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arXiv · 2403.03743

Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes

Abstract

We present here an extended nuclear network, with 90 species, designed for being coupled with hydrodynamic simulations, which includes neutrons, protons, electrons, positrons, and the corresponding neutrino and anti-neutrino emission. This network is also coupled with temperature, making it extremely robust and, together with its size, unique of its kind. The inclusion of electron captures on free protons makes the network very appropriate for multidimensional studies of Type Ia supernova explosions, especially when the exploding object is a massive white dwarf. The results obtained with the proposed medium-sized network compare fairly well, to a few percent, with those computed with the extended network WinNet (> 2000 isotopes) in scenarios reproducing the gross physical conditions of current Type Ia supernova explosion models. In those cases where the carbon and oxygen fuel ignites at high density, the high-temperature plateau typical of the nuclear statistical equilibrium regime is well defined and stable, allowing large integration time steps. We show that the inclusion of electron captures on free protons substantially improves the estimation of the electron fraction of the mixture. Therefore, the pressure is better determined than in networks where electron captures are excluded, which will ultimately lead to more reliable hydrodynamic models. Explosive combustion of helium at low density, occurring near the surface layer of a white dwarf, is also better described with the proposed network, which gives nuclear energy generation rates much closer to WinNet than typical reduced alpha networks.

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Domingo García-Senz, Rubén M. Cabezón, Moritz Reichert, Axel S. Lechuga, José A. Escartín, Athanasios Psaltis, Almudena Arcones, Friedrich-Karl Thielemann. 2024-03-06. Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes. https://doi.org/10.1051/0004-6361%2F202449863

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