How low does it go? Too few Galactic satellites with standard reionization quenching

ABSTRACT A standard prediction of galaxy formation theory is that the ionizing background suppresses galaxy formation in haloes with peak circular velocities smaller than $V_{\rm peak}\simeq 20 \, \rm km \, s^{-1}$, rendering the majority of haloes below this scale completely dark. We use a suite of cosmological zoom simulations of Milky Way-like haloes that include central Milky Way disc galaxy potentials to investigate the relationship between subhaloes and ultrafaint galaxies. We find that there are far too few subhaloes within 50 kpc of the Milky Way that had $V_{\rm peak}\gtrsim 20\, \rm km \, s^{-1}$ to account for the number of ultrafaint galaxies already known within that volume today. In order to match the observed count, we must populate subhaloes down to $V_{\rm peak}\simeq 6\, \rm km \, s^{-1}$ with ultrafaint dwarfs. The required haloes have peak virial temperatures as low as 1500 K, well below the atomic hydrogen cooling limit of 104 K. Allowing for the possibility that the Large Magellanic Cloud contributes several of the satellites within 50 kpc could potentially raise this threshold to $10\, \rm km \, s^{-1}$ (4000 K), still below the atomic cooling limit and far below the nominal reionization threshold.

The mass of the Milky Way from satellite dynamics

We present and apply a method to infer the mass of the Milky Way (MW) by comparing the dynamics of MW satellites to those of model satellites in the eagle cosmological hydrodynamics simulations. A distribution function (DF) for galactic satellites is constructed from eagle using specific angular momentum and specific energy, which are scaled so as to be independent of host halo mass. In this two-dimensional space, the orbital properties of satellite galaxies vary according to the host halo mass. The halo mass can be inferred by calculating the likelihood that the observed satellite population is drawn from this DF. Our method is robustly calibrated on mock eagle systems. We validate it by applying it to the completely independent suite of 30 auriga high-resolution simulations of MW-like galaxies: the method accurately recovers their true mass and associated uncertainties. We then apply it to 10 classical satellites of the MW with six-dimensional phase-space measurements, including updated proper motions from the Gaia satellite. The mass of the MW is estimated to be $M_{200}^{\rm {MW}}=1.17_{-0.15}^{+0.21}\times 10^{12}\, \mathrm{M}_{\odot }$ (68 per cent confidence limits). We combine our total mass estimate with recent mass estimates in the inner regions of the Galaxy to infer an inner dark matter (DM) mass fraction $M^\rm {DM}(\lt 20~\rm {kpc})/M^\rm {DM}_{200}=0.12$, which is typical of ${\sim }10^{12}\, \mathrm{M}_{\odot }$ lambda cold dark matter haloes in hydrodynamical galaxy formation simulations. Assuming a Navarro, Frenk and White (NFW) profile, this is equivalent to a halo concentration of $c_{200}^{\rm {MW}}=10.9^{+2.6}_{-2.0}$.

Tracing the Galactic Halo: Obtaining Bayesian mass estimates of the Galaxy in the presence of incomplete data

The mass and cumulative mass profile of the Galaxy are its most fundamental properties. Estimating these properties, however, is not a trivial problem. We rely on the kinematic information from Galactic satellites such as globular clusters and dwarf galaxies, and this data is incomplete and subject to measurement uncertainty. In particular, the complete 3D velocity vectors of objects are sometimes unavailable, and there may be selection biases due to both the distribution of objects around the Galaxy and our measurement position. On the other hand, the uncertainties of these data are fairly well understood. Thus, we would like to incorporate these uncertainties and the incomplete data into our estimate of the Milky Way's mass. The Bayesian paradigm offers a way to deal with both the missing kinematic data and measurement errors using a hierarchical model. An application of this method to the Milky Way halo mass profile, using the kinematic data for globular clusters and dwarf satellites, is shown.

Probing non-spherical dark halos in the Galactic dwarf satellites

We construct axisymmetric mass models for dwarf spheroidal (dSph) galaxies in the Milky Way to obtain realistic limits on the non-spherical structure of their dark halos. This is motivated by the fact that the observed luminous parts of the dSphs are actually non-spherical and cold dark matter models predict non-spherical virialized dark halos on sub-galactic scales. Applying these models to line-of-sight velocity dispersion profiles along three position angles in six Galactic satellites, we find that the best fitting cases for most of the dSphs yield not spherical but oblate and flattened dark halos. We also find that the mass of the dSphs enclosed within inner 300 pc varies depending on their total luminosities, contrary to the conclusion of previous spherical models. This suggests the importance of considering non-spherical shapes of dark halos in dSph mass models.

Spikes in the SED and ripples in the outskirts of galaxies

We describe a new method that allows us to quantitatively characterize galactic satellites from analysis of disturbances in outer gas disks, without requiring knowledge of their optical light. We have demonstrated the validity of this method, which we call Tidal Analysis, by applying it to local spirals with known optical companions, including M51 and NGC 1512. These galaxies span the range from having a low mass companion (~ one-hundredth the mass of the primary galaxy) to a fairly massive companion (~ one-third the mass of the primary galaxy). This approach has broad implications for many areas of astrophysics – for the indirect detection of dark matter (or dark matter-dominated dwarf galaxies), and for galaxy evolution in its use as a decipher of the dynamical impact of satellites on galactic disks. Here, we present some preliminary results on the emergent SEDs and images, calculated along the time sequence of these dynamical simulations using the 3-D self-consistent Monte Carlo radiative transfer code RADISHE. We explore star formation prescriptions and how they affect the emergent SEDs and images. Our goal is to identify SED colors that are primarily affected by the galaxy's interaction history, and are not significantly affected by the choice of star formation prescription. If successful, we may be able to utilize the emergent UV-IR SED of the primary galaxy to understand its recent interaction history.