Through an examination of recent data on the mass distribution and velocity curve of the Milky Way Galaxy, I produce a new estimate of the dark matter distribution, as well as the overall dark matter content, of our galaxy. Initially, I develop a model of the baryonic mass of the galaxy (i.e. luminous matter and interstellar clouds). This model incorporates three components: an exponential stellar disc and a central stellar bulge, based on the TuorlaHeidelberg model, and a gaseous layer, fit to the gas density distribution data of Olling & Merrifield (2001). Secondly, incorporating recent data, I calculate an updated rotational velocity curve for the galaxy as a function of galactocentric radius. Using this velocity curve, I determine t...
In this work we characterize the distribution of Dark Matter (DM) in the Milky Way (MW), and its unc...
International audienceIn this work we characterize the distribution of Dark Matter (DM) in the Milky...
We develop a novel Bayesian methodology aimed at reliably and precisely inferring the distribution o...
Mapping the dark matter distribution across our Galaxy represents a central challenge for the near f...
The distribution of dark matter in the Milky Way is a crucial input for ongoing studies in cosmology...
The ubiquitous presence of dark matter in the Universe is today a central tenet in modern cosmology ...
An accurate knowledge of the dark matter distribution in the Milky Way is of crucial importance for ...
Recent estimates indicate that dark matter represents 85% of the total matter in the Universe. Its p...
A wealth of recent observational studies shows the dark matter in the Milky Way to have the followin...
I review current efforts to measure the mean density of dark matter near the Sun. This encodes valua...
We derive new constraints on the mass of the Milky Way's dark matter halo, based on 2401 rigorously ...
Context. The rotation curve, the total mass and the gravitational potential of the Galaxy are sensit...
We show that current microlensing and dynamical observations of the Galaxy permit to set interesting...
In this universe, not all of the matter around us can be readily seen. The further an object is away...
We use particle data from the Illustris simulation, combined with individual kinematic constraints o...
In this work we characterize the distribution of Dark Matter (DM) in the Milky Way (MW), and its unc...
International audienceIn this work we characterize the distribution of Dark Matter (DM) in the Milky...
We develop a novel Bayesian methodology aimed at reliably and precisely inferring the distribution o...
Mapping the dark matter distribution across our Galaxy represents a central challenge for the near f...
The distribution of dark matter in the Milky Way is a crucial input for ongoing studies in cosmology...
The ubiquitous presence of dark matter in the Universe is today a central tenet in modern cosmology ...
An accurate knowledge of the dark matter distribution in the Milky Way is of crucial importance for ...
Recent estimates indicate that dark matter represents 85% of the total matter in the Universe. Its p...
A wealth of recent observational studies shows the dark matter in the Milky Way to have the followin...
I review current efforts to measure the mean density of dark matter near the Sun. This encodes valua...
We derive new constraints on the mass of the Milky Way's dark matter halo, based on 2401 rigorously ...
Context. The rotation curve, the total mass and the gravitational potential of the Galaxy are sensit...
We show that current microlensing and dynamical observations of the Galaxy permit to set interesting...
In this universe, not all of the matter around us can be readily seen. The further an object is away...
We use particle data from the Illustris simulation, combined with individual kinematic constraints o...
In this work we characterize the distribution of Dark Matter (DM) in the Milky Way (MW), and its unc...
International audienceIn this work we characterize the distribution of Dark Matter (DM) in the Milky...
We develop a novel Bayesian methodology aimed at reliably and precisely inferring the distribution o...