BYU

Abstract by Kinamo Williams

Personal Infomation


Presenter's Name

Kinamo Williams

Degree Level

Undergraduate

Co-Authors

Yonatan Kurniawan
Mark Transtrum
Cody Petrie

Abstract Infomation


Department

Physics and Astronomy

Faculty Advisor

Mark Transtrum

Title

Bayesian Approach to Uncertainty Quantification of Interatomic Models in OpenKIM Database

Abstract

Interatomic models (IMs) are used in molecular modeling to predict material properties of interest. The development of a single IM can take anywhere from several months to years and relies on expert intuition, and yet these potentials are usually only valid for a particular application of interest. Extending existing IMs to new applications is an active area of research. Quantifying the uncertainty of an IM can tell us how much we can trust the predictions it makes. Using Monte Carlo methods, I sample from the posterior distribution of the parameters when trained on data. I demonstrate this method on Lennard-Jones and Morse potentials fit to triclinic crystal configurations from the OpenKIM database. In particular, IMs are often sloppy, i.e., have likelihood surfaces with long, narrow canyons and broad, flat plateaus. I also discuss the use of Fisher Information Matrix for uncertainty quantification for these potentials. I discuss implications of sloppiness for uncertainty quantification in molecular modeling.