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Register a new userPropagation of Statistical Uncertainties of Skyrme Mass Models to Simulations of $r$-Process Nucleosynthesis
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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 $beta$-decay and neutron capture rates. We additionally make the first identifications of specific parameters of Skyrme-like energy density functionals which are correlated 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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Multimessenger observations of the neutron star merger event GW170817 have re-energized the debate over the astrophysical origins of the most massive elements via the r-process nucleosynthesis. A key aspect of such studies is comparing astronomical observations to theoretical nucleosynthesis yields in a meaningful way. To perform realistic nucleosynthesis calculations, understanding the uncertainty in microphysics details such as nuclear reaction rates is as essential as understanding uncertainties in modeling the astrophysical environment. We present an investigation of neutron capture rate calculations uncertainty away from stability using the Hauser-Feshbach model. We provide a quantitative measure of the calculations dependability when we extrapolate models of statistical properties to nuclei in an r-process network. We select several level density and gamma-ray strength models appropriate for neutron-capture and use them to calculate the reaction rate for each nucleus in the network. We observe how statistical properties affect the theoretical reaction rates. The rates are then sampled with the Monte Carlo technique and used in network calculations to map the range of possible r-process abundances. The results show that neutron capture rates can vary by a couple of orders of magnitude between calculations. Phenomenological models provide smoother results than semi-microscopic. They cannot, however, reproduce nuclear structure changes such as shell closures. While semi-microscopic models predict nuclear structure effects away from stability, it is not clear that these results are quantitatively accurate. The effect of the uncertainty on r-process yields is large enough to impede comparisons between observation and calculations. Progress in developing better microscopic models of gamma strengths and level densities is urgently needed to improve the fidelity of r-process models.
Based on a simple site-independent approach, we attempt to reproduce the solar $r$-process abundance with four nuclear mass models, and investigate the impact of the nuclear mass uncertainties on the $r$ process. In this paper, we first analyze the reliability of an adopted empirical formula for $beta$-decay half-lives which is a key ingredient for the $r$ process. Then we apply four different mass tables to study the $r$-process nucleosynthesis together with the calculated $beta$-decay half-lives, and the existing $beta$-decay data from FRDM+QRPA is also considered for comparison. The numerical results show that the main features of the solar $r$-process pattern and the locations of the abundance peaks can be reproduced well via the $r$-process simulations. Moreover, we also find that the mass uncertainties can significantly affect the derived astrophysical conditions for the $r$-process site, and resulting in a remarkable impact on the $r$ process.
About half of the heavy elements in the Solar System were created by rapid neutron capture, or r-process, nucleosynthesis. In the r-process, heavy elements are built up via a sequence of neutron captures and beta decays in which an intense neutron flux pushes material out towards the neutron drip line. The nuclear network simulations used to test potential astrophysical scenarios for the r-process therefore require nuclear physics data (masses, beta decay lifetimes, neutron capture rates, fission probabilities) for thousands of nuclei far from stability. Only a small fraction of this data has been experimentally measured. Here we discuss recent sensitivity studies that aim to determine the nuclei whose properties are most crucial for r-process calculations.
Background: Exotic non-spherical nuclear pasta shapes are expected in nuclear matter at just below saturation density because of competition between short range nuclear attraction and long range Coulomb repulsion. Purpose: We explore the impact of nuclear pasta on nucleosynthesis, during neutron star mergers, as cold dense nuclear matter is ejected and decompressed. Methods: We perform classical molecular dynamics simulations with 51200 and 409600 nucleons, that are run on GPUs. We expand our simulation region to decompress systems from an initial density of 0.080 fm^{-3} down to 0.00125 fm^{-3}. We study proton fractions of Y_P=0.05, 0.10, 0.20, 0.30, and 0.40 at T =0.5, 0.75, and 1.0 MeV. We calculate the composition of the resulting systems using a cluster algorithm. Results: We find final compositions that are in good agreement with nuclear statistical equilibrium models for temperatures of 0.75 and 1 MeV. However, for proton fractions greater than Y_P=0.2 at a temperature of T = 0.5 MeV, the MD simulations produce non-equilibrium results with large rod-like nuclei. Conclusions: Our MD model is valid at higher densities than simple nuclear statistical equilibrium models and may help determine the initial temperatures and proton fractions of matter ejected in mergers.
Simulations of r-process nucleosynthesis require nuclear physics information for thousands of neutron-rich nuclear species from the line of stability to the neutron drip line. While arguably the most important pieces of nuclear data for the r-process are the masses and beta decay rates, individual neutron capture rates can also be of key importance in setting the final r-process abundance pattern. Here we consider the influence of neutron capture rates in forming the A~80 and rare earth peaks.
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