相关论文: Weighing the Milky Way and Andromeda with Artifici…

We propose a versatile and accurate method to estimate the halo mass and concentration from the kinematics of satellite galaxies. We construct the 6D phase-space distribution function of satellites from a cosmological simulation based on…

Using a large sample of galaxies taken from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, a suite of hydrodynamic simulations varying both cosmological and astrophysical parameters, we train a…

We introduce a new suite of 1,024 cosmological and hydrodynamical zoom-in simulations of Milky Way-mass halos, run with Cold Dark Matter, as part of the DREAMS Project. Each simulation in the suite has a unique set of initial conditions and…

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233…

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…

We introduce the ARTEMIS simulations, a new set of 42 zoomed-in, high-resolution (baryon particle mass of ~ 2x10^4 Msun/h), hydrodynamical simulations of galaxies residing in haloes of Milky Way mass, simulated with the EAGLE galaxy…

The satellite galaxies of the Local Group provide us with an important probe of galaxy formation, evolution, and cosmology. The two large spirals that dominate this group -- the Milky Way and Andromeda -- are each host to tens of…

We present a new method for determining the Galactic gravitational potential based on forward modeling of tidal stellar streams. We use this method to test the performance of smooth and static analytic potentials in representing realistic…

The recent advent of deep observational surveys of local Milky Way `analogues' and their satellite populations allows us to place the Milky Way in a broader cosmological context and to test models of galaxy formation on small scales. In the…

We use particle data from the Illustris simulation, combined with individual kinematic constraints on the mass of the Milky Way (MW) at specific distances from the Galactic center, to infer the radial distribution of the MW's dark matter…

Near-field observations may provide tight constraints - i.e. "boundary conditions" - on any model of structure formation in the Universe. Detailed observational data have long been available for the Milky Way (e.g. Freeman $\&$…

We present a new measurement of the mass of the Milky Way (MW) based on observed properties of its largest satellite galaxies, the Magellanic Clouds (MCs), and an assumed prior of a {\Lambda}CDM universe. The large, high-resolution Bolshoi…

We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…

The mass assembly of a whole population of sub-Milky Way galaxies is studied by means of hydrodynamical simulations within the $\Lambda$-CDM cosmology. Our results show that while dark halos assemble hierarchically, in stellar mass this…

We perform an analysis of the Cosmic Web as a complex network, which is built on a $\Lambda$CDM cosmological simulation. For each of nodes, which are in this case dark matter halos formed in the simulation, we compute 10 network metrics,…

We investigate machine learning (ML) techniques for predicting the number of galaxies (N_gal) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for…

Stellar streams have proven to be powerful tools for measuring the Milky Way's gravitational potential and hence its dark matter halo. In the coming years, Vera Rubin, Euclid, ARRAKIHS, and NGRST will uncover a plethora of streams around…

We present new limits on the global shape of the dark matter halo in the Andromeda galaxy using and generalizing non-spherical mass models developed by Hayashi & Chiba and compare our results with theoretical predictions of cold dark matter…

We estimate the Milky Way (MW) halo properties using satellite kinematic data including the latest measurements from Gaia DR2. With a simulation-based 6D phase-space distribution function (DF) of satellite kinematics, we can infer halo…

The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large datasets becoming available in the near future, we develop a likelihood-free Deep Learning technique…