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Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

Lookup NU author(s): Dr Dani LeonardORCiD

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Author(s): Aubourg E, Avestruz C, Becker MR, Biswas B, Biswas R, Bolliet B, Bolton AS, Bom C, Bonnet-Guerrini R, Boucaud A, Campagne J, Chang C, Ciprijanovic A, Cohen-Tanugi J, Coughlin M, Crenshaw J, Cuevas-Tello J, de Vicente J, Digel S, Dillmann S, Romero M, Drlica-Wagner A, Erickson S, Gagliano A, Georgiou C, Ghosh A, Grayling M, Grishin K, Heavens A, House L, Ishak M, Kabalan W, Kannawadi A, Lanusse F, Leonard CD, Leget P, Lochner M, Mao YY, Melchior P, Merz G, Millon M, Moller A, Narayan G, Omori Y, Peiris H, Perreault-Levasseur L, Malagon A, Ramachandra N, Remy B, Roucelle C, Ruiz-Zapatero J, Schuldt S, Sevilla-Noarbe I, Shah V, Starkenburg T, Thorp S, Cipriano J, Troster T, Trotta R, Venkatraman P, Wasserman A, White T, Zeghal J, Zhang T, Zhang Y

Publication type: Note

Publication status: Submitted

Journal: arXiv

Year: 2026

Online publication date: 20/01/2026

Acceptance date: 20/01/2026

URL: https://doi.org/10.48550/arXiv.2601.14235

DOI: 10.48550/arXiv.2601.14235

Notes: This is v1.0 of the DESC's white paper on AI/ML, a collaboration document that is being made public but which is not planned for submission to a journal.

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