors

  • Nishad Maskara

    • Physics, California Institute ot Technology

  • Evert Van Nieuwenburg

    • IQIM, Caltech
    • Caltech
    • Physics, California Institute ot Technology

  • Manuel Endres

    • Caltech
    • Physics, California Institute ot Technology

  View abstract →

• Unsupervised learning of topological indices

  ORAL

  March 4, 2020, 10:12 AM – March 4, 2020, 10:24 AM

  Presenters

  • Oleksandr Balabanov

    • University of Gothenburg

  Authors

  • Oleksandr Balabanov

    • University of Gothenburg

  • Mats Granath

    • Goteborg Univ
    • University of Gothenburg

  View abstract →

• Machine Learning based BCS superconductivity Predictor from Normal State Properties

  ORAL

  March 4, 2020, 10:24 AM – March 4, 2020, 10:36 AM

  Presenters

  • Fei Han

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  Authors

  • Fei Han

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  • Nina Andrejevic

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  • Thanh Nguyen

    • Massachusetts Institute of Technology MIT

  • Quynh Nguyen

    • Massachusetts Institute of Technology MIT

  • Shreya Parjan

    • Wellesley College

  • Mingda Li

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  View abstract →

• Unlocking quantum critical phenomena with physics guided artificial intelligence

  ORAL

  March 4, 2020, 10:36 AM – March 4, 2020, 10:48 AM

  Presenters

  • Matthew Redell

    • Binghamton University
    • Physics, Binghamton University

  Authors

  • Christopher Singh

    • Binghamton University
    • Physics, Binghamton University
    • Physics, Applied Physics, and Astronomy, Binghamton University

  • Matthew Redell

    • Binghamton University
    • Physics, Binghamton University

  • Mohannad Elhamod

    • Virginia Tech
    • Computer Science, Virginia Tech

  • Jie Bu

    • Virginia Tech
    • Computer Science, Virginia Tech

  • Wei-Cheng Lee

    • Binghamton University
    • Physics, Binghamton University
    • Physics, Applied Physics, and Astronomy, Binghamton University

  • Anuj Karpatne

    • Virginia Tech
    • Computer Science, Virginia Tech

  View abstract →

• Neural-Network Approach to Dissipative Quantum Many-Body Dynamics

  ORAL

  March 4, 2020, 10:48 AM – March 4, 2020, 11:00 AM

  Presenters

  • Michael Hartmann

    • Univ Erlangen Nuremberg

  Authors

  • Michael Hartmann

    • Univ Erlangen Nuremberg

  • Giuseppe Carleo

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

  View abstract →