Bayesian fits that include the 2024 NICER results for PSR J0437 and J1231 narrow the allowed radius range for canonical-mass neutron stars to roughly 12.5 to 12.8 km in covariant density functional models.
Impact of Multiple Phase Transitions in Dense QCD on Compact Stars
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abstract
This review covers several recent developments in the physics of dense QCD with an emphasis on the impact of multiple phase transitions on astrophysical manifestations of compact stars. It is conjectured that pair-correlated quark matter in $\beta$-equilibrium is within the same universality class as spin-imbalanced cold atoms and the isospin asymmetrical nucleonic matter. This then implies the emergence of phases with broken space symmetries and tri-critical (Lifshitz) points. We construct an equation of state (EoS) that extends the two-phase EoS of dense quark matter within the constant speed of sound parameterization by adding a conformal fluid with a speed of sound $c_{\rm conf.}=1/\sqrt{3}$ at densities $\ge 10~n_{\rm sat}$, where $n_{\rm sat}$ is the saturation density. With this input, we construct static, spherically symmetrical compact hybrid stars in the mass--radius diagram, recover such features as the twins and triplets, and show that the transition to conformal fluid leads to the spiraling-in of the tracks in this diagram. Stars on the spirals are classically unstable with respect to the radial oscillations but can be stabilized if the conversion timescale between quark and nucleonic phases at their interface is larger than the oscillation period. Finally, we review the impact of a transition from high-temperature gapped to low-temperature gapless two-flavor phase on the thermal evolution of hybrid stars.
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Bayesian constraints on covariant density functional equations of state of compact stars with new NICER mass-radius measurements
Bayesian fits that include the 2024 NICER results for PSR J0437 and J1231 narrow the allowed radius range for canonical-mass neutron stars to roughly 12.5 to 12.8 km in covariant density functional models.