Pattern Recognition with Deep Learning in Quantum Materials

ORAL

Abstract

The capabilities of surface probe experiments are rapidly expanding, providing views on quantum materials at unprecedented length and time scales. Many such materials display intricate pattern formation in the electronic properties on the observable surface. This rich spatial information contains information about interactions, dimensionality, and disorder.[1] A well-tuned machine learning framework can decipher this information with minimal effort from the user.[2] We show the effectiveness of our deep learning framework on simulations of statistical models. We then use our machine learning model to analyze experimental data from an optical microscope[3] on a vanadium dioxide film as it goes through the insulator-metal transition.
[1] B. Phillabaum, et al. Nat Commun 3, 915(2012).
[2] L. Burzawa, et al. Phys. Rev. Materials 3, 033805(2019).
[3] A. Zimmers, et al. Phys. Rev. Lett. 110, 056601(2013).

*NSF Grant No. DMR-1508236 and DMR-2006192, the Research Corporation for Science Advancement SEED Award, and XSEDE Grant Nos. TG-DMR-180098 and DMR-190014. S.B. acknowledges support from a Bilsland Dissertation Fellowship. E.W.C. acknowledges support from a Fulbright Fellowship. P.S. and I.K.S. acknowledge support by the QMEENC-EFRC funded by the U.S. DOE, under Award # DE-SC0019273.

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Presenters

  • Sayan Basak

    • Dept. of Physics and Astronomy, Purdue University

Authors

  • Sayan Basak

    • Dept. of Physics and Astronomy, Purdue University

  • Forrest Simmons

    • Dept. of Physics and Astronomy, Purdue University
    • Purdue University

  • Pavel Salev

    • Dept. of Physics and Center for Advanced Nanoscience, UCSD, La Jolla, CA, USA
    • Department of Physics, University of California, San Diego
    • University of California, San Diego

  • Ivan Schuller

    • University of California, San Diego
    • Dept. of Physics and Center for Advanced Nanoscience, UCSD, La Jolla, CA, USA
    • Physics Department, University of California, San Diego
    • Department of Physics, University of California, San Diego

  • Lionel Aigouy

    • LPEM, ESPCI-PSL, CNRS, Sorbonne Univ., Paris-France

  • Alexandre J Zimmers

    • LPEM, ESPCI-PSL, CNRS, Sorbonne Univ., Paris-France

  • Erica W Carlson

    • Dept. of Physics and Astronomy, Purdue University
    • Purdue University