Big band and big data

To understand the nature of dark energy and dark matter and to test Einstein's theory of general relativity, the parameters of the standard model of cosmology must be accurately measured, using data taken with space or ground telescopes. The volume of data acquired poses serious problems with calibration, archival and access as well as with scientific exploitation of the products obtained (images, spectra, catalogues, etc.). The challenge is to analyse these datasets with algorithms capable of revealing signals with a very low noise ratio and utilising the most advanced methodologies: learning techniques, statistical tools, or concepts from harmonic analysis. These challenges have led to the emergence of a community of scientists from different backgrounds (astrophysics, statistics, computing, signal processing and so on). The goal is to promote methodologies, develop new algorithms, disseminate codes, use them for scientific exploitation of data and train young researchers at the crossroads between disciplines. (A.C.)