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Title: Calibration of energy density functionals with deformed nuclei

Abstract

Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy functional and a many-body scheme (e.g., single- or multireference level), the predictive power of the theory depends strongly on how the parameters of the energy functionals have been calibrated with experimental data. Expanded algorithms and computing power have enabled recent optimization protocols to include data in deformed nuclei in order to optimize the coupling constants of the energy functional. The primary motivation of this work is to test the robustness of such protocols with respect to some of the technical and numerical details of the underlying calculations, especially when the calibration explores a large parameter space. To this end, we quantify the effect of these uncertainties on both the optimization and statistical emulation of composite objective functions. We also emphasize that Bayesian calibration can provide better estimates of the theoretical errors used to define objective functions.

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [3]; ORCiD logo [2]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Nuclear Physics (NP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR). Scientific Discovery through Advanced Computing (SciDAC)
OSTI Identifier:
1634891
Alternate Identifier(s):
OSTI ID: 1635271; OSTI ID: 1657135
Report Number(s):
LLNL-JRNL-805357; LA-UR-20-21538
Journal ID: ISSN 0954-3899; 1010365
Grant/Contract Number:  
AC52-07NA27344; AC02-06CH11357; 89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physics. G, Nuclear and Particle Physics
Additional Journal Information:
Journal Volume: 47; Journal Issue: 7; Journal ID: ISSN 0954-3899
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; Density functional theory; self-consistent calculations; Bayesian calibration; optimized energy density functionals; Skyme functionals; supervised learning; Density function theory

Citation Formats

Schunck, N., O’Neal, J., Grosskopf, M., Lawrence, E., and Wild, S. M. Calibration of energy density functionals with deformed nuclei. United States: N. p., 2020. Web. doi:10.1088/1361-6471/ab8745.
Schunck, N., O’Neal, J., Grosskopf, M., Lawrence, E., & Wild, S. M. Calibration of energy density functionals with deformed nuclei. United States. doi:https://doi.org/10.1088/1361-6471/ab8745
Schunck, N., O’Neal, J., Grosskopf, M., Lawrence, E., and Wild, S. M. Thu . "Calibration of energy density functionals with deformed nuclei". United States. doi:https://doi.org/10.1088/1361-6471/ab8745.
@article{osti_1634891,
title = {Calibration of energy density functionals with deformed nuclei},
author = {Schunck, N. and O’Neal, J. and Grosskopf, M. and Lawrence, E. and Wild, S. M.},
abstractNote = {Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy functional and a many-body scheme (e.g., single- or multireference level), the predictive power of the theory depends strongly on how the parameters of the energy functionals have been calibrated with experimental data. Expanded algorithms and computing power have enabled recent optimization protocols to include data in deformed nuclei in order to optimize the coupling constants of the energy functional. The primary motivation of this work is to test the robustness of such protocols with respect to some of the technical and numerical details of the underlying calculations, especially when the calibration explores a large parameter space. To this end, we quantify the effect of these uncertainties on both the optimization and statistical emulation of composite objective functions. We also emphasize that Bayesian calibration can provide better estimates of the theoretical errors used to define objective functions.},
doi = {10.1088/1361-6471/ab8745},
journal = {Journal of Physics. G, Nuclear and Particle Physics},
number = 7,
volume = 47,
place = {United States},
year = {2020},
month = {6}
}

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