Oscillating magnetised hybrid stars under the magnifying glass of multi-messenger observations

Autor: Mariani, Mauro, Tonetto, Lucas, Rodríguez, M. Camila, Celi, Marcos O., Ranea-Sandoval, Ignacio F., Orsaria, Milva G., Martínez, Aurora Pérez
Rok vydání: 2022
Předmět:
Zdroj: Monthly Notices of the Royal Astronomical Society, 2022, stac546
Druh dokumentu: Working Paper
DOI: 10.1093/mnras/stac546
Popis: We model neutron stars as magnetised hybrid stars with an abrupt hadron-quark phase transition in their cores, taking into account current constraints from nuclear experiments and multi-messenger observations. We include magnetic field effects considering the Landau level quantisation of charged particles and the anomalous magnetic moment of neutral particles. We construct the magnetised hybrid equation of state, and we compute the particle population, the matter magnetisation and the transverse and parallel pressure components. We integrate the stable stellar models, considering the dynamical stability for \emph{rapid} or \emph{slow} hadron-quark phase conversion. Finally, we calculate the frequencies and damping times of the fundamental and $g$ non-radial oscillation modes. The latter, a key mode to learn about phase transitions in compact objects, is only obtained for stars with slow conversions. For low magnetic fields, we find that one of the objects of the GW170817 binary system might be a hybrid star belonging to the slow extended stability branch. For magnetars, we find that a stronger magnetic field always softens the hadronic equation of state. Besides, only for some parameter combinations a stronger magnetic field implies a higher hybrid star maximum mass. Contrary to previous results, the incorporation of anomalous magnetic moment does not affect the studied astrophysical quantities. We discuss possible imprints of the microphysics of the equation of state that could be tested observationally in the future, and that might help infer the nature of dense matter and hybrid stars.
Comment: Accepted for publication in MNRAS (February 2022)
Databáze: arXiv