279 citations · 1.1k across the 44 of their papers we have counts for
5 papers · 1 filter
Dark Energy Survey Year 6 Results: fast and interpretable posterior predictive checks for correlated cosmic probes
C. Doux, J. Muir, A. Ferté +59
We present a fast and numerically stable framework for conducting posterior predictive distribution (PPD) tests of internal consistency in correlated cosmological probes. Our metho…
Deep Learning for Point Spread Function Modeling in Cosmology
Dayana Andrea Henao Arbeláez, Pierre-François Léget, Andrés Alejandro Plazas Malagón
We present the development of a data-driven, AI-based model of the Point Spread Function (PSF) that achieves higher accuracy than the current state-of-the-art approach, "PSF in the…
Dark Energy Survey Year 6 Results: Cosmological Constraints from Cosmic Shear
DES Collaboration, T. M. C. Abbott, M. Aguena +126
We present legacy cosmic shear measurements and cosmological constraints using six years of Dark Energy Survey imaging data. From these data, we study ~140 million galaxies (8.29 g…
Lessons Learned from Integrating Generative AI into an Introductory Undergraduate Astronomy Course at Harvard
Christopher W. Stubbs, Dongpeng Huang, Jungyoon Koh +2
We describe our efforts to fully integrate generative artificial intelligence (GAI) into an introductory undergraduate astronomy course. Ordered by student perception of utility, G…
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…