A scaling relation between merger rate of galaxies and their close pair count

We study how to measure the galaxy merger rate from the observed close pair count. Using a high-resolution N-body/SPH cosmological simulation, we find an accurate scaling relation between galaxy pair counts and merger rates down to a stellar mass ratio of about 1:30. The relation explicitly accounts for the dependence on redshift (or time), on pair separation, and on mass of the two galaxies in a pair. With this relation, one can easily obtain the mean merger timescale for a close pair of galaxies. The use of virial masses, instead of stellar masses, is motivated by the fact that the dynamical friction time scale is mainly determined by the dark matter surrounding central and satellite galaxies. This fact can also minimize the error induced by uncertainties in modeling star formation in the simulation. Since the virial mass can be read from the well-established relation between the virial masses and the stellar masses in observation, our scaling relation can be easily applied to observations to obtain the merger rate and merger time scale. For major merger pairs (1:1-1:4) of galaxies above a stellar mass of 4*10^10 M_sun/h at z=0.1, it takes about 0.31 Gyr to merge for pairs within a projected distance of 20 kpc/h with stellar mass ratio of 1:1, while the time taken goes up to 1.6 Gyr for mergers with stellar mass ratio of 1:4. Our results indicate that a single timescale usually used in literature is not accurate to describe mergers with the stellar mass ratio spanning even a narrow range from 1:1 to 1:4.Comment: accepted for publication in Ap

A physical and concise halo model based on the depletion radius

We develop a self-consistent and accurate halo model by partitioning matter according to the depletion radii of haloes. Unlike conventional models that define haloes with the virial radius while relying on a separate exclusion radius or ad-hoc fixes to account for halo exclusion, our model distributes mass across all scales self-consistently. Using a cosmological simulation, we show that our halo definition leads to very simple and intuitive model components, with the one-halo term given by the Einasto profile with no truncation needed, and the halo-halo correlation function following a universal power-law form down to the halo boundary. The universal halo-halo correlation also allows us to easily model the distribution of unresolved haloes as well as diffuse matter. Convolving the halo profile with the halo-halo correlation function, we obtain a complete description of the halo-matter correlation across all scales, which self-consistently accounts for halo exclusion on the transition scale. Mass conservation is explicitly maintained in our model, and the scale dependence of the classical halo bias is easily reproduced. Our model can successfully reconstruct the halo-matter correlation function with percent level accuracy for halo virial masses in the range of $10^{11.5}h^{-1}{\rm M}_{\odot}<M_{\rm vir}<10^{15.35}h^{-1}{\rm M}_{\odot}$ at $z=0$, and covers the radial range of $0.01h^{-1}{\rm Mpc}<r<20h^{-1}{\rm Mpc}$. We also show that our model profile can accurately predict the characteristic depletion radius at the minimum bias and the splash-back radius at the steepest density slope locations.Comment: 19 pages, 19 figure

The mass of our Milky Way

We perform an extensive review of the numerous studies and methods used to determine the total mass of the Milky Way. We group the various methods into seven broad classes, including: i) estimating Galactic escape velocity using high velocity objects; ii) measuring the rotation curve through terminal and circular velocities; iii) modeling halo stars, globular clusters and satellite galaxies with the Spherical Jeans equation and iv) with phase-space distribution functions; v) simulating and modeling the dynamics of stellar streams and their progenitors; vi) modeling the motion of the Milky Way, M31 and other distant satellites under the framework of Local Group timing argument; and vii) measurements made by linking the brightest Galactic satellites to their counterparts in simulations. For each class of methods, we introduce their theoretical and observational background, the method itself, the sample of available tracer objects, model assumptions, uncertainties, limits and the corresponding measurements that have been achieved in the past. Both the measured total masses within the radial range probed by tracer objects and the extrapolated virial masses are discussed and quoted. We also discuss the role of modern numerical simulations in terms of helping to validate model assumptions, understanding systematic uncertainties and calibrating the measurements. While measurements in the last two decades show a factor of two scatters, recent measurements using \textit{Gaia} DR2 data are approaching a higher precision. We end with a detailed discussion of future developments, especially as the size and quality of the observational data will increase tremendously with current and future surveys. In such cases, the systematic uncertainties will be dominant and thus will necessitate a much more rigorous testing and characterization of the various mass determination methods.Comment: invited review published by Science China Physics, Mechanics & Astronom

The multidimensional dependence of halo bias in the eye of a machine: a tale of halo structure, assembly and environment

We develop a novel approach in exploring the joint dependence of halo bias on multiple halo properties using Gaussian process regression. Using a $\Lambda$CDM $N$-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 $V_\mathrm{max}/V_\mathrm{vir}$ is 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 $20\%$ level at $\sim 10\mathrm{Mpc}h^{-1}$. When an environmental density is measured outside $1\mathrm{Mpc}h^{-1}$ 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 $30\%$.Comment: MNRAS accepte