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The inference of the Milky Way halo mass requires modelling the phase space structure of dynamical tracers, with different tracers following different models and having different levels of sensitivity to the halo mass. For steady-state models, deviations from steady-state in the tracer distribution lead to an irreducible stochastic bias. This bias is small for satellite galaxies and dark matter particles, but as large as a factor of 2 for halo stars. This is consistent with the picture that satellite galaxies closely trace the underlying phase space distribution of dark matter particles, while halo stars are less phase-mixed. As a result, the use of only ~100 satellite galaxies can achieve a significantly higher accuracy than that achievable with a much larger sample of halo stars. [ABSTRACT FROM AUTHOR]

We investigate the angular and kinematic distributions of satellite galaxies around a large sample of bright isolated primaries in the spectroscopic and photometric catalogues of the Sloan Digital Sky Survey (SDSS). We detect significant anisotropy in the spatial distribution of satellites. To test whether this anisotropy could be related to the rotating discs of satellites recently found by Ibata et al. in a sample of SDSS galaxies, we repeat and extend their analysis. Ibata et al. found an excess of satellites on opposite sides of their primaries having anticorrelated radial velocities. We find that this excess is sensitive to small changes in the sample selection criteria which can greatly reduce its significance. In addition, we find no evidence for correspondingly correlated velocities for satellites observed on the same side of their primaries, which would be expected for rotating discs of satellites. We conclude that the detection of rotating planes of satellites in the observational sample of Ibata et al. is not robust to changes in the sample selection criteria. We compare our data to the A cold dark matter Millennium simulations populated with galaxies according to the semi-analytic model of Guo et al. We find excellent agreement with the spatial distribution of satellites in the SDSS data and the lack of a strong signal from coherent rotation. [ABSTRACT FROM AUTHOR]

We use the Eighth Data Release of the Sloan Digital Sky Survey (SDSS/DR8) galaxy sample to study the radial distribution of satellite galaxies around isolated primaries, comparing to semi-analytic models of galaxy formation based on the Millennium and Millennium-II simulations. SDSS satellites behave differently around high- and low-mass primaries: those orbiting objects with M* > 1011 M⊙ are mostly red and are less concentrated towards their host than the inferred dark matter halo, an effect that is very pronounced for the few blue satellites. On the other hand, less massive primaries have steeper satellite profiles that agree quite well with the expected dark matter distribution and are dominated by blue satellites, even in the inner regions where strong environmental effects are expected. In fact, such effects appear to be strong only for primaries with M* > 1011 M⊙. This behaviour is not reproduced by current semi-analytic simulations, where satellite profiles always parallel those of the dark matter and satellite populations are predominantly red for primaries of all masses. The disagreement with SDSS suggests that environmental effects are too efficient in the models. Modifying the treatment of environmental and star formation processes can substantially increase the fraction of blue satellites, but their radial distribution remains significantly shallower than observed. It seems that most satellites of low-mass primaries can continue to form stars even after orbiting within their joint halo for 5 Gyr or more. [ABSTRACT FROM AUTHOR]

We study the abundance of satellite galaxies as a function of primary stellar mass using the Sloan Digital Sky Survey/Data Release 7 (SDSS/DR7) spectroscopic catalogue. In contrast with previous studies, which focused mainly on bright primaries, our central galaxies span a wide range of stellar mass, 107.5  Mpri*/M⊙  1011, from dwarfs to central cluster galaxies. Our analysis confirms that the average number of satellites around bright primaries, when expressed in terms of satellite-to-primary stellar mass ratio (msat*/M*pri), is a strong function of Mpri*. On the other hand, satellite abundance is largely independent of primary mass for dwarf primaries (Mpri* < 1010 M⊙). These results are consistent with galaxy formation models in the Λ cold dark matter (ΛCDM) scenario. We find excellent agreement between SDSS data and semianalytic mock galaxy catalogues constructed from the Millennium-II Simulation. Satellite galaxies trace dark matter substructure in ΛCDM, so satellite abundance reflects the dependence on halo mass, M200, of both substructure and galaxy stellar mass (M*). Since dark matter substructure is almost scale free, the dependence of satellite abundance on primary mass results solely from the well-defined characteristic mass in the galaxy mass-halo mass relation. On dwarf galaxy scales, where models predict a power-law scaling, M*∝M2.5200, similarity is preserved and satellite abundance is independent of primary mass. For primaries brighter than the characteristic mass of the M*–M200 relation, satellite abundance increases strongly with primary mass. Our results provide strong support for the steep, approximately power-law dependence of dwarf galaxy mass on halo mass envisioned in ΛCDM galaxy formation models. [ABSTRACT FROM PUBLISHER]

We investigate the importance of various dynamical features in predicting the dynamical state (ds) of galaxy clusters, based on the Random Forest (RF) machine-learning approach. We use a large sample of galaxy clusters from the Three Hundred Project of hydrodynamical zoomed-in simulations, and construct dynamical features from the raw data as well as from the corresponding mock maps in the optical, X-ray, and Sunyaev–Zel'dovich (SZ) channels. Instead of relying on the impurity based feature importance of the RF algorithm, we directly use the out-of-bag (oob) scores to evaluate the importance of individual features and different feature combinations. Among all the features studied, we find the virial ratio, η, to be the most important single feature. The features calculated directly from the simulations and in three dimensions carry more information on the ds than those constructed from the mock maps. Compared with the features based on X-ray or SZ maps, features related to the centroid positions are more important. Despite the large number of investigated features, a combination of up to three features of different types can already saturate the score of the prediction. Lastly, we show that the most sensitive feature η is strongly correlated with the well-known half-mass bias in dynamical modelling. Without a selection in ds , cluster haloes have an asymmetric distribution in η, corresponding to an overall positive half-mass bias. Our work provides a quantitative reference for selecting the best features to discriminate the ds  of galaxy clusters in both simulations and observations. [ABSTRACT FROM AUTHOR]

Using hydrodynamical simulations, we study how well the underlying gravitational potential of a galaxy cluster can be modelled dynamically with different types of tracers. In order to segregate different systematics and the effects of varying estimator performances, we first focus on applying a generic minimal assumption method (oPDF) to model the simulated haloes using the full 6D phase-space information. We show that the halo mass and concentration can be recovered in an ensemble unbiased way, with a stochastic bias that varies from halo to halo, mostly reflecting deviations from steady state in the tracer distribution. The typical systematic uncertainty is ∼0.17 dex in the virial mass and ∼0.17 dex in the concentration as well when dark matter (DM) particles are used as tracers. The dynamical state of satellite galaxies are close to that of DM particles, while intracluster stars are less in a steady state, resulting in an ∼0.26-dex systematic uncertainty in mass. Compared with galactic haloes hosting Milky-Way-like galaxies, cluster haloes show a larger stochastic bias in the recovered mass profiles. We also test the accuracy of using intracluster gas as a dynamical tracer modelled through a generalized hydrostatic equilibrium equation, and find a comparable systematic uncertainty in the estimated mass to that using DM. Lastly, we demonstrate that our conclusions are largely applicable to other steady-state dynamical models including the spherical Jeans equation, by quantitatively segregating their statistical efficiencies and robustness to systematics. We also estimate the limiting number of tracers that leads to the systematics-dominated regime in each case. [ABSTRACT FROM AUTHOR]

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 |$c_{200}^{\rm {MW}}=10.9^{+2.6}_{-2.0}$|⁠. [ABSTRACT FROM AUTHOR]

We develop a novel approach in exploring the joint dependence of halo bias on multiple halo properties using Gaussian process regression. Using a lambda cold dark matter N -body simulation, we carry out a comprehensive study of the joint bias dependence on halo structure, formation history, and environment. We show that the bias is a multivariate function of halo properties that falls into three regimes. For massive haloes, halo mass explains the majority of bias variation. For early-forming haloes, bias depends sensitively on the recent mass accretion history. For low-mass and late-forming haloes, bias depends more on the structure of a halo such as its shape and spin. Our framework enables us to convincingly prove that V max/ V viris a lossy proxy of formation time for bias modelling, whereas the mass, spin, shape, and formation time variables are non-redundant with respect to each other. Combining mass and formation time largely accounts for the mass accretion history dependence of bias. Combining all the internal halo properties fully accounts for the density profile dependence inside haloes, and predicts the clustering variation of individual haloes to a |$20{{\ \rm per\ cent}}$| level at |${\sim } 10\,{\rm Mpc}\, h^{-1}$|⁠. When an environmental density is measured outside |$1\,{\rm Mpc}\, h^{-1}$| from the halo centre, it outperforms and largely accounts for the bias dependence on the internal halo structure, explaining the bias variation above a level of |$30{{\ \rm per\ cent}}$|⁠. [ABSTRACT FROM AUTHOR]

Observationally, the fraction of blue satellite galaxies decreases steeply with host halo mass, and their radial distribution around central galaxies is significantly shallower in massive (M* ≥ 1011 M⊙) than in Milky Way-like systems. Theoretical models, based primarily on semi-analytical techniques, have had a long-standing problem with reproducing these trends, instead predicting too few blue satellites in general but also estimating a radial distribution that is too shallow, regardless of primary mass. In this Letter, we use the Illustris cosmological simulation to study the properties of satellite galaxies around isolated primaries. For the first time, we find good agreement between theory and observations. We identify the main source of this success relative to earlier work to be a consequence of the large gas contents of satellites at infall, a factor ∼5–10 times larger than in semi-analytical models. Because of their relatively large gas reservoirs, satellites can continue to form stars long after infall, with a typical time-scale for star-formation to be quenched ∼2 Gyr in groups but more than ∼5 Gyr for satellites around Milky Way-like primaries. The gas contents we infer are consistent with z = 0 observations of H i gas in galaxies, although we find large discrepancies among reported values in the literature. A testable prediction of our model is that the gas-to-stellar mass ratio of satellite progenitors should vary only weakly with cosmic time. [ABSTRACT FROM PUBLISHER]