Amorphous materials modeling and classification for low mechanical loss mirror coatings using machine learning methods

ORAL

Abstract

Instead of the well-defined atomic structures of crystals, amorphous materials are more complicated due to intrinsic randomness. Modeling and predicting the properties of amorphous materials (amorphous Ta2O5, doped Ta2O5) are important to understand experimental results and to find lower mechanical loss mirror coatings to reduce thermal noise in the next generation of LIGO laser interferometer gravitational wave detectors. In our work, thousands of atomic models of amorphous materials are generated using reverse Monte Carlo (RMC) and molecular dynamics (MD) simulations based on experimental data. Classifying them into different groups according to their properties and features with the help of machine learning, enables us to understand the differences between these models and use the information from these structures to find the best materials for low mechanical loss mirror coating.

*NSF/PHY 1707870 and NSF/PHY 1404110. Thanks Ximing Wang for the discussion and the help with the machine learning method.

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Presenters

  • Jun Jiang

    • Department of Physics and Quantum Theory Project, University of Florida

Authors

  • Jun Jiang

    • Department of Physics and Quantum Theory Project, University of Florida

  • Maher Yazback

    • Department of Physics and Quantum Theory Project, University of Florida
    • University of Florida

  • Alec Mishkin

    • Department of Physics and Quantum Theory Project, University of Florida

  • Kiran Prasai

    • E. L. Ginzton Laboratory, Stanford University
    • Ginzton Laboratory, Stanford University
    • Applied Physics, Stanford University
    • E. L. Ginzton Laboratory, Stanford

  • Riccardo Bassiri

    • Department of Applied Physics, Ginzton Laboratory, Stanford University, Stanford, CA, USA
    • Applied Physics, Stanford University
    • E. L. Ginzton Laboratory, Stanford University
    • Ginzton Laboratory, Stanford University
    • E. L. Ginzton Laboratory, Stanford

  • Martin Fejer

    • Department of Applied Physics, Ginzton Laboratory, Stanford University, Stanford, CA, USA
    • Stanford University
    • Applied Physics, Stanford University
    • E. L. Ginzton Laboratory, Stanford University
    • Ginzton Laboratory, Stanford University
    • E. L. Ginzton Laboratory, Stanford

  • Hai-Ping Cheng

    • Department of Physics and Quantum Theory Project, University of Florida
    • Department of Physics and the Quantum Theory Project, University of Florida