Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses

Surman, Rebecca; Mumpower, Matthew; McLaughlin, Gail

doi:10.7566/JPSCP.14.010612

Title: Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses

Abstract

Unknown nuclear masses are a major source of nuclear physics uncertainty for r-process nucleosynthesis calculations. Here we examine the systematic and statistical uncertainties that arise in r-process abundance predictions due to uncertainties in the masses of nuclear species on the neutron-rich side of stability. There is a long history of examining systematic uncertainties by the application of a variety of different mass models to r-process calculations. Here we expand upon such efforts by examining six DFT mass models, where we capture the full impact of each mass model by updating the other nuclear properties — including neutron capture rates, β-decay lifetimes, and β-delayed neutron emission probabilities — that depend on the masses. Unlike systematic effects, statistical uncertainties in the r-process pattern have just begun to be explored. Here we apply a global Monte Carlo approach, starting from the latest FRDM masses and considering random mass variations within the FRDM rms error. Here, we find in each approach that uncertain nuclear masses produce dramatic uncertainties in calculated r-process yields, which can be reduced in upcoming experimental campaigns.

Authors:

Surman, Rebecca ^[1];

^[2]; McLaughlin, Gail ^[3]

Univ. of Notre Dame, Notre Dame, IN (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
North Carolina State Univ., Raleigh, NC (United States)

Publication Date:: Mon Feb 27 00:00:00 EST 2017

Research Org.:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Nuclear Physics (NP)

OSTI Identifier:: 1351194

Report Number(s):: LA-UR-16-26923
Journal ID: ISSN 9999-0004

Grant/Contract Number:: AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: JPS Conference Proceedings

Additional Journal Information:: Conference: 14. Interational Symposium on Nuclei In the Cosmos (NIC2016), Niigata (Japan), 19-24 Jun 2016; Journal ID: ISSN 9999-0004

Publisher:: Physical Society of Japan

Country of Publication:: United States

Language:: English

Subject:: 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 97 MATHEMATICS AND COMPUTING; atomic and nuclear physics; astronomy and astrophysics; nuclear masses; r-process; binding energies and masses

Citation Formats


                    Surman, Rebecca, Mumpower, Matthew, and McLaughlin, Gail. Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses.  United States: N. p., 2017. 
Web.  doi:10.7566/JPSCP.14.010612.

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                    Surman, Rebecca, Mumpower, Matthew, & McLaughlin, Gail. Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses.  United States.  https://doi.org/10.7566/JPSCP.14.010612

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                    Surman, Rebecca, Mumpower, Matthew, and McLaughlin, Gail. Mon .  
"Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses".  United States.  https://doi.org/10.7566/JPSCP.14.010612.  https://www.osti.gov/servlets/purl/1351194.

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@article{osti_1351194,

  title        = {Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses},

  author       = {Surman, Rebecca and Mumpower, Matthew and McLaughlin, Gail},

  abstractNote = {Unknown nuclear masses are a major source of nuclear physics uncertainty for r-process nucleosynthesis calculations. Here we examine the systematic and statistical uncertainties that arise in r-process abundance predictions due to uncertainties in the masses of nuclear species on the neutron-rich side of stability. There is a long history of examining systematic uncertainties by the application of a variety of different mass models to r-process calculations. Here we expand upon such efforts by examining six DFT mass models, where we capture the full impact of each mass model by updating the other nuclear properties — including neutron capture rates, β-decay lifetimes, and β-delayed neutron emission probabilities — that depend on the masses. Unlike systematic effects, statistical uncertainties in the r-process pattern have just begun to be explored. Here we apply a global Monte Carlo approach, starting from the latest FRDM masses and considering random mass variations within the FRDM rms error. Here, we find in each approach that uncertain nuclear masses produce dramatic uncertainties in calculated r-process yields, which can be reduced in upcoming experimental campaigns.},

  doi          = {10.7566/JPSCP.14.010612},

  journal      = {JPS Conference Proceedings},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Feb 27 00:00:00 EST 2017},

  month        = {Mon Feb 27 00:00:00 EST 2017}

}

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Works referencing / citing this record:

A Minimal Nuclear Energy Density Functional
text, January 2017

Bulgac, Aurel; Forbes, Michael McNeil; Jin, Shi
arXiv
DOI: 10.48550/arxiv.1708.08771

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Title: Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses

Abstract

Citation Formats

A Minimal Nuclear Energy Density Functional text, January 2017

A Minimal Nuclear Energy Density Functional
text, January 2017