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17 papers · 1 filter
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…
Skykatana: a scalable framework to construct sky masks for the Vera Rubin Observatory and large astronomical surveys
Claudio Lopez, Emilio Donoso, Mariano Javier de L. Dominguez Romero
Modern wide-field surveys require robust spatial masks to excise bright-star halos, bleed trails, poor-quality regions, and user-defined geometry at scale. We present Skykatana, an…
Valuation system for telescope observation time proposals for the Gemini Observatory
C. G. Díaz, R. Petrucci, L. V. Ferrero +1
The preparation of a telescope observation time proposal is a recurring activity in observational astronomy. It is a necessary investment of time and effort to obtain data to advan…
The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
The Astropy Collaboration, Adrian M. Price-Whelan, Pey Lian Lim +133
The Astropy Project supports and fosters the development of open-source and openly-developed Python packages that provide commonly needed functionality to the astronomical communit…
The LSST-DESC 3x2pt Tomography Optimization Challenge
Joe Zuntz, François Lanusse, Alex I. Malz +25
This paper presents the results of the Rubin Observatory Dark Energy Science Collaboration (DESC) 3x2pt tomography challenge, which served as a first step toward optimizing the tom…
Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV
J. B. Cabral, M. Lares, S. Gurovich +2
As most of the modern astronomical sky surveys produce data faster than humans can analyze it, Machine Learning (ML) has become a central tool in Astronomy. Modern ML methods can b…