Paper detail

Thermodynamics of self-gravitating fermions as a robust theory for dark matter halos: Stability analysis applied to the Milky Way

We present a framework for dark matter (DM) halo formation based on a kinetic theory of self-gravitating fermions together with a solid connection to thermodynamics. Based on maximum entropy arguments, this approach predicts a most likely phase-space distribution which takes into account the Pauli exclusion principle, relativistic effects, and particle evaporation. The most general equilibrium configurations depend on the particle mass and develop a degenerate compact core embedded in a diluted halo, both linked by their fermionic nature. By applying such a theory to the Milky Way we analyze the stability of different families of equilibrium solutions with implications on the DM distribution and the mass of the DM candidate. We find that stable core-halo profiles, which explain the DM distribution in the Galaxy, exist only in the range $mc^2 \approx 194 - 387\,\rm{keV}$. The lower bound is a consequence of imposing thermodynamical stability on the core-halo solutions having a $4.2\times 10^6 M_\odot$ quantum core mass alternative to the black hole hypothesis at the Galaxy center. The upper bound is solely an outcome of general relativity when the quantum core reaches the Oppenheimer-Volkoff limit and undergoes gravitational collapse towards a black hole. We demonstrate that there exists a set of stable core-halo profiles which are astrophysically relevant in the sense that their total mass is finite, do not suffer from the gravothermal catastrophe, and agree with observations. The morphology of the outer halo tail is described by a polytrope of index $5/2$, developing a sharp decline of the density beyond $25\,\rm{kpc}$ in excellent agreement with the latest Gaia DR3 rotation curve data. Moreover, we obtain a total mass of about $2\times 10^{11} M_\odot$ including baryons and a local DM density of about $0.4\,\rm{GeV}\,c^{-2}\,\rm{cm}^{-3}$ in line with recent independent estimates.