CosmoStat – An AIM laboratory @CEA Saclay

Welcome to CosmoStat

The CosmoStat team (LCS) is composed of both cosmologists and computer scientists working together to develop new methods of statistics, signal processing, and apply them to cosmological data set. CosmoStat goals are:

Statistics & Signal Processing: Develop new methods for analyzing astronomical data, and especially in cosmology where the needs of powerful statistical methods are very important.
Cosmology: Analyze and interpret data.
Projects: Participation to important astronomical projects such as Euclid, etc.
Teaching: Teach students and young researchers how to analyze astronomical data.
Dissemination: Take opportunity to disseminate our idea, tools and products in and outside the astronomical field (CEA, CNRS, University, Industry...).
Diversity: Host a diverse group of researchers from all around the world.

From 2012 to 2018, the activity has been mainly driven by two international projects, PLANCK and Euclid, with a increasing involvement with time in Euclid.

CosmoStat News

Checkout all the latest CosmoStat news, events and publications

PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing

Authors: S. Farrens, A. Grigis, L. El Gueddari, Z. Ramzi, Chaithya G. R., S. Starck, B. Sarthou, H. Cherkaoui,...

Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies

Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies Authors: S. Pires, V. Vandenbussche, V. Kansal, R. Bender, L. Blot,...

Euclid : un subtil amalgame pour un résultat cosmologique plus précis

Au terme de trois années de travail, une équipe de la collaboration Euclid, coordonnée par l'Irfu, dévoile une nouvelle méthode...

La quête de l’origine de l’accélération cosmique

Déterminer la cause de l’accélération cosmique est l’un des grands défis de la cosmologie. S’agit-il d’une constante (ΛCDM) ou d’un...

Du machine learning dans l’espace

Clefs CEA n°69 - L'intelligence Artificielle, Novembre 2019. En astrophysique, à l’instar de nombreux autres domaines scientifiques, le machine learning est...