Propagation of statistical uncertainties of Skyrme mass models to simulations of r -process nucleosynthesis

Sprouse, T. M.; Navarro Perez, R.; Surman, R.; Mumpower, Matthew Ryan; McLaughlin, G. C.; Schunck, N.

doi:10.1103/PhysRevC.101.055803

Title: Propagation of statistical uncertainties of Skyrme mass models to simulations of $r$ -process nucleosynthesis

Journal Article · Fri May 15 00:00:00 EDT 2020 · Physical Review C

DOI:https://doi.org/10.1103/PhysRevC.101.055803· OSTI ID:1630410

^[1]; Navarro Perez, R. ^[2]; Surman, R. ^[3];

^[4]; McLaughlin, G. C. ^[5]; Schunck, N. ^[6]

Univ. of Notre Dame, IN (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
San Diego State Univ., CA (United States)
Univ. of Notre Dame, IN (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
North Carolina State Univ., Raleigh, NC (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Uncertainties in nuclear models have a major impact on simulations that aim at understanding the origin of heavy elements in the universe through the rapid neutron capture process ( r process) of nucleosynthesis. Within the framework of the nuclear density functional theory, we use results of Bayesian statistical analysis to propagate uncertainties in the parameters of energy density functionals to the predicted r -process abundance pattern, by way not only of the nuclear masses but also through the influence of the masses on β -decay and neutron capture rates. We point out the importance of the nonequilibrium end stage of the r process in determining the width of the resulting abundance pattern uncertainty bands. We additionally make the first identifications of specific parameters of Skyrme-like energy density functionals which show tentative correlations with particular aspects of the r -process abundance pattern. While previous studies have explored the reduction in the abundance pattern uncertainties due to anticipated new measurements of neutron-rich nuclei, here we point out that an even larger reduction will occur when these new measurements are used to reduce the uncertainty of model predictions of masses, which are then propagated through to the abundance pattern. We make a quantitative prediction for how large this reduction will be.

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Research Organization:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC52-07NA27344; SC0013039; FG02-95ER40934; FG02-02ER41216; FG02-93ER40756; SC0018232; SC0018223; 89233218CNA000001

OSTI ID:: 1630410

Alternate ID(s):: OSTI ID: 1634950

Report Number(s):: LLNL-JRNL-767227; LA-UR-19-20003; PRVCAN; 957667; TRN: US2200661

Journal Information:: Physical Review C, Vol. 101, Issue 5; ISSN 2469-9985

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 20 works

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