Derivative-free Optimization for Parameter Estimation in Computational Nuclear Physics

TitleDerivative-free Optimization for Parameter Estimation in Computational Nuclear Physics
Publication TypeJournal Article
Year of Publication2015
AuthorsSarich, J, Schunck, N, Wild, SM
JournalJournal of Physics G: Nuclear and Particle Physics
Volume42
Issue3
Pagination034031
Other NumbersANL/MCS-P5149-0614
AbstractWe consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. We examine the cost of not having derivatives of these functionals with respect to the parameters. We show that the POUNDERS code for local derivative-free optimization obtains consistent solutions on a variety of computationally expensive energy density functional calibration problems. We also provide a primer on the operation of the POUNDERS software in the Toolkit for Advanced Optimization.
DOI10.1088/0954-3899/42/3/034031
PDFhttp://www.mcs.anl.gov/papers/P5149-0614.pdf