The impact of mass uncertainties on the r-process nucleosynthesis in neutron star mergers
A&A 694, A180 (2025) Theoretical predictions of element yields from the rapid neutron capture (r-) process are subject to large uncertainties due to incomplete knowledge of nuclear properties and approximative hydrodynamical modeling of matter ejection. A major source of uncertainty in determini...
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Main Authors | , |
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Format | Journal Article |
Language | English |
Published |
07.01.2025
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Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.2501.03633 |
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Summary: | A&A 694, A180 (2025) Theoretical predictions of element yields from the rapid neutron capture (r-)
process are subject to large uncertainties due to incomplete knowledge of
nuclear properties and approximative hydrodynamical modeling of matter
ejection. A major source of uncertainty in determining ejecta composition and
radioactive decay heat is the lack of nuclear mass data for exotic neutron-rich
nuclei produced during neutron irradiation.
We examine both model (systematic) and parameter (statistical) uncertainties
affecting nuclear mass predictions and their impact on r-process
nucleosynthesis, and consequently, the composition of neutron star merger
ejecta. To estimate the effect of model uncertainties, we consider five nuclear
mass models that accurately describe known masses. We also use a
backward-forward Monte Carlo method to estimate uncorrelated uncertainties from
local variations in model parameters, constraining them to experimentally known
masses before propagating them to unknown masses of neutron-rich nuclei.
These mass uncertainties are then applied to a 1.38-1.38 M$_{\odot}$ neutron
star merger model, considering a wide range of ejecta trajectories. We find
that uncorrelated parameter uncertainties lead to ejected abundance
uncertainties of 20% up to A $\simeq$ 130, 40% between A=150 and 200, with
peaks around A $\simeq$ 140 and A $\simeq$ 203, leading to deviations of
100-300%. While correlated model uncertainties generally exceed parameter
uncertainties for most nuclei, both have a significant impact on heavy element
production.
Overall, improvements in nuclear models are essential to reducing
uncertainties in r-process predictions. Both correlated model uncertainties and
coherent determination of parameter uncertainties are crucial for sensitivity
analysis in r-process nucleosynthesis. |
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DOI: | 10.48550/arxiv.2501.03633 |