Téléphone : 04 92 00 30 62
Durée : 3 mois
Lieu : mont-gros
Financement : Demande de financement au laboratoire
Domaine : Cosmologie
Niveau d’études : Master 2
Désignation du projet : Modelling observed stellar streams around the Milky Way
Résumé : The standard model of cosmology predicts a hierarchical galaxy formation process in which most of the stellar mass in galaxy halos has been accreted by infall of smaller objects. In the outer regions of the galactic halo, dynamical times are long and accreted material remains coherent for many billions of years in the form of streams. These observed stellar streams are therefore powerful probes of the formation and evolution of galaxies: in addition to providing direct evidence of accretion, the observed properties of these substructures contain a wealth of information on both their progenitors and the host galaxy. The apparent width and velocity dispersion of globular cluster streams can reveal the amount of clumpiness of the dark matter halo. In addition, the stars from disrupted satellites approximately follow, and therefore trace, the orbit of their progenitor, which provides an estimate of the mass and morphology of the potential enclosed within the o rbit.
With the advent of wide-field photometric observations and surveys, many such streams have been detected in the Galactic halo. As a result of their different accretion history, orbits, and progenitors, the streams present a broad variety of physical and dynamical properties.
The objective of the project is to design and run simulations of globular cluster (and dwarf galaxy) accretion and disruption in the halo of a toy galaxy. By varying various parameters such as the shape of the gravitational potential, the type of orbit, and the properties of the progenitors, the student will generate a series of model stellar streams that will be compared to known streams in the Milky Way in order to constrain the origin of their diverse properties. The student will learn about N-body simulations, galaxy formation, and programming on GPUs.