Multi-wavelength scaling relations in galaxy groups: a detailed comparison of GAMA and KiDS observations to BAHAMAS simulations
Arthur Jakobs, Massimo Viola, Ian McCarthy, Ludovic van Waerbeke, Henk, Hoekstra, Aaron Robotham, Gary Hinshaw, Alireza Hojjati, Hideki Tanimura,, Tilman Tr\"oster, Ivan Baldry, Catherine Heymans, Hendrik Hildebrandt, Konrad, Kuijken, Peder Norberg, Joop Schaye

TL;DR
This study compares galaxy group scaling relations from GAMA and KiDS observations with BAHAMAS simulations, revealing good agreement in some properties but discrepancies in X-ray luminosities, highlighting potential biases in selection methods.
Contribution
It provides a detailed comparison of observed and simulated galaxy group properties using multi-wavelength data, emphasizing the importance of consistent selection and analysis procedures.
Findings
Simulations match the richness, size, and stellar mass functions of GAMA groups.
Simulations overpredict X-ray luminosities compared to observations.
Optical selection methods can be improved to reduce biases.
Abstract
We study the scaling relations between the baryonic content and total mass of groups of galaxies, as these systems provide a unique way to examine the role of non-gravitational processes in structure formation. Using Planck and ROSAT data, we conduct detailed comparisons of the stacked thermal Sunyaev-Zel'dovich (tSZ) and X-ray scaling relations of galaxy groups found in the Galaxy And Mass Assembly (GAMA) survey and the BAHAMAS hydrodynamical simulation. We use weak gravitational lensing data from the Kilo Degree Survey (KiDS) to determine the average halo mass of the studied systems. We analyse the simulation in the same way, using realistic weak lensing, X-ray, and tSZ synthetic observations. Furthermore, to keep selection biases under control, we employ exactly the same galaxy selection and group identification procedures to the observations and simulation. Applying this comparison,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
