Related papers: Determining Satellite Infall Times Using Machine L…

Mergers of binary neutron stars (BNSs) emit signals in both the gravitational-wave (GW) and electromagnetic (EM) spectra. Famously, the 2017 multi-messenger observation of GW170817 led to scientific discoveries across cosmology, nuclear…

Context. The environment plays a crucial role in galaxy evolution, particularly for galaxies infalling into clusters. Accurately estimating the infall times of galaxies from observations can significantly enhance our understanding of the…

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 demonstrate that the asymmetric distribution of M31 satellites cannot be produced by tides from the Milky Way as such effects are too weak. However, loosely bound associations and groups of satellites can fall into larger haloes and give…

In this pilot study, we investigate the use of a deep learning (DL) model to temporally evolve the dynamics of gas accreting onto a black hole in the form of a radiatively inefficient accretion flow (RIAF). We have trained a machine to…

The evolution of a dark matter halo in a dark matter only simulation is governed purely byNewtonian gravity, making a clean testbed to determine what halo properties drive its fate.Using machine learning, we predict the survival, mass loss,…

Many observable properties of globular clusters (GCs) provide valuable insights for unveiling the hierarchical assembly of their host galaxy. For the Milky Way (MW) in particular, GCs from different accreted satellite galaxies show distinct…

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain utility from those data. We have compiled, curated,…

Merging satellite and gauge data with machine learning produces high-resolution precipitation datasets, but uncertainty estimates are often missing. We addressed the gap of how to optimally provide such estimates by benchmarking six…

We compare satellite quenched fractions across three cosmological simulation suites (FIREbox, the FIRE-2 zoom-ins, and IllustrisTNG50) and observational datasets from SAGA, ELVES, and the combined satellite population of the Milky Way and…

We make publicly available a catalog of calibrated environmental measures for galaxies in the five 3D-HST/CANDELS deep fields. Leveraging the spectroscopic and grism redshifts from the 3D-HST survey, multi wavelength photometry from…

We investigate the fraction of quenched satellite galaxies in host galaxy groups and clusters using TNG300 in the IllustrisTNG cosmological magnetohydrodynamical simulations. Simulations show that most satellites are quenched after they…

Low-mass satellites around Milky Way (MW)-like galaxies are important probes of small scale structure and galaxy formation. However, confirmation of satellite candidates with distance measurements remains a key barrier to fast progress in…

In this paper, we use a variance-based genetic ensemble (VGE) of Neural Networks (NNs) to detect anomalies in the satellite's historical data. We use an efficient ensemble of the predictions from multiple Recurrent Neural Networks (RNNs) by…

We present new deep, wide-field Large Binocular Telescope (LBT) $g$ and $r$ imaging data from the Smallest Scale of Hierarchy Survey (SSH) revealing previously undetected tidal features and stellar streams in the outskirts of six dwarf…

We apply the empirical galaxy--halo connection model UniverseMachine to dark matter-only zoom-in simulations of isolated Milky Way (MW)--mass halos along with their parent cosmological simulations. This application extends…

Isolated dwarf galaxies are intrinsically faint and difficult to detect. The limited sample size makes it challenging to observationally constrain the physical mechanisms that quench their star formation. To disentangle the quenching…

In the currently favored cosmological paradigm galaxies form hierarchically through the accretion of numerous satellite galaxies. Since the satellites are much less massive than the host halo, they occupy a small fraction of the volume in…

We explore the possibility of inferring the properties of the Galactic neutron star population through machine learning. In particular, in this paper we focus on their dynamical characteristics and show that an artificial neural network is…

The Gaia satellite will observe the positions and velocities of over a billion Milky Way stars. In the early data releases, the majority of observed stars do not have complete 6D phase-space information. In this Letter, we demonstrate the…