An expanded ultraluminous X-ray source catalogue
arXiv:2110.14562 · doi:10.1051/0004-6361/202141560
Abstract
Context. ULXs ( erg s) are excellent probes of accretion physics, star formation and IMBHs searches. As the sample size of X-ray data from modern observatories increases, producing extensive catalogues of ULXs and studying their collective properties is a possibility and a priority. Aims. We build a ULX catalogue based on one of the latest XMM-Newton releases, 4XMM-DR9, and the galaxy catalogue HECATE and study whether the properties of the expanded XMM-Newton ULX population are consistent with previous findings. Methods. We perform cross-matching between XMM-Newton sources and HECATE objects to identify host galaxies, and flag known interlopers in external catalogues and databases. Manual inspection of image data from PanSTARRS1 and the NASA/IPAC database is occasionally performed. We use distance and luminosity arguments to identify ULX candidates. Spectral, abundance and variability properties of the candidates are studied from 4XMM-DR9, HECATE and 4XMM-DR9s parameters. Results. We identify 779 ULX candidates. In spiral galaxies the number of ULX candidates per star forming rate is consistent with previous studies, and a significant ULX population in elliptical and lenticular is also found. Candidates hosted by late-type galaxies are more abundant, present harder spectra and undergo more and more extreme inter-observation variability than the early-type hosted ones. Around 30 candidates with erg s are also identified. Conclusions. Our results on the spectral and abundance properties of ULXs confirm the findings made by previous studies based on XMM-Newton and Chandra data, while our population-scale study on variability properties is unprecedented. Our study provides limited insight on the properties of the brightest ULX candidates due to the small sample size.
arXiv commentPaper accepted for publication in A&A on 2021-10-13. 18 pages, 22 figures, 8 tables. Catalogue soon to be uploaded to the CDS - VizieR database
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