Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis
In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and compa...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-12-01
|
| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2022.1046638/full |
| _version_ | 1798006462708973568 |
|---|---|
| author | Nicole Vassh Gail C. McLaughlin Matthew R. Mumpower Matthew R. Mumpower Rebecca Surman |
| author_facet | Nicole Vassh Gail C. McLaughlin Matthew R. Mumpower Matthew R. Mumpower Rebecca Surman |
| author_sort | Nicole Vassh |
| collection | DOAJ |
| description | In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements. |
| first_indexed | 2024-04-11T12:55:27Z |
| format | Article |
| id | doaj.art-958ad62fca9f42ed903d132a8893b96e |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-11T12:55:27Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-958ad62fca9f42ed903d132a8893b96e2022-12-22T04:23:05ZengFrontiers Media S.A.Frontiers in Physics2296-424X2022-12-011010.3389/fphy.2022.10466381046638Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesisNicole Vassh0Gail C. McLaughlin1Matthew R. Mumpower2Matthew R. Mumpower3Rebecca Surman4TRIUMF, Vancouver, BC, CanadaDepartment of Physics, North Carolina State University, Raleigh, NC, United StatesTheoretical Division, Los Alamos National Laboratory, Los Alamos, NM, United StatesCenter for Theoretical Astrophysics, Los Alamos National Laboratory, Los Alamos, NM, United StatesDepartment of Physics, University of Notre Dame, Notre Dame, IN, United StatesIn recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.https://www.frontiersin.org/articles/10.3389/fphy.2022.1046638/fullnucleosynthesissolar abundancesr-processheavy elementsMarkov Chain Monte Carlo (MCMC)uncertainty quantification (UQ) |
| spellingShingle | Nicole Vassh Gail C. McLaughlin Matthew R. Mumpower Matthew R. Mumpower Rebecca Surman Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis Frontiers in Physics nucleosynthesis solar abundances r-process heavy elements Markov Chain Monte Carlo (MCMC) uncertainty quantification (UQ) |
| title | Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis |
| title_full | Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis |
| title_fullStr | Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis |
| title_full_unstemmed | Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis |
| title_short | Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis |
| title_sort | solar data uncertainty impacts on mcmc methods for r process nucleosynthesis |
| topic | nucleosynthesis solar abundances r-process heavy elements Markov Chain Monte Carlo (MCMC) uncertainty quantification (UQ) |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2022.1046638/full |
| work_keys_str_mv | AT nicolevassh solardatauncertaintyimpactsonmcmcmethodsforrprocessnucleosynthesis AT gailcmclaughlin solardatauncertaintyimpactsonmcmcmethodsforrprocessnucleosynthesis AT matthewrmumpower solardatauncertaintyimpactsonmcmcmethodsforrprocessnucleosynthesis AT matthewrmumpower solardatauncertaintyimpactsonmcmcmethodsforrprocessnucleosynthesis AT rebeccasurman solardatauncertaintyimpactsonmcmcmethodsforrprocessnucleosynthesis |