Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session S59: Matter under Extreme Conditions III
8:00 AM–10:24 AM,
Thursday, March 9, 2023
Room: Room 301
Sponsoring
Unit:
DCOMP
Chair: Rahul Jangid, University of California, Davis
Abstract: S59.00003 : Uncertainty propagation in the equation-of-state model for gold*
8:24 AM–8:36 AM
Presenter:
Lin H Yang
(Lawrence Livermore Natl Lab)
Author:
Lin H Yang
(Lawrence Livermore Natl Lab)
Collaborations:
Jim A Gaffney, Phil A Sterne, Suzanne Ali
Gaussian Processes (GPs) are a class of kernel methods that can provide a potential alternative to the current approach that does not contain data uncertainty in the model. GPs come equipped with the possibility to obtain a predictive variance (i.e., error bars, confidence intervals) for each prediction. Unfortunately, the GP formulation assumes no noise in the inputs, only in the observations. In this work, we will formulate an Errors-in-Variables GP EOS model that explores the processes of propagating input and output uncertainties to model uncertainty in EOS table generation. We will demonstrate the approach using experimental and simulation data for gold and explore the robustness of uncertainty propagation in the resulting EOS due to data sparsity, experiment and simulation noises, and extrapolation from available data.
*Prepared for LLNL under Contract DE-AC52-07NA27344.
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