6 papers
The Vera C. Rubin Observatory Data Preview 1
Vera C Rubin Observatory Team, Tatiana Acero Cuellar, Emily Acosta +325
We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detecti…
Variability-finding in Rubin Data Preview 1 with LSDB
Konstantin Malanchev, Melissa DeLucchi, Neven Caplar +56
The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in t…
What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23
Maria V. Pruzhinskaya, Anastasia D. Lavrukhina, Timofey A. Semenikhi +7
We present results from the SNAD VIII Workshop, during which we conducted the first systematic anomaly search in the ZTF fields also observed by LSSTComCam during Rubin Scientific…
Signatures to help interpretability of anomalies
Emmanuel Gangler, Emille E. O. Ishida, Matwey V. Kornilov +8
Machine learning is often viewed as a black box when it comes to understanding its output, be it a decision or a score. Automatic anomaly detection is no exception to this rule, an…
Dataset of artefacts for machine learning applications in astronomy
Sreevarsha Sreejith, Maria V. Pruzhinskaya, Alina A. Volnova +8
Accurate photometry in astronomical surveys is challenged by image artefacts, which affect measurements and degrade data quality. Due to the large amount of available data, this ta…
Real-bogus scores for active anomaly detection
T. A. Semenikhin, M. V. Kornilov, M. V. Pruzhinskaya +8
In the task of anomaly detection in modern time-domain photometric surveys, the primary goal is to identify astrophysically interesting, rare, and unusual objects among a large vol…