Issue |
A&A
Volume 699, July 2025
|
|
---|---|---|
Article Number | A206 | |
Number of page(s) | 26 | |
Section | Extragalactic astronomy | |
DOI | https://doi.org/10.1051/0004-6361/202553977 | |
Published online | 09 July 2025 |
Modelling the selection of galaxy groups with end-to-end simulations
1
Department of Astronomy, University of Geneva, Ch. d’Ecogia 16, CH-1290 Versoix, Switzerland
2
Department of Physics, University of Helsinki, Gustaf Hällströmin katu 2, 00560 Helsinki, Finland
3
Max-Planck-Institut für extraterrestrische Physik (MPE), Giessenbachstraße 1, D-85748 Garching bei München, Germany
4
Department of Computer Science, Aalto University, PO Box 15400, Espoo, FI-00076, Finland
5
Tartu Observatory, University of Tartu, Observatooriumi 1, 61602 Tõravere, Estonia
6
Estonian Academy of Sciences, Kohtu 6, 10130 Tallinn, Estonia
7
Dr. Karl Remeis-Observatory and Erlangen Centre for Astroparticle Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Sternwartstr. 7, 96049 Bamberg, Germany
8
Institut d’Astrophysique de Paris (UMR 7095: CNRS & Sorbonne Université), 98 bis Bd Arago, F-75014 Paris, France
9
INAF/IASF-Milano, Via A. Corti 12, 20133 Milano, Italy
10
INAF, Osservatorio di Astrofisica e Scienza dello Spazio, via Piero Gobetti 93/3, 40129 Bologna, Italy
11
Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA
12
Centre for Radio Astronomy Techniques and Technologies, Department of Physics and Electronics, Rhodes University, PO Box 94, Makhanda 6140, South Africa
13
South African Radio Astronomy Observatory, Black River Park North, 2 Fir St, Cape Town 7925, South Africa
14
Centre for Astrophysics Research, Department of Physics, Astronomy and Mathematics, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK
15
Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK
16
Department of Physics and Astronomy, The University of Alabama in Huntsville, Huntsville, AL 35899, USA
17
Max-Planck-Institut für Astronomie, Königstuhl 17, 69117 Heidelberg, Germany
⋆ Corresponding author: riccardo.seppi@unige.ch
Received:
31
January
2025
Accepted:
3
June
2025
Context. Feedback from supernovae and active galactic nuclei (AGN) shapes the galaxy formation and evolution, but its impact remains unclear. Galaxy groups offer a crucial probe to determine this impact because their gravitational binding energy is comparable to the energy that is available from their central AGN. The XMM-Newton Group AGN Project (X-GAP) is a sample of 49 groups that were selected in the X-ray (ROSAT) and optical (SDSS) bands and provides a benchmark for hydrodynamical simulations.
Aims. For this comparison, it is essential to understand the selection effects. We model the selection function of X-GAP by forward-modelling the detection process in the X-ray and optical bands.
Methods. Using the Uchuu N-body simulation, we built a dark matter halo light cone, predicted X-ray group properties with a neural network trained on hydrodynamical simulations, and assigned matching observed properties to the galaxies. We compared the selected sample to the parent population in the light cone.
Results. Our method provided a sample that matched the observed distribution of the X-ray luminosity and velocity dispersion. A completeness of 50% was reached at a velocity dispersion of 450 km/s in the X-GAP redshift range. The selection is driven by X-ray flux, with a secondary dependence on the velocity dispersion and redshift. We estimated a purity level of 93% for the X-GAP parent sample. We calibrated the relation of the velocity dispersion to the halo mass. We found a normalisation and slope that agree with the literature and an intrinsic scatter of about 0.06 dex. The measured velocity dispersion is only accurate within 10% for rich systems with more than about 20 members, and the velocity dispersion for groups with fewer than 10 members is biased at more than 20%.
Conclusions. The X-ray follow-up refines the optical selection and enhances the purity, but reduces completeness. In an SDSS-like set-up, measurement errors for the velocity dispersion dominate the intrinsic scatter. Our selection model enables unbiased comparisons of thermodynamic properties and gas fractions between X-GAP groups and hydrodynamical simulations.
Key words: methods: data analysis / surveys / galaxies: clusters: intracluster medium / galaxies: groups: general / large-scale structure of Universe / X-rays: galaxies: clusters
© The Authors 2025
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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