Near-Field Limits on the Role of Faint Galaxies in Cosmic Reionization

Reionizing the Universe with galaxies appears to require significant star formation in low-mass halos at early times, while local dwarf galaxy counts tell us that star formation has been minimal in small halos around us today. Using simple models and the ELVIS simulation suite, we show that reionization scenarios requiring appreciable star formation in halos with $M_{\rm vir} \approx 10^{8}\,M_{\odot}$ at $z=8$ are in serious tension with galaxy counts in the Local Group. This tension originates from the seemingly inescapable conclusion that 30 - 60 halos with $M_{\rm vir} > 10^{8}\,M_{\odot}$ at $z=8$ will survive to be distinct bound satellites of the Milky Way at $z = 0$. Reionization models requiring star formation in such halos will produce dozens of bound galaxies in the Milky Way's virial volume today (and 100 - 200 throughout the Local Group), each with $\gtrsim 10^{5}\,M_{\odot}$ of old stars ($\gtrsim 13$ Gyr). This exceeds the stellar mass function of classical Milky Way satellites today, even without allowing for the (significant) post-reionization star formation observed in these galaxies. One possible implication of these findings is that star formation became sharply inefficient in halos smaller than $\sim 10^9 \,M_{\odot}$ at early times, implying that the high-$z$ luminosity function must break at magnitudes brighter than is often assumed (at ${\rm M_{UV}} \approx -14$). Our results suggest that JWST (and possibly even HST with the Frontier Fields) may realistically detect the faintest galaxies that drive reionization. It remains to be seen how these results can be reconciled with the most sophisticated simulations of early galaxy formation at present, which predict substantial star formation in $M_{\rm vir} \sim 10^8 \, M_{\odot}$ halos during the epoch of reionization.Comment: 6 pages, 4 figures; minor updates. Published in MNRAS Letter

ELVIS: Exploring the Local Volume in Simulations

We introduce a set of high-resolution dissipationless simulations that model the Local Group (LG) in a cosmological context: Exploring the Local Volume in Simulations (ELVIS). The suite contains 48 Galaxy-size halos, each within high-resolution volumes that span 2-5 Mpc in size, and each resolving thousands of systems with masses below the atomic cooling limit. Half of the ELVIS galaxy halos are in paired configurations similar to the Milky Way (MW) and M31; the other half are isolated, mass-matched analogs. We find no difference in the abundance or kinematics of substructure within the virial radii of isolated versus paired hosts. On Mpc scales, however, LG-like pairs average almost twice as many companions and the velocity field is kinematically hotter and more complex. We present a refined abundance matching relation between stellar mass and halo mass that reproduces the observed satellite stellar mass functions of the MW and M31 down to the regime where incompleteness is an issue, $M_\star \sim 5\times 10^5 \, M_\odot$. Within a larger region spanning approximately 3 Mpc, the same relation predicts that there should be $\sim$ 1000 galaxies with $M_\star > 10^{3}\,M_\odot$ awaiting discovery. We show that up to 50% of halos within 1 Mpc of the MW or M31 could be systems that have previously been within the virial radius of either giant. By associating never-accreted halos with gas-rich dwarfs, we show that there are plausibly 50 undiscovered dwarf galaxies with HI masses $> 10^5\,M_\odot$ within the Local Volume. The radial velocity distribution of these predicted gas-rich dwarfs can be used to inform follow-up searches based on ultra-compact high-velocity clouds found in the ALFALFA survey.Comment: 22 pages, 19 figures, 3 tables; v2 -- accepted to MNRAS. Movies, images, and data are available at http://localgroup.ps.uci.edu/elvi

On the stark difference in satellite distributions around the Milky Way and Andromeda

We compare spherically-averaged radial number counts of bright (> 10^5 Lsun) dwarf satellite galaxies within 400 kpc of the Milky Way (MW) and M31 and find that the MW satellites are much more centrally concentrated. Remarkably, the two satellite systems are almost identical within the central 100 kpc, while M31 satellites outnumber MW satellites by about a factor of four at deprojected distances spanning 100 - 400 kpc. We compare the observed distributions to those predicted for LCDM suhbalos using a suite of 44 high-resolution ~10^12 halo zoom simulations, 22 of which are in pairs like the MW and M31. We find that the radial distribution of satellites around M31 is fairly typical of those predicted for subhalos, while the Milky Way's distribution is more centrally concentrated that any of our simulated LCDM halos. One possible explanation is that our census is bright (> 10^5 Lsun) MW dwarf galaxies is significantly incomplete beyond ~ 100 kpc of the Sun. If there were ~8 - 20 more bright dwarfs orbiting undetected at 100 - 400 kpc, then the Milky Way's radial distribution would fall within the range expected from subhalo distributions and alos look very much like the known M31 system. We use our simulations to demonstrate that there is enough area left unexplored by the Sloan Digital Sky Survey and its extensions that the discovery of ~10 new bright dwarfs is not implausible given the expected range of angular anisotropy of subhalos in the sky.Comment: 10 pages, 8 figures, submitted to MNRA

Organized Chaos: Scatter in the relation between stellar mass and halo mass in small galaxies

We use Local Group galaxy counts together with the ELVIS N-body simulations to explore the relationship between the scatter and slope in the stellar mass vs. halo mass relation at low masses, $M_\star \simeq 10^5 - 10^8 M_\odot$. Assuming models with log-normal scatter about a median relation of the form $M_\star \propto M_\mathrm{halo}^\alpha$, the preferred log-slope steepens from $\alpha \simeq 1.8$ in the limit of zero scatter to $\alpha \simeq 2.6$ in the case of $2$ dex of scatter in $M_\star$ at fixed halo mass. We provide fitting functions for the best-fit relations as a function of scatter, including cases where the relation becomes increasingly stochastic with decreasing mass. We show that if the scatter at fixed halo mass is large enough ($\gtrsim 1$ dex) and if the median relation is steep enough ($\alpha \gtrsim 2$), then the "too-big-to-fail" problem seen in the Local Group can be self-consistently eliminated in about $\sim 5-10\%$ of realizations. This scenario requires that the most massive subhalos host unobservable ultra-faint dwarfs fairly often; we discuss potentially observable signatures of these systems. Finally, we compare our derived constraints to recent high-resolution simulations of dwarf galaxy formation in the literature. Though simulation-to-simulation scatter in $M_\star$ at fixed $M_\mathrm{halo}$ is large among separate authors ($\sim 2$ dex), individual codes produce relations with much less scatter and usually give relations that would over-produce local galaxy counts.Comment: 15 pages, 6 figures, 1 table. Accepted for publication into MNRA

Can Feedback Solve the Too Big to Fail Problem?

The observed central densities of Milky Way dwarf spheroidal galaxies (dSphs) are significantly lower than the densities of the largest (Vmax about 35 km/s) subhalos found in dissipationless simulations of Galaxy-size dark matter hosts. One possible explanation is that gas removal from feedback can lower core densities enough to match observations. We model the dynamical effects of supernova feedback through the use of a time-varying central potential in high resolution, idealized numerical simulations and explore the resulting impact on the mass distributions of dwarf dark matter halos. We find that in order to match the observed central masses of M_star about 10^6 M_sun dSphs, the energy equivalent of more than 40,000 supernovae must be delivered with 100% efficiency directly to the dark matter. This energy requirement exceeds the number of supernovae that have ever exploded in most dSphs for typical initial mass functions. We also find that, per unit energy delivered and per cumulative mass removed from the galaxy, single blow-out events are more effective than repeated small bursts in reducing central dark matter densities. We conclude that it is unlikely that supernova feedback alone can solve the "Too Big to Fail" problem for Milky Way subhalos.Comment: 9 pages, 6 figures; v2 -- accepted to MNRA

Too Big to Fail in the Local Group

We compare the dynamical masses of dwarf galaxies in the Local Group (LG) to the predicted masses of halos in the ELVIS suite of $\Lambda$CDM simulations, a sample of 48 Galaxy-size hosts, 24 of which are in paired configuration similar to the LG. We enumerate unaccounted-for dense halos ($V_\mathrm{max} \gtrsim 25$ km s$^{-1}$) in these volumes that at some point in their histories were massive enough to have formed stars in the presence of an ionizing background ($V_\mathrm{peak} > 30$ km s$^{-1}$). Within 300 kpc of the Milky Way, the number of unaccounted-for massive halos ranges from 2 - 25 over our full sample. Moreover, this "too big to fail" count grows as we extend our comparison to the outer regions of the Local Group: within 1.2 Mpc of either giant we find that there are 12-40 unaccounted-for massive halos. This count excludes volumes within 300 kpc of both the MW and M31, and thus should be largely unaffected by any baryonically-induced environmental processes. According to abundance matching -- specifically abundance matching that reproduces the Local Group stellar mass function -- all of these missing massive systems should have been quite bright, with $M_\star > 10^6M_\odot$. Finally, we use the predicted density structure of outer LG dark matter halos together with observed dwarf galaxy masses to derive an $M_\star-V_\mathrm{max}$ relation for LG galaxies that are outside the virial regions of either giant. We find that there is no obvious trend in the relation over three orders of magnitude in stellar mass (a "common mass" relation), from $M_\star \sim 10^8 - 10^5 M_\odot$, in drastic conflict with the tight relation expected for halos that are unaffected by reionization. Solutions to the too big to fail problem that rely on ram pressure stripping, tidal effects, or statistical flukes appear less likely in the face of these results.Comment: 16 pages, 14 figures, 2 tables, submitted to MNRA

Chasing Accreted Structures within Gaia DR2 using Deep Learning

In previous work, we developed a deep neural network classifier that only relies on phase-space information to obtain a catalog of accreted stars based on the second data release of Gaia (DR2). In this paper, we apply two clustering algorithms to identify velocity substructure within this catalog. We focus on the subset of stars with line-of-sight velocity measurements that fall in the range of Galactocentric radii r ∈ [6.5, 9.5] kpc and vertical distances |z|<3 kpc. Known structures such as Gaia Enceladus and the Helmi stream are identified. The largest previously unknown structure, Nyx, is a vast stream consisting of at least 200 stars in the region of interest. This study displays the power of the machine-learning approach by not only successfully identifying known features but also discovering new kinematic structures that may shed light on the merger history of the Milky Way

Running with BICEP2: Implications for Small-Scale Problems in CDM

The BICEP2 results, when interpreted as a gravitational wave signal and combined with other CMB data, suggest a roll-off in power towards small scales in the primordial matter power spectrum. Among the simplest possibilities is a running of the spectral index. Here we show that the preferred level of running alleviates small-scale issues within the $\Lambda$CDM model, more so even than viable WDM models. We use cosmological zoom-in simulations of a Milky Way-size halo along with full-box simulations to compare predictions among four separate cosmologies: a BICEP2-inspired running index model ($\alpha_s$ = -0.024), two fixed-tilt $\Lambda$CDM models motivated by Planck, and a 2.6 keV thermal WDM model. We find that the running BICEP2 model reduces the central densities of large dwarf-size halos ($V_\mathrm{max}$ ~ 30 - 80 km s$^{-1}$) and alleviates the too-big-to-fail problem significantly compared to our adopted Planck and WDM cases. Further, the BICEP2 model suppresses the count of small subhalos by ~50% relative to Planck models, and yields a significantly lower "boost" factor for dark matter annihilation signals. Our findings highlight the need to understand the shape of the primordial power spectrum in order to correctly interpret small-scale data.Comment: 10 pages, 8 figures, 2 tables, published in MNRA

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

We identify subhalos in dark matter-only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)-mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion, and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an $85\%$ out-of-bag classification score. We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.Comment: 20 pages, 14 figures. Updated to published version. Code available at https://github.com/ollienad/subhalo_randomfores