Projets de recherche

Title: Exploring the circumstellar environment by direct imaging at high-contrast: a focus on data-driven approaches and application on VLT/SPHERE-IFS data 

Instructor: Olivier Flasseur (CRAL, Lyon, France)

Short description:

From 4D (x, y, time, lambda) datacubes recorded by the VLT/SPHERE-IFS instrument in total intensity, the goal of this project is threefold:

1. detecting faint point-like sources (e.g., exoplanets, brown dwarfs) at a controlled detection confidence;

2. estimating accurately their astrometry and spectral energy distribution with the associated confidence intervals and inferring some key astrophysical parameters (e.g., effective temperature, surface gravity, metalicity, C/O ratio);

3. reconstructing the flux distribution of spatially resolved and extended objects (circumstellar disks) in the vicinity of the host star. For that purpose, we will investigate advanced processing and optimization methods.

Requirements: Python, Fits viewer (DS9 SAOImage or QFitsView).

Title: Hunting for faint and distant galaxies in near-infrared observations by VLT/SINFONI

Instructor: Jens-Kristian Krogager (CRAL, Lyon, France)

Short description:

The goal of the project is to identify faint emission signatures from galaxies near a bright back-ground quasar and to look for extended emission in the quasar itself. We will model spectral features in 1D and 3D in order to subtract the bright quasar.

Requirements: Python, QFitsView, model fitting

Title: Identifying strongly lensed galaxy candidates from MUSE/VLT observations

Instructor: Johan Richard (CRAL, Lyon, France)

Short description:

The goal of the project is to search for line emitters in MUSE observations of massive galaxy clusters and identify pairs of multiple images which could originate from the same source. We will then use the most convincing candidates to model the mass distribution of the cluster with a very simplified mass model.

Requirements: Python,  Fits viewer (DS9 SAOImage or QFitsView), (optional) Topcat

Title: Measuring Bar Pattern Speed using IFU observation  

Instructor: Kanak Saha (IUCAA, India)

Short description: 

A large fraction of spiral galaxies including our Milky Way host a stellar bar at their central region. These bars are known to rotate with a fixed pattern speed. However, direct measurement of their pattern speed remains a challenging problem, despite IFU observations being available for many such galaxies. This project aims at measuring bar pattern speed utilizing the well-known Tremaine-Weinberg method.

Requirements: Python coding; Photutils package, DS9 SAOImage

Title: Kinematic properties of ionised gas and stars in spiral galaxies

Instructor: Christian Herenz (IUCAA, India)

Short description:

Kinematics of galaxies are not only governed by the gravitational potential, but also by feedback processes from stellar winds and supernovae.  We will perform a kinematical analysis of spiral galaxies using MUSE data.  Our aim is to map differences between stellar kinematics and kinematics of the ionised gas.  Especially, we will visualise differences in rotation speed and velocity dispersion between those consitituents of galaxies. 

Requirements: Python (Anaconda Environment)