Looking for exoplanets molecular content: inverse problem approach to optimize data reduction

10/01/2022 – 11/01/2022 all-day

Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : Institut de Planétologie et d’Astrophysique de Gr
Durée : >4 mois
Contact : philippe.delorme@univ-grenoble-alpes.fr
Date limite de publication : 2022-01-10

Contexte :
Exoplanets are planets orbiting other stars than the Sun. Since their luminosity is orders of magnitude smaller than their host star, finding them and characterizing their properties is extremely challenging and necessitate very careful data analysis and data calibration. For years astronomers used empirical calibrations to improve data quality, but recent publications by data scientists have shown that an inverse problem approach with minimal empirical information can improve data reduction, especially for integrated field spectrographs, that produce both an image and a spectra for each pixel in the image. Notably it does remove very efficiently systematic errors from the early data reductions steps, thus improving the full reduction chain. These improvements are key to allows the most advanced data algorithms to reveal their full potential, enabling reliable analysis of the molecular content of exoplanet atmospheres. With the higher spectral resolution of instruments such as MUSE, SINFONI and soon ERIS, we can detect spectral lines associated with individual molecules and perform molecular mapping to improve the detection and characterization of exoplanets. In fine, each of these developments will help in the coming years with the ultimate goal to search for life in the atmospheres of Earth-like planets with the next generation of extremely large telescopes.

Sujet :
The work will take place within the ANR project FRAME, that aims at finding accreting young exoplanets. The intern will be based at IPAG in Grenoble, home of the FRAME team and will also have the opportunity to collaborate with researchers from CRAL in Lyon. The intern is expected to read and take the time to understand the inverse problem approach of reducing direct imaging data targeted at finding exoplanets. The existing algorithm (PIC 1) is applied to low resolution integrated field spectrographs, and the aim of the internship is to adapt the algorithm to higher resolution instruments that can characterize the molecular content of exoplanet atmospheres. The intern will have access to raw and reduced data of such higher resolution instruments (notably SINFONI and ERIS), and with the help of his/her supervisor he/she is expected to develop a data reduction tool adapted to higher spectral resolution instruments and if possible, to improve it using information coming from astrophysical and detector physics knowledge of the problem. The supervisor will also provide benchmark datasets, some including real planets, reduced with the “traditional” empirical approach, against which to estimate advantages and drawbacks of each approach. Since this work is an open research question, unexpected issues will probably arise, and the longer the internship, the most likely significant results can be achieved. However we do not expect the intern to fully resolve the problem during the course of the internship, and we have funding for a PhD in continuation of this project, also involving observations, improvement of advanced data analysis tools and direct application to look for massive exoplanets and characterize their atmospheres.

Profil du candidat :
Niveau M2 ou équivalent

Formation et compétences requises :
– curiosity
– correct linear algebra basis
– enthusiasm to deal with open questions
– Interest for astrophysics

Adresse d’emploi :
Institut de Planétologie et d’Astrophysique de Grenoble
414, Rue de la Piscine
Domaine Universitaire
38400 St-Martin d’Hères