Related papers: Inferring galaxy dark halo properties from visible…
The nature of dark matter (DM) is still under intense debate. Sub-galactic scales are particularly critical, as different, currently viable DM models make diverse predictions on the expected abundance and density profile of DM haloes on…
Recently, it has been shown that electrons and positrons from dark matter (DM) annihilations provide an excellent fit to the Fermi, PAMELA, and HESS data. Using this DM model, which requires an enhancement of the annihilation cross section…
Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS}…
Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order to answer these questions, two important…
Galaxy-galaxy lensing is a powerful probe of the relation between galaxies and dark matter halos, but its theoretical interpretation requires a careful modeling of various contributions, such as the contribution from central and satellite…
Kinematic studies have produced accurate measurements of the total dark matter mass and mean dark matter density within the optical extent of galaxies, for large samples of objects. Here we consider theoretical predictions for the latter…
It has been shown that a self-gravitating system of massive keV fermions in thermodynamic equilibrium correctly describes the dark matter (DM) distribution in galactic halos and predicts a denser quantum core towards the center of the…
A precise determination of the local dark matter density and an accurate control over the corresponding uncertainties are of paramount importance for Dark Matter (DM) searches. Using very recent high-resolution numerical simulations of a…
Galaxy-galaxy lensing measures the mean excess surface density DS(r) around a sample of lensing galaxies. We develop a method for combining DS(r) with the galaxy correlation function xi_gg(r) to constrain Omega_m and sigma_8, going beyond…
It is widely recognized that cold dark matter models predict abundant dark matter substructure in halos of all sizes. Galaxy-galaxy lensing provides a unique opportunity to directly measure the presence and the mass of such substructures in…
We use the IllustrisTNG (TNG) cosmological simulations to provide theoretical expectations for the dark matter mass fractions (DMFs) and circular velocity profiles of galaxies. TNG predicts flat circular velocity curves for $z = 0$ Milky…
There is strong astrophysical evidence that dark matter (DM) makes up some 27% of all mass in the universe. Yet, beyond gravitational interactions, little is known about its properties or how it may connect to the Standard Model. Multiple…
The annihilation of huge quantities of captured dark matter (DM) particles inside low-mass stars has been shown to change some of the stellar properties, such as the star's effective temperature or the way the energy is transported…
We explore the impact of a LWDM cosmological scenario on the clustering properties of large-scale structure in the Universe. We do this by extending the halo model. The new development is that we consider two components to the mass density:…
We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…
Cold dark matter subhalos are expected to populate galaxies in numbers. If dark matter self-annihilates, these objects turn into prime targets for indirect searches, in particular with gamma-ray telescopes. Incidentally, the Fermi-LAT…
Gravitational lensing is a powerful tool for constraining substructure in the mass distribution of galaxies, be it from the presence of dark matter sub-halos or due to physical mechanisms affecting the baryons throughout galaxy evolution.…
For a galaxy, given its observed rotation curve, can one directly infer parameters of the dark matter density profile (such as dark matter particle mass $m$, scaling parameter $s$, core-to-envelope transition radius $r_t$ and NFW scale…
We investigate the ability of machine learning to infer the virial mass ($M_{\rm vir}$) and the scale radius ($r_{\rm s}$) of galaxy clusters from their observables. Using the Uchuu--UniverseMachine galaxy catalog at $z=0.093$, we generate…
Dark matter (DM) constitutes around a 25% of the Universe, while baryons only a 4%. DM can be reasonably assumed to be made of particles, and many theories (Super-symmetry, Universal Extra Dimensions, etc.) predict Weakly Interacting…