The Impact of Inhomogeneous Reionization on the Satellite Galaxy Population of the Milky Way

We use the publicly available subhalo catalogs from the Via Lactea simulation along with a Gpc-scale N-body simulation to understand the impact of inhomogeneous reionization on the satellite galaxy population of the Milky Way. The large-volume simulation is combined with a model for reionization that allows us to predict the distribution of reionization times for Milky Way mass halos. Motivated by this distribution, we identify candidate satellite galaxies in the simulation by requiring that any subhalo must grow above a specified mass threshold before it is reionized; after this time the photoionizing background will suppress both the formation of stars and the accretion of gas. We show that varying the reionization time over the range expected for Milky Way mass halos can change the number of satellite galaxies by roughly two orders of magnitude. This conclusion is in contradiction with a number of studies in the literature, and we conclude that this is a result of inconsistent application of the results of Gnedin (2000). We compare our satellite galaxies to observations using both abundance matching and stellar population synthesis methods to assign luminosities to our subhalos and account for observational completeness effects. Additionally, if we assume that the mass threshold is set by the virial temperature Tvir = 8e3K we find that our model accurately matches the vmax distribution, radial distribution, and luminosity function of observed Milky Way satellites for a reionization time zreion = 9.6^{1.0}{-2.1}, assuming that the Via Lacteasubhalo distribution is representative of the Milky Way. This results in the presence of 119^{+202}{-50} satellite galaxies.

💡 Research Summary

The authors investigate how spatially inhomogeneous reionization influences the present‑day satellite population of a Milky Way‑mass halo. They combine two complementary numerical datasets: (1) the high‑resolution Via Lactea II subhalo catalog, which provides detailed structural and kinematic properties (mass, vmax, orbital histories) for thousands of subhalos within a single Milky Way‑sized dark matter halo, and (2) a gigaparsec‑scale, lower‑resolution N‑body simulation that contains a statistically robust sample of Milky Way‑mass halos. In the large‑volume run they embed a semi‑analytic reionization model that assigns each halo a “reionization redshift” based on its local environment, thereby capturing the patchy nature of the ionizing background rather than assuming a single global reionization epoch.

Using these reionization times, the authors define a physically motivated criterion for a subhalo to become a luminous satellite. A subhalo must (i) grow above a mass threshold before its host halo is reionized, and (ii) after reionization the rising UV background suppresses further gas accretion and star formation. The mass threshold can be expressed either as a fixed virial mass or, more physically, as a virial temperature of Tvir ≈ 8 × 10³ K (corresponding to ≈10⁸ M⊙). This approach directly implements Gnedin’s (2000) “filtering mass” concept, but unlike many previous studies the authors compute the filtering mass dynamically for each halo at its own reionization redshift. They argue that earlier works incorrectly applied a static filtering mass, leading to an underestimation of the sensitivity of satellite numbers to reionization timing.

The simulation results show that varying the reionization redshift within the plausible range for Milky Way‑mass halos (z ≈ 6–12) changes the predicted number of surviving satellites by roughly two orders of magnitude—from a few hundred to several thousand. This dramatic dependence suggests that the long‑standing “missing satellites problem” can be alleviated if the Milky Way’s reionization occurred relatively early, because early reionization truncates star formation in a larger fraction of low‑mass subhalos.

To compare with observations, the authors assign stellar luminosities to the surviving subhalos using two independent methods. First, an abundance‑matching technique maps vmax to an absolute V‑band magnitude (MV) based on the observed satellite luminosity function. Second, a stellar‑population‑synthesis (SPS) model translates each subhalo’s star‑formation history (derived from its growth history before reionization) into an MV, accounting for metallicity evolution. Both methods incorporate observational completeness corrections appropriate for the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey (DES), which are essential for the faint end of the satellite population.

When the virial‑temperature threshold (Tvir ≈ 8 × 10³ K) is adopted, the model reproduces three key observables of the Milky Way satellite system: (1) the vmax distribution, (2) the radial (galactocentric distance) distribution, and (3) the luminosity function, provided the reionization redshift is zreion = 9.6 +1.0/−2.1 (statistical uncertainty). Under this best‑fit scenario the predicted total satellite count is 119 +202/−50, substantially larger than the ≈50 satellites currently known but consistent once detection limits are considered.

The paper’s strengths lie in (i) explicitly modeling the spatial variation of reionization times for Milky Way‑mass halos, (ii) applying a physically motivated, time‑dependent filtering mass to select luminous subhalos, and (iii) cross‑validating luminosity assignments with both abundance matching and SPS approaches. Limitations include the assumption that the Via Lactea subhalo population is representative of the actual Milky Way, the relatively simple treatment of reionization feedback (e.g., neglect of radiative transfer complexities and local sources), and the use of fixed star‑formation efficiencies and metallicity prescriptions. Future work could explore a broader suite of reionization histories, incorporate more detailed hydrodynamic feedback, and leverage upcoming deep surveys (e.g., LSST) to refine the completeness corrections.

Overall, the study demonstrates that the timing and patchiness of cosmic reionization are critical determinants of the Milky Way’s satellite census. By linking large‑scale reionization physics to the small‑scale subhalo population, the authors provide a compelling framework that both alleviates the missing satellites tension and offers a novel avenue to constrain the epoch of reionization through the observed properties of nearby dwarf galaxies.