activity
20152026
most citedImplications for planetary system formation from interstellar object 1I/2017 U1 (`Oumuamua)

60 citations · 389 across the 47 of their papers we have counts for

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Showing 2026Show all

11 papers · 1 filter

astro-ph.IM2026

The LSST Science Pipelines Software: Optical Survey Pipeline Reduction and Analysis Environment

Rubin Observatory Science Pipelines Developers, Yusra AlSayyad, Robert Armstrong +83

The NSF-DOE Vera C. Rubin Observatory is executing the Legacy Survey of Space and Time (LSST) as its prime mission, producing a series of data releases over the ten-year survey. Th…

astro-ph.EP2026

Tails and Trails: Comets and NEOs Survive Co-addition in Rubin Early Data Preview 2

Colin Orion Chandler, Joseph Murtagh, Ian Chow +11

We identify effectively single-visit imaging hidden within the deep co-added images of the NSF-DOE Vera C. Rubin Observatory Early Data Preview 2 (EDP2). These shallow regions cont…

astro-ph.EP2026

High water D/H ratio of the interstellar object 3I/ATLAS is consistent with a low-metallicity origin

Kenji Furuya, Martin Cordiner, Dominique Bockelée-Morvan +5

Recent JWST observations have revealed unusually high C/C ratios in carbon-bearing molecules of the interstellar object 3I/ATLAS, consistent with formation in a lower…

astro-ph.IM2026

The Rubin Observatory Target-of-Opportunity System in the First Year of Operations

Sean Patrick MacBride, R. Lynne Jones, Peter Yoachim +41

The NSF/DOE Vera C. Rubin Observatory is a discovery machine, with unprecedented survey speed, which can be used to identify exotic astrophysical transients. In its prime mission,…

astro-ph.IM2026

Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

Aritra Ghosh, Drew Oldag, Michael Tauraso +29

The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-domain data at scales that inc…

astro-ph.EP2026

You Only Stack Once (YOSO): A Motion-Filtered, Deep-Learning Framework for Detecting Faint Moving Sources

Nitya Pandey, César Fuentes, Pedro Bernardinelli +15

We present You Only Stack Once (YOSO), an automated pipeline designed to detect faint, slow-moving Solar System objects in wide-field astronomical surveys. The pipeline integrates…