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Identification and Photometric Classification of Extragalactic Transients in the Vera C. Rubin Observatory’s Data Preview

  • James Freeburn
  • , Igor Andreoni
  • , Kaylee M. De Soto
  • , Cristina Andrade
  • , Akash Anumarlapudi
  • , Tyler Barna
  • , Jonathan Carney
  • , Sushant Sharma Chaudhary
  • , Michael W. Coughlin
  • , Felipe Fontinele Nunes
  • , Sarah Teague
  • , Mickael Rigault
  • , V. Ashley Villar
  • , Gloria Fonseca Alvarez
  • , Federica B. Bianco
  • , Alexandre Boucaud
  • , Dominique Boutigny
  • , Andrew Bradshaw
  • , Hsin Fang Chiang
  • , Phil N. Daly
  • Felipe Daruich, Guillaume Daubard, Holger Drass, Laurent Le Guillou, Leanne P. Guy, Patrick Ingraham, M. James Jee, Steven M. Kahn, Yijung Kang, Arun Kannawadi, Lee S. Kelvin, Didier Laporte, Shuang Liang, Nate B. Lust, Mostafa Lutfi, Gabriele Mainetti, Andrés A. Plazas Malagón, Felipe Menanteau, David J. Mills, Marc Moniez, Erfan Nourbakhsh, Russell E. Owen, Maria T. Patterson, John R. Peterson, Wouter Van Reeven, Vincent J. Riot, William Roby, David Sanmartim, Jacques Sebag, Nima Sedaghat, Richard A. Shaw, Alysha Shugart, Krzysztof Suberlak, John D. Swinbank, Dan S. Taranu, Charlotte Ward, Christopher Z. Waters, W. M. Wood-Vasey

Research output: Contribution to journalArticlepeer-review

Abstract

The Vera C. Rubin Observatory will soon survey the southern sky, delivering a depth and sky coverage that is unprecedented in time-domain astronomy. As part of commissioning, Data Preview 1 (DP1) has been released. It comprises a Legacy Survey of Space and Time (LSST) Commissioning Camera observing campaign between 2024 November and December with multiband imaging of seven fields, covering roughly 0.4 deg2 each, providing a first glimpse into the data products that will become available once the LSST begins. In this work, we search three fields for extragalactic transients. We identify eight new likely supernovae (SNe), and three known ones from a sample of 369,644 difference image analysis objects. Photometric classification using Superphot+ assigns subclasses with >95% confidence to only one SN Ia and one SN II in this sample. Our findings are in agreement with SN detection rate predictions of 15 ± 4 SNe from simulations using simsurvey. The SN detection rate in the data is possibly affected by the lack of suitable templates. Nevertheless, this work demonstrates the quality of the data products delivered in DP1 and indicates that the Rubin Observatory’s LSST is well placed to fulfill its discovery potential in time-domain astronomy.

Original languageEnglish (US)
Article numberL24
JournalAstrophysical Journal Letters
Volume994
Issue number1
DOIs
StatePublished - Nov 20 2025

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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