Bayesian inference of thermal effects in dense matter within the covariant density functional theory

Adriana R. Raduta; Mikhail V. Beznogov; Micaela Oertel

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arXiv · 2402.14593

Bayesian inference of thermal effects in dense matter within the covariant density functional theory

Adriana R. Raduta·Mikhail V. Beznogov·Micaela Oertel

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Abstract

The high temperatures reached in a proto-neutron star or during the post-merger phase of a binary neutron star coalescence lead to non-negligible thermal effects on the equation of state (EOS) of dense nuclear matter. Here we study these effects within the covariant density functional theory employing the posteriors of a Bayesian inference, which encompasses a large sample of EOS models. Different densities and temperatures are considered. We find that for a number of quantities thermal effects are strongly correlated with the Dirac effective mass ($m^*$) of the nucleons and/or its logarithmic derivative as a function of density. These results can be explained within the low temperature approximation though they survive beyond this limit.

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Adriana R. Raduta, Mikhail V. Beznogov, Micaela Oertel. 2024-02-22. Bayesian inference of thermal effects in dense matter within the covariant density functional theory. https://arxiv.org/abs/2402.14593

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