Speaker
Description
The quest for primordial B-mode polarisation in the cosmic microwave background poses significant analysis challenges. Because the signal is so faint, robust measurements (or constraints) require a particular attention to systematic effects, astrophysical foregrounds, as well as the interplay between the two. This task is made even more difficult by the volume and complexity of the datasets collected by modern observatories. We present FURAX (Framework for Unified and Robust data Analysis with JAX), an open-source Python library designed to address these challenges by providing flexible tools for data modeling, while benefitting from cutting-edge optimisation and GPU utilisation from the JAX library. Examples include map-making, component separation, gap-filling of time-ordered series, and incorporation and non-ideal instrumental components.