131 citations · 261 across the 8 of their papers we have counts for
8 papers
Uncertainty Quantification for Optical Model Parameters
A. E. Lovell, F. M. Nunes, J. Sarich +1
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well kn…
Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing
Sven Leyffer, Stefan M. Wild, Mike Fagan +4
Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness, where the quality of the solution can be traded for energy savings, has b…
Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements
J. D. McDonnell, N. Schunck, D. Higdon +3
Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models; to estimate mo…
Nuclear Energy Density Optimization: UNEDF2
M. Kortelainen, J. McDonnell, W. Nazarewicz +8
The parameters of the UNEDF2 nuclear energy density functional (EDF) model were obtained in an optimization to experimental data consisting of nuclear binding energies, proton radi…
Statistical uncertainties of a chiral interaction at next-to-next-to leading order
A. Ekström, B. D. Carlsson, K. A. Wendt +4
We have quantified the statistical uncertainties of the low-energy coupling-constants (LECs) of an optimized nucleon-nucleon (NN) interaction from chiral effective field theory ($χ…
Derivative-free optimization for parameter estimation in computational nuclear physics
Stefan M. Wild, Jason Sarich, Nicolas Schunck
We consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. W…