1000 cataclysmic variables identified from DESI spectroscopy

Abstract Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1028 CVs, 221 of which are new including ten of the AMCVn subtype. We have spectroscopically confirmed 440 CV candidates and obtained 85 new or improved orbital periods.We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion.

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Journal
Monthly Notices of the Royal Astronomical Society
Published
2026-10-28
DOI
https://doi.org/10.1093/mnras/stag2061
Primary Topic
Astrophysical Phenomena and Observations
Type
article
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0.00

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article

1000 cataclysmic variables identified from DESI spectroscopy

Will J. Percival, J. Najita, Christopher J. Manser, Stéphanie Juneau et al.
2 links
Monthly Notices of the Royal Astronomical Society
Astrophysical Phenomena and Observations
article

1000 cataclysmic variables identified from DESI spectroscopy

Will J. Percival, J. Najita, Christopher J. Manser, Stéphanie Juneau, J. Moustakas, P. Doel, Laurent Le Guillou, B A Weaver, Ignasi Pérez-Ràfols, Martin Landriau, Keith Inight, B. T. Gänsicke, J. Guy, Satya Gontcho A Gontcho, John R.  Thorstensen, R. Miquel, J. E. Forero-Romero, Steven P. Ahlen, Aaron Meisner, Sergey E. Koposov, A. Aungwerojwit, Aguilar Jl., A.D. Myers, R. Joyce, H. Zou, J. Silber, H. Seo, Biprateep Dey, G. Tarlé, D Bianchi, G. Rossi, F. Prada, D. Brooks, R. Zhou, D. Schlegel, M. Schubnell, E. J. Sanchez, P. Izquierdo, A. Swan, G. Gutierrez, A. de la Macorra, A. Kremin, A. Font-Ribera, T. Claybaugh
article en

Abstract

Abstract Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1028 CVs, 221 of which are new including ten of the AMCVn subtype. We have spectroscopically confirmed 440 CV candidates and obtained 85 new or improved orbital periods.We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion.

Monthly Notices of the Royal Astronomical Society
Dartmouth College (US), Boston University (US), Institució Catalana de Recerca i Estudis Avançats (ES), University of Wyoming (US), Centre National de la Recherche Scientifique (FR), Fermi National Accelerator Laboratory (US), Lawrence Berkeley National Laboratory (US), University of Waterloo (CA), Universidad de Los Andes (CO), University of Pittsburgh (US), Perimeter Institute (CA), University of Toronto (CA), Institute for High Energy Physics (ES), University of Milan (IT), Chinese Academy of Sciences (CN), University of Cambridge (GB), University of Michigan (US), Brera Astronomical Observatory (IT), Sejong University (KR), University of Warwick (GB), Sorbonne Université (FR), Laboratoire de Physique Nucléaire et de Hautes Énergies (FR), Royal Observatory (GB), Ohio University (US), Barcelona Institute of Science and Technology (ES), Institut National de Physique Nucléaire et de Physique des Particules (FR), NSF NOIRLab (US), Instituto de Astrofísica de Andalucía (ES), National Astronomical Observatories (CN), Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (ES), University College London (GB), University of Virginia (US), Naresuan University (TH), Universidad Nacional Autónoma de México (MX), Universitat Politècnica de Catalunya (ES), University of Edinburgh (GB)
National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Gordon and Betty Moore Foundation, European Commission, Ministerio de Ciencia e Innovación, Naresuan University, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Office of Science, Science and Technology Facilities Council, Division of Astronomical Sciences, High Energy Physics
Openalex Percentile: Top 42%
Astrophysical Phenomena and Observations
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