On the mass of the Local Group

We use recent proper motion measurements of the tangential velocity of M31, along with its radial velocity and distance, to derive the likelihood of the sum of halo masses of the Milky Way and M31. This is done using a sample halo pairs in the Bolshoi cosmological simulation of $Lambda$CDM cosmology selected to match properties and environment of the Local Group. The resulting likelihood gives estimate of the sum of masses of $M_{rm MW,200}+M_{rm M31,200}=$ $2.40_{-1.05}^{+1.95}times10^{12},M_{odot}$ ($90%$ confidence interval). This estimate is consistent with individual mass estimates for the Milky Way and M31 and is consistent, albeit somewhat on the low side, with the mass estimated using the timing argument. We show that although the timing argument is unbiased on average for all pairs, for pairs constrained to have radial and tangential velocities similar to that of the Local Group the argument overestimates the sum of masses by a factor of $1.6$. Using similar technique we estimate the total dark matter mass enclosed within $1$ Mpc from the Local Group barycenter to be $M_{rm LG}(r<1, {rm Mpc})=4.2_{-2.0}^{+3.4}times10^{12},M_{odot}$ ($90%$ confidence interval).

Satellites in MW-like hosts: Environment dependence and close pairs

Previous studies showed that an estimate of the likelihood distribution of the Milky Way halo mass can be derived using the properties of the satellites similar to the Large and Small Magellanic Clouds (LMC and SMC). However, it would be straightforward to interpret such an estimate only if the properties of the Magellanic Clouds (MCs) are fairly typical and are not biased by the environment. In this study we explore whether the environment of the Milky Way affects the properties of the SMC and LMC such as their velocities. To test for the effect of the environment, we compare velocity distributions for MC-sized subhalos around Milky Way hosts in a sample selected simply by mass and in the second sample of such halos selected with additional restrictions on the distance to the nearest cluster and the local galaxy density, designed to mimic the environment of the Local Group (LG). We find that satellites in halos in the LG-like environments do have somewhat larger velocities, as compared to the halos of similar mass in the sample without environmental constraints. We derive the host halo likelihood distribution for the samples in the LG-like envirionment and in the control sample and find that the environment does not significantly affect the derived likelihood. We use the updated properties of the SMC and LMC to derive the constraint on the MW halo mass $log{({rm M}_{200} /msol)}=12.06^{+0.31}_{-0.19}$ (90% confidence interval). We also explore the incidence of close pairs with relative velocities and separations similar to those of the LMC and SMC and find that such pairs are quite rare among $Lambda$CDM halos. Taking into account the close separation of the MCs in the Busha et al. 2011 method results in the shift of the MW halo mass estimate to smaller masses, with the peak shifting approximately by a factor of two.[Abridged]

Automated detection of filaments in the large scale structure of the universe

We present a new method to identify large scale filaments and apply it to a cosmological simulation. Using positions of haloes above a given mass as node tracers, we look for filaments between them using the positions and masses of all the remaining dark-matter haloes. In order to detect a filament, the first step consists in the construction of a backbone linking two nodes, which is given by a skeleton-like path connecting the highest local dark matter (DM) density traced by non-node haloes. The filament quality is defined by a density and gap parameters characterising its skeleton, and filament members are selected by their binding energy in the plane perpendicular to the filament. This membership condition is associated to characteristic orbital times; however if one assumes a fixed orbital timescale for all the filaments, the resulting filament properties show only marginal changes, indicating that the use of dynamical information is not critical for the method. We test the method in the simulation using massive haloes($M>10^{14}$h$^{-1}M_{odot}$) as filament nodes. The main properties of the resulting high-quality filaments (which corresponds to $simeq33%$ of the detected filaments) are, i) their lengths cover a wide range of values of up to $150 $h$^{-1}$Mpc, but are mostly concentrated below 50h$^{-1}$Mpc; ii) their distribution of thickness peaks at $d=3.0$h$^{-1}$Mpc and increases slightly with the filament length; iii) their nodes are connected on average to $1.87pm0.18$ filaments for $simeq 10^{14.1}M_{odot}$ nodes; this number increases with the node mass to $simeq 2.49pm0.28$ filaments for $simeq 10^{14.9}M_{odot}$ nodes.