Related papers: Sensitivity Estimation for Dark Matter Subhalos in…

This paper demonstrates that the stellar masses of galaxies in the Galaxy and Mass Assembly (GAMA) survey, originally derived via stellar population synthesis modelling, can be accurately predicted using only their absolute magnitudes and…

The interaction properties of cold dark matter (CDM) particle candidates, such as those of weakly interacting massive particles (WIMPs), generically lead to the structuring of dark matter on scales much smaller than typical galaxies,…

We assess the effectiveness of a non-parametric bias model in generating mock halo catalogues for modified gravity (MG) cosmologies, relying on the distribution of dark matter from either MG or $\Lambda$CDM. We aim to generate halo…

Around one third of the point-like sources in the Fermi-LAT catalogs remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of…

We present a comparison of several Difference Image Analysis (DIA) techniques, in combination with Machine Learning (ML) algorithms, applied to the identification of optical transients associated with gravitational wave events. Each…

We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems…

We compare the measured angular cross-correlation between the Fermi-LAT gamma-ray sky and catalogues of extra-galactic objects with the expected signal induced by weakly interacting massive particle (WIMP) dark matter (DM). We include a…

Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has…

We provide new constraints on the connection between galaxies in the local universe, identified by the Sloan Digital Sky Survey (SDSS), and dark matter halos and their constituent substructures in the $\Lambda$CDM model using WMAP7…

The Dark Energy Survey is able to collect image data of an extremely large number of extragalactic objects, and it can be reasonably assumed that many unusual objects of high scientific interest are hidden inside these data. Due to the…

We show that Global Navigation Satellite Systems (GNSS) and gravimeters on Earth and in space can potentially offer the most accurate direct measurement of local density of near-Earth asteroid-mass Primordial Black Holes (PBHs) and Dark…

We determine the total dynamical matter density in the solar neighbourhood using the second Gaia data release (DR2). The dynamical matter density distribution is inferred in a framework of a Bayesian hierarchical model, which accounts for…

We present a panoramic map of the stellar streams of the Milky Way based upon astrometric and photometric measurements from the Gaia DR2 catalogue. In this first contribution, we concentrate on the halo at heliocentric distances beyond 5…

Any successful model of dark matter must explain the diversity of observed Milky Way (MW) satellite density profiles, from very dense ultrafaints to large, low density satellites such as Crater~II that appear to be larger their anticipated…

Parallaxes measured by the Gaia mission have huge significance for astronomy, but parallaxes in Gaia DR2 are known to have systematic errors that depend on the source position and other quantities. We use the abundant information in faint…

We investigate the claim that the largest subhaloes in high resolution dissipationless cold dark matter (CDM) simulations of the Milky Way are dynamically inconsistent with observations of its most luminous satellites. We find that the…

Dark matter pervades the Solar System, free-streaming at the halo's local Galactic orbital velocity and density. As these objects pass through the Solar system, they perturb gravitationally, and thus very weakly, all nearby inertial masses.…

We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and…

We present a novel method to infer the Dark Matter (DM) content and spatial distribution within galaxies, based on convolutional neural networks trained within state-of-the-art hydrodynamical simulations (Illustris TNG100). The framework we…

We predict the number of black holes with stellar companions that are potentially detectable with Gaia astrometry over the course of its five-year mission. Our model estimates that nearly 2$\times$10$^5$ astrometric binaries hosting black…