6 papers
A GPU-Accelerated JAX Framework for Robust Parametric Component Separation and Clustering Optimization for CMB Polarization Satellites
Wassim Kabalan, Arianna Rizzieri, Wuhyun Sohn +6
We present a novel, JAX-powered implementation of a parametric component-separation method for CMB polarization data, explicitly designed to handle spatially varying foreground Spe…
Furax: A Modular JAX Framework for Linear Operators in Astrophysical and Cosmological Data Analysis
Pierre Chanial, Simon Biquard, Wassim Kabalan +10
The Framework for Unified and Robust data Analysis with JAX (Furax) is an open-source Python framework for modeling data acquisition systems and solving inverse problems in astroph…
Half-wave-plate non idealities propagated to component separated CMB -modes
Ema Tsang-King-Sang, Josquin Errard, Simon Biquard +4
We assess the impact of non-ideal, continuously rotating half-wave plates (HWPs) on cosmic microwave background (CMB) polarization measurements targeting large angular scale signal…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
The Simons Observatory: forecasted constraints on primordial gravitational waves with the expanded array of Small Aperture Telescopes
The Simons Observatory Collaboration, I. Abril-Cabezas, S. Adachi +479
We present updated forecasts for the scientific performance of the degree-scale (0.5 deg FWHM at 93 GHz), deep-field survey to be conducted by the Simons Observatory (SO). By 2027,…
Bayesian Deconvolution of Astronomical Images with Diffusion Models: Quantifying Prior-Driven Features in Reconstructions
Alessio Spagnoletti, Alexandre Boucaud, Marc Huertas-Company +2
Deconvolution of astronomical images is a key aspect of recovering the intrinsic properties of celestial objects, especially when considering ground-based observations. This paper…