Spectroscopic Identification and Population Properties of Cataclysmic Variables from DESI DR1

Abstract We present a systematic search for cataclysmic variables (CVs) using spectroscopic data from Data Release 1 of the Dark Energy Spectroscopic Instrument. Applying the Bagging-TopPush algorithm, we identified 433 CV candidates and related objects, of which 412 are confirmed CVs including 76 new systems. Subtypes were assigned through a combination of DESI spectra, Gaia data, and light curves from time-domain surveys, revealing populations of dwarf novae, novalike variables, magnetic CVs, and AM CVn binaries. Orbital periods were constrained from eclipsing light curves and DESI radial velocity curves for 14 systems. For 31 WZ Sge–type dwarf novae, we estimated white dwarf masses and radii by combining Galaxy Evolution Explorer ultraviolet photometry with DESI optical spectra, obtaining average values of 0.82 M ⊙ for mass and 13,452 K for effective temperature. We also calculated the strength of the magnetic field for three polars based on the cyclotron features. Furthermore, we derived subtype-dependent space densities and found values consistent, within uncertainties, with those inferred from Sloan Digital Sky Survey, Gaia, and other survey data, though remaining lower than theoretical predictions by 1–2 orders of magnitude. Besides, we highlight several notable objects, including newly identified AM CVn systems, eclipsing systems in the period gap, donor-dominated binaries, and other unusual systems of particular interest for follow-up observations.

Authors

Publication Details

Journal
The Astrophysical Journal Supplement Series
Published
2026-01-13
DOI
https://doi.org/10.3847/1538-4365/ae2024
Primary Topic
Astrophysical Phenomena and Observations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spectroscopic Identification and Population Properties of Cataclysmic Variables from DESI DR1

Wen Hou, Jia-Mao 佳茂 Lin 林, Shu-Guo 树国 Ma 马, Yi-Qiao 义乔 Dong 董 et al.
The Astrophysical Journal Supplement Series
Astrophysical Phenomena and Observations
article

Spectroscopic Identification and Population Properties of Cataclysmic Variables from DESI DR1

Wen Hou, Jia-Mao 佳茂 Lin 林, Shu-Guo 树国 Ma 马, Yi-Qiao 义乔 Dong 董, A-Li 阿理 Luo 罗, Zhi-Bin 智斌 Dai 戴
article en

Abstract

Abstract We present a systematic search for cataclysmic variables (CVs) using spectroscopic data from Data Release 1 of the Dark Energy Spectroscopic Instrument. Applying the Bagging-TopPush algorithm, we identified 433 CV candidates and related objects, of which 412 are confirmed CVs including 76 new systems. Subtypes were assigned through a combination of DESI spectra, Gaia data, and light curves from time-domain surveys, revealing populations of dwarf novae, novalike variables, magnetic CVs, and AM CVn binaries. Orbital periods were constrained from eclipsing light curves and DESI radial velocity curves for 14 systems. For 31 WZ Sge–type dwarf novae, we estimated white dwarf masses and radii by combining Galaxy Evolution Explorer ultraviolet photometry with DESI optical spectra, obtaining average values of 0.82 M ⊙ for mass and 13,452 K for effective temperature. We also calculated the strength of the magnetic field for three polars based on the cyclotron features. Furthermore, we derived subtype-dependent space densities and found values consistent, within uncertainties, with those inferred from Sloan Digital Sky Survey, Gaia, and other survey data, though remaining lower than theoretical predictions by 1–2 orders of magnitude. Besides, we highlight several notable objects, including newly identified AM CVn systems, eclipsing systems in the period gap, donor-dominated binaries, and other unusual systems of particular interest for follow-up observations.

The Astrophysical Journal Supplement SeriesVol. 282(2)
Openalex Percentile: Top 88%
Astrophysical Phenomena and Observations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.