Speaker
Pierre Chanial
(APC)
Description
Modern scientific data analyses involve complex models, presenting significant challenges in both data volume and computation. We present FURAX (Framework for Unified and Robust data Analysis with JAX), an open-source Python library that provides building blocks to construct instrument and noise models in a modular fashion, that benefit from the cutting-edge optimisation and GPU utilisation from JAX. FURAX is applied to cosmological data analysis with the CMB data. The examples include maximum-likelihood map-making, gap-filling of a time-ordered series and incorporation of non-ideal instrumental components.
Primary author
Pierre Chanial
(APC)
Co-authors
Simon Biquard
(APC)
Wassim Kabalan
(APC - CNRS/IN2P3)
