APS Logo

Bayesian Uncertainty Quantification: BayUQ

INVITED · JA · ID: 605536

Presentations

  • The Bayesian Analysis of Nuclear Dynamics Framework

    ORAL · Invited

    –

    Publication: Get on the BAND Wagon: A Bayesian Framework for Quantifying Model Uncertainties in Nuclear Dynamics<br>(D.R. Phillips, R.J. Furnstahl, U. Heinz, T. Maiti, W. Nazarewicz, F.M. Nunes, M. Plumlee, M.T. Pratola, S. Pratt, F.G. Viens, and S.M. Wild) <br>J. Phys. G 48, 072001 (2021)<br><br>Performing Bayesian Analyses with AZURE2 using BRICK: an Application to the Be-7 System<br>(Daniel Odell, Carl R. Brune, Daniel R. Phillips, Richard James deBoer, Som Nath Paneru)<br>arXiv:2112.12838, for in press in Special Issue of Frontiers on Uncertainty Quantification in Nuclear Physics<br><br>Uncertainty Quantification in Breakup Reactions <br>https://arxiv.org/abs/2205.07119<br>(Özge Sürer, Filomena M. Nunes, Matthew Plumlee, Stefan M. Wild)<br>Submitted to PRC.<br><br>For a full list of BAND supported publications, see http://bandframework.github.io<br>

    Presenters

    • Ozge Surer

      Northwestern University, Miami University

    Authors

    • Ozge Surer

      Northwestern University, Miami University

    View abstract →

  • Bayesian Tools for a Better Optical Model

    ORAL · Invited

    –

    Publication: Phys. Rev. C 104, 064611 (2021)

    Presenters

    • Amy E Lovell

      Los Alamos Natl Lab

    Authors

    • Amy E Lovell

      Los Alamos Natl Lab

    • Manuel Catacora-Rios

      University of Chicago

    • Garrett B King

      Washington University, St. Louis

    • Filomena Nunes

      Michigan State University

    View abstract →