Viewing time-resolved X-ray scattering data in a maximally sparse basis

ORAL

Abstract

Time-resolved X-ray scattering (TRXS) data on photoexcited molecules contains rich spatial and temporal information that can yield unique insights into ultrafast chemical dynamics. Recent advances in data analysis methodology have shown promise in reducing molecular motion to sparse data features, such as frequency-resolved X-ray scattering (FRXS) for temporal sparsity and natural scattering kernels (NSK) for spatial sparsity. However, these techniques fail to achieve sparsity along both axes simultaneously, posing a challenge for directly extracting molecular structure and dynamics.



Our remedy to this problem is to utilize a Hough transform applied to FRXS data to achieve simultaneous sparsity for two important classes of molecular motion: vibration and dissociation. Vibrations and dissociations have one-dimensional sparsity in FRXS data, appearing as linear features in (Q,ω) space. The Hough transform reduces these features to points in (slope, y-intercept) space. Molecular motion can then be extracted via simple one-dimensional lineouts of the Hough transform, yielding information such as vibrational frequency, dissociation velocity distribution, and fragment rovibrational states. Experimental results are presented to showcase the Hough transform technique.

*This work is supported by the AMOS program in the Chemical Sciences, Geosciences, and Biosciences Division of Basic Energy Sciences at the U.S. Department of Energy.

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Publication: Gabalski, Ian, et al. "Transient vibration and product formation of photoexcited CS2 measured by time-resolved x-ray scattering." The Journal of Chemical Physics 157.16 (2022): 164305.

Presenters

  • Ian Gabalski

    • Stanford Univ
    • Stanford University

Authors

  • Ian Gabalski

    • Stanford Univ
    • Stanford University

  • Malick Sere

    • Stanford University

  • Kyle Acheson

    • University of Edinburgh

  • Felix Allum

    • Stanford University
    • Stanford PULSE Institute
    • Stanford PULSE Institute, Menlo Park, CA, USA

  • Sebastien Boutet

    • SLAC - Natl Accelerator Lab
    • SLAC National Accelerator Laboratory

  • Gopal Dixit

    • MBI Berlin

  • Ruaridh Forbes

    • SLAC National Accelerator Laboratory
    • LCLS, SLAC National Accelerator Laboratory, Menlo Park, CA, USA

  • James M Glownia

    • SLAC - Natl Accelerator Lab
    • LCLS, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
    • SLAC National Accelerator Laboratory

  • Nathan Goff

    • Brown University

  • Kareem Hegazy

    • Stanford Univ

  • Andrew J Howard

    • Stanford University

  • Mengning Liang

    • SLAC National Accelerator Laboratory
    • SLAC Natl Accelerator Lab

  • Michael Minitti

    • SLAC National Accelerator Laboratory
    • SLAC Natl Accelerator Lab

  • Russell S Minns

    • University of Southampton

  • Adi Natan

    • SLAC National Accelerator Laboratory

  • Nolan Peard

    • Stanford University

  • Weronika O Razmus

    • University of Southampton

  • Roseanne J Sension

    • University of Michigan

  • Mattew Ware

    • Stanford University

  • Peter M Weber

    • Brown University

  • Nicholas Werby

    • Stanford University

  • Thomas J Wolf

    • SLAC - Natl Accelerator Lab
    • SLAC National Accelerator Laboratory

  • Adam Kirrander

    • University of Oxford
    • Oxford University

  • Philip H Bucksbaum

    • Stanford Univ
    • Stanford University