The first all-sky survey of star-forming galaxies with eROSITA: Scaling relations and a population of X-ray luminous starbursts
Files
Author/Creator ORCID
Date
Type of Work
Department
Program
Citation of Original Publication
Kyritsis, E., A. Zezas, F. Haberl, P. Weber, A. Basu-Zych, N. Vulic, C. Maitra, et al. "The First All-Sky Survey of Star-Forming Galaxies with eROSITA. Scaling Relations and a Population of X-Ray Luminous Starbursts". Astronomy & Astrophysics, 11 December 2024. https://doi.org/10.1051/0004-6361/202449593.
Rights
This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0
Public Domain Mark 1.0
Abstract
Context. In this work, we present the results from a study of X-ray normal galaxies (i.e. not harbouring active galactic nuclei; AGN) using data from the first complete all-sky scan of the eROSITA X-ray survey (eRASS1) obtained with eROSITA on board the Spectrum-Roentgen-Gamma (SRG) observatory. eRASS1 provides the first unbiased X-ray census of local normal galaxies allowing us to study the X-ray emission (0.2-8.0 keV) from X-ray binaries (XRBs) and the hot interstellar medium in the full range of stellar population parameters present in the local Universe. Aims. By combining the updated version of the Heraklion Extragalactic Catalogue (HECATE v2.0) value-added catalogue of nearby galaxies (D≲200Mpc) with the X-ray data obtained from the eRASS1, we study the integrated X-ray emission from normal galaxies as a function of their star-formation rate (SFR), stellar mass (M⋆), Metallicity, and stellar population age. Methods. After applying stringent optical and mid-infrared activity classification criteria, we constructed a sample of 18790 bonafide star-forming galaxies (HEC-eR1 galaxy sample) with measurements of their integrated X-ray luminosity (using each galaxy’s D25), over the full range of stellar population parameters present in the local Universe. By stacking the X-ray data in SFR-M⋆-D bins we study the correlation between the average X-ray luminosity and the average stellar population parameters. We also present updated Lₓ-SFR and Lₓ/SFR-Metallicity scaling relations based on a completely blind galaxy sample and accounting for the scatter dependence on the SFR. Results. The average X-ray spectrum of star-forming galaxies is well described by a power-law (Γ = 1.75⁺⁰.¹²₋₀.₀₇) and a thermal plasma component (kT = 0.70⁰.⁰⁶ ₋₀.₀₇ keV). We find that the integrated X-ray luminosity of the individual HEC-eR1 star-forming galaxies is significantly elevated (reaching 10⁴²erg s⁻¹ ) with respect to that expected from the current standard scaling relations. The observed scatter is also significantly larger. This excess persists even when we measure the average luminosity of galaxies in SFR–M⋆-D and metallicity bins and it is stronger (up to ~2dex) towards lower SFRs. Our analysis shows that the excess is not the result of the contribution by hot gas, low-mass X-ray binaries, background AGN, low-luminosity AGN (including tidal disruption events), or stochastic sampling of the X-ray binary X-ray luminosity function. We find that while the excess is generally correlated with lower metallicity galaxies, its primary driver is the age of the stellar populations. Conclusions. Our analysis reveals a sub-population of very X-ray luminous starburst galaxies with higher sSFRs, lower metallicities, and younger stellar populations. This population drives upwards the X-ray scaling relations for star-forming galaxies, and has important implications for understanding the population of X-ray binaries contributing in the most X-ray luminous galaxies in the local and high-redshift Universe. These results demonstrate the power of large blind surveys such eRASS1 which can provide a more complete picture of the X-ray emitting galaxy population and their diversity, revealing rare populations of objects and recovering unbiased underlying correlations.