Automating Electronic Transport Measurements at Low Temperatures and Performing Angle Resolved Photoemission Spectroscopy (ARPES) Data Analysis Using Python

ORAL

Abstract

Low temperature electron transport experiments on low dimensional nanomaterials are ruled by exciting quantum effects. In order to extract meaningful information from these experiments, data must be collected and analyzed in an organized and efficient manner. We present a method using the Python programming language and open source libraries to control the acquisition, interactive visualization, and analysis of data from a closed cycle cryostat and different measurment instruments. Additionally, we show the data analysis of a large amount of ARPES data corresponding to the modulation of the intensity of C60 band clusters with the incident photon energy.

*This project is supported in part by Department of Energy award DE-SC0018154 and by the Richard and Florence Scalettar Scholarship

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Presenters

  • Ryan Reno

    • Cal State Univ- Long Beach

Authors

  • Ryan Reno

    • Cal State Univ- Long Beach

  • Drew Latzke

    • University of California Berkeley
    • Applied Science & Technology, Univ of California - Berkeley
    • Univ. of California - Berkeley

  • Alessandra Lanzara

    • University of California Berkeley
    • University of California
    • Univ of California - Berkeley
    • Physics Department - University California, Berkeley, Materials Sciences Division - Lawrence Berkeley National Laboratory
    • Materials Sciences Division, Lawrence Berkeley National Laboratory
    • University of California, Berkeley and Lawrence Berkeley National Laboratory
    • Department of Physics, Univ of California - Berkeley
    • Univ. of California - Berkeley

  • Claudia Ojeda-Aristizabal

    • Cal State Univ- Long Beach
    • Department of Physics and Astronomy, California State University, Long Beach