Machine Learning Quantum States II

FOCUS · F18

Presentations

  • Machine Learning Physics: From Quantum Mechanics to Holographic Geometry

    Invited

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    Presenters

    • Yizhuang You

      University of California, San Diego, Department of Physics, Harvard University, Physics, University of California, San Diego, Department of Physics, University of California, San Diego, Harvard University, UCSD

    Authors

    • Yizhuang You

      University of California, San Diego, Department of Physics, Harvard University, Physics, University of California, San Diego, Department of Physics, University of California, San Diego, Harvard University, UCSD

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  • Comparing deep reinforcement-learning techniques: applications to quantum memory

    ORAL

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    Presenters

    • Petru Tighineanu

      Max Planck Institute for the Science of Light

    Authors

    • Petru Tighineanu

      Max Planck Institute for the Science of Light

    • Thomas Foesel

      Max Planck Institute for the Science of Light

    • Talitha Weiss

      IQOQI, University of Innsbruck, Institute for Quantum Optics and Quantum Information

    • Florian Marquardt

      Max Planck Institute for the Science of Light, Max Planck Institute for the Science of Light, Staudtstrasse 2, 91058 Erlangen, Germany

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  • Structural Predictors for Machine Learning Modeling of Superconductivity in Iron-based Materials

    ORAL

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    Presenters

    • Valentin Stanev

      University of Maryland, College Park

    Authors

    • Valentin Stanev

      University of Maryland, College Park

    • Jack Flowers

      University of Maryland, College Park

    • Ichiro Takeuchi

      Materials Science and Engineering, University of Maryland, University of Maryland, University of Maryland, College Park, Materials Science & Engineering Dept, University of Maryland

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  • Understanding Magnetic Properties of Uranium-Based Binary Compounds from Machine Learning

    ORAL

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    Presenters

    • Ayana Ghosh

      Materials Science and Engineering, University of Connecticut

    Authors

    • Ayana Ghosh

      Materials Science and Engineering, University of Connecticut

    • Serge M Nakhmanson

      Department of Materials Science and Engineering, University of Connecticut, Materials Science and Engineering, University of Connecticut

    • Jian-Xin Zhu

      Theoretical Division, Los Alamos National Laboratory, Los Alamos National Laboratory, Theoretical Division and Center for Integrated Nanotechnologies, Los Alamos National Laboratory, T4-PHYS OF CONDENSED MATTER & COMPLEX SYS, Los Alamos National Laboratory, Los aAlamos, USA, CINT, Los Alamos National Laboratory, Center for Integrated Nanotechnologies, Los Alamos National Laboratory, Los Alamos National Laboratory,

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  • Machine learning-assisted search for high performance plasmonic metals

    ORAL

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    Presenters

    • Ethan Shapera

      Department of Physics, University of Illinois at Urbana-Champaign

    Authors

    • Ethan Shapera

      Department of Physics, University of Illinois at Urbana-Champaign

    • Andre Schleife

      University of Illinois at Urbana-Champaign, Materials Science and Engineering, University of Illinois at Urbana-Champaign, Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign

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  • Machine Learning and Crystal Structure Prediction of Molecular Crystals

    ORAL

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    Presenters

    • Emine Kucukbenli

      Condensed Matter Physics, International School for Advanced Studies, International School for Advanced Studies

    Authors

    • Ruggero Lot

      International School for Advanced Studies

    • Franco Pellegrini

      SISSA, Trieste, Italy, International School for Advanced Studies

    • Yusuf Shaidu

      Condensed Matter Physics, International School for Advanced Studies, International School for Advanced Studies

    • Emine Kucukbenli

      Condensed Matter Physics, International School for Advanced Studies, International School for Advanced Studies

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  • Fitting effective models using QMC parameter derivatives

    ORAL

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    Presenters

    • William Wheeler

      University of Illinois at Urbana-Champaign

    Authors

    • William Wheeler

      University of Illinois at Urbana-Champaign

    • Shivesh Pathak

      University of Illinois at Urbana-Champaign

    • Lucas Wagner

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

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  • Detection of Phase Transitions in Quantum Spin Chains via Unsupervised Machine Learning

    ORAL

    –

    Presenters

    • Yutaka Akagi

      Department of Physics, The University of Tokyo

    Authors

    • Yutaka Akagi

      Department of Physics, The University of Tokyo

    • Nobuyuki Yoshioka

      Department of Physics, The University of Tokyo

    • Hosho Katsura

      Physics, University of Tokyo, Department of Physics, University of Tokyo, University of Tokyo, Department of Physics, The University of Tokyo

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