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astro-ph.IM2024
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…
astro-ph.IM2024
MADNESS Deblender: Maximum A posteriori with Deep NEural networks for Source Separation
Biswajit Biswas, Eric Aubourg, Alexandre Boucaud +4
Due to the unprecedented depth of the upcoming ground-based Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory, approximately two-thirds of the galaxies are li…
astro-ph.IM2020
Fink, a new generation of broker for the LSST community
Anais Möller, Julien Peloton, Emille E. O. Ishida +33
Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).…