Information from the 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.
Why this record is monitored
This record has an Impact Signal of 75/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Astrophysical Phenomena and Observations · Stellar, planetary, and galactic studies · Galaxies: Formation, Evolution, Phenomena
Thai researcher and institutional participation
A. Aungwerojwit · Naresuan University
Data limitations
This page is a bibliographic record based on abstract-level information, not a full analysis or quality assessment. Verify the DOI and original article before citation.