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astro-ph.CO2026
Field-level multi-tracers simulation-based inference of cosmological parameters from 3D maps
Giulio Scelfo, Satvik Mishra, Mauro Rigo +2
Extracting maximum cosmological information from current and upcoming large-scale structure data requires going beyond summary statistics as currently used in likelihood-based infe…
astro-ph.IM2026
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…