相关论文: Sensitivity Estimation for Dark Matter Subhalos in…

Detecting the dark matter annihilation signal from Galactic substructure, or subhalos, is an important challenge for high-energy gamma-ray experiments. In this paper we discuss detection prospects by combining two different aspects of the…

We present and analyse mock stellar catalogues that match the selection criteria and observables (including uncertainties) of the Gaia satellite data release 2 (DR2). The source are six cosmological high-resolution magneto-hydrodynamic…

This paper presents a machine learning-based method for the detection of the unique gravitational microlensing signatures of extended dark objects, such as boson stars, axion miniclusters and subhalos. We adapt MicroLIA, a machine…

Microlensing events can be used to directly measure the masses of single field stars to a precision of $\sim$1-10\%. The majority of direct mass measurements for stellar and sub-stellar objects typically only come from observations of…

We examine the prospects for detecting gamma-rays from dark matter annihilation in the six most promising dwarf spheroidal (dSph) satellite galaxies of the Milky Way. We use recently-measured velocity dispersion profiles to provide a…

Dark matter subhalos, predicted in large numbers in the cold dark matter scenario, should have an impact on particle dark matter searches. Recent results show that tidal disruption of these objects in computer simulations is over-efficient…

We present a model for the structure of the particle phase space average density ($P^2SAD$) in galactic haloes, introduced recently as a novel measure of the clustering of dark matter. Our model is based on the stable clustering hypothesis…

Dwarf galaxies are small, dark matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter --…

Reducing theoretical uncertainties in Galactic dark matter (DM) searches is an important challenge as several experiments are now delving into the parameter space relevant to popular (particle or not) candidates. Since many DM signal…

We explore how diffuse stellar light and globular clusters (GCs) can be used to trace the matter distribution of their host halo using an observational methodology. For this, we use 117 simulated dark matter (DM) haloes from the $(34.4~\rm…

The local group dwarf spheroidal galaxies (LG dSphs) are among the most promising astrophysical targets for probing the small scale structure of dark matter (DM) subhalos. We describe a method for testing the correspondence between proposed…

Milky Way dwarf spheroidal satellites are a prime target for Dark Matter (DM) indirect searches. There have been recent reassessments of the expected DM gamma-ray signals in case of long-range interactions, commonly known as Sommerfeld…

Modern radio telescope surveys, capable of detecting billions of galaxies in wide-field surveys, have made manual morphological classification impracticable. This applies in particular when the Square Kilometre Array Observatory (SKAO)…

Different models of dark matter can alter the distribution of mass in galaxy clusters in a variety of ways. However, so can uncertain astrophysical feedback mechanisms. Here we present a Machine Learning method that ''learns'' how the…

Upcoming $\gamma$-ray satellites will search for Dark Matter annihilations in Milky Way substructures (or 'clumps'). The prospects for detecting these objects strongly depend on the assumptions made on the distribution of Dark Matter in…

We perform a comprehensive study of Milky Way (MW) satellite galaxies to constrain the fundamental properties of dark matter (DM). This analysis fully incorporates inhomogeneities in the spatial distribution and detectability of MW…

The debris from past merger events is expected and, to some extent, known to populate the stellar halo near the Sun. We aim to identify and characterise such merger debris using Gaia DR3 data supplemented by metallicity and chemical…

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…

We present a detailed analysis of the effect of an observationally determined dark matter (DM) velocity distribution function (VDF) of the Milky Way (MW) on DM direct detection rates. We go beyond local kinematic tracers and use rotation…

Understanding the impact of halo properties beyond halo mass on the clustering of galaxies (namely galaxy assembly bias) remains a challenge for contemporary models of galaxy clustering. We explore the use of machine learning to predict the…