Related papers: Galaxy Rotation Curve Fitting Using Machine Learni…
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using…
Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as…
[Abridged] The S-stars motion around the Galactic center (Sgr A*) implies the existence of a compact source with a mass of about $4\times 10^6 M_\odot$, traditionally assumed to be a massive black hole (BH). Important for any model is the…
Studying the kinematics and mass modelling of galaxies from HI 21 cm data provides valuable insights into the properties of both the baryonic components and the dark matter halo in nearby galaxies. Despite many observational studies, mass…
We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics using reinforcement learning. The most important halo…
This paper is the third in a series on submillimeter galaxy magnification bias, focusing on the tomographic scenario. It refines the methodology used to constrain the halo occupation distribution model and cosmological parameters within a…
We apply a statistical deconvolution of the parallax errors based on Lucy's inversion method (LIM) to the Gaia-DR3 sources to measure their three dimensional velocity components in the range of Galactocentric distances $R$ between 8 kpc and…
Morphological classification is a key piece of information to define samples of galaxies aiming to study the large-scale structure of the universe. In essence, the challenge is to build up a robust methodology to perform a reliable…
After explaining the motivation for this article, I briefly recapitulate the methods used to determine, somewhat coarsely, the rotation curves of our Milky Way Galaxy and other spiral galaxies, especially in their outer parts, and the…
We present the mass models of 31 spiral and irregular nearby galaxies obtained using hybrid rotation curves (RCs) combining high resolution GHASP Fabry-Perot H$\alpha$ RCs and extended WHISP HI ones together with 3.4 $\mu$m WISE photometry.…
The problem of modeling the distribution of dark matter in galaxies in terms of equilibrium configurations of collisionless self-gravitating quantum particles is considered. We first summarize the pioneering model of a Newtonian…
Current images of the supermassive black hole (SMBH) candidates at the center of our Galaxy and M87 have opened an unprecedented era for studying strong gravity and the nature of relativistic sources. Very-long-baseline interferometry…
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…
We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…
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…
We present a manifestly diffeomorphism-invariant simple model of galaxy dynamics obtained by applying the Dressing Field Method (DFM) to a general-relativistic system comprising the metric and four scalar fields, phenomenologically…
We conducted an analysis of the velocity field of dwarf galaxies in the LITTLE THINGS sample, focusing on deriving 2D velocity maps that encompass both the transverse and radial velocity fields. Within the range of radial distances where…
We use the adiabatic compression theory to build a physically well - motivated Milky Way mass model in agreement with the observational data. The visible mass of the Galaxy is distributed in a spheroidal bulge and a multi - components disc…
A parameterized model of the mass distribution within the Milky Way is fitted to the available observational constraints. The most important single parameter is the ratio of the scale length R_d* of the stellar disk to R0. The disk and…
The Gaia mission has provided the largest ever astrometric chart of the Milky Way. Using it to map the Galactic halo is helpful for disentangling its merger history. The identification of halo stars in Gaia DR2 with reliable distance…