Issue |
A&A
Volume 690, October 2024
|
|
---|---|---|
Article Number | A311 | |
Number of page(s) | 22 | |
Section | Extragalactic astronomy | |
DOI | https://doi.org/10.1051/0004-6361/202451671 | |
Published online | 21 October 2024 |
Validating the clustering predictions of empirical models with the FLAMINGO simulations
1
Donostia International Physics Center, Manuel Lardizabal Ibilbidea, 4, 20018
Donostia, Gipuzkoa, Spain
2
IKERBASQUE, Basque Foundation for Science, 48013
Bilbao, Spain
3
Institut de Física d’Altes Energies, The Barcelona Institute of Science and Technology, Campus UAB, E-08193
Bellaterra, Barcelona, Spain
4
Leiden Observatory, Leiden University, PO Box 9513
2300 RA
Leiden, The Netherlands
5
Lorentz Institute for Theoretical Physics, Leiden University, PO box 9506
2300 RA
Leiden, The Netherlands
Received:
26
July
2024
Accepted:
24
August
2024
Context. Mock galaxy catalogues are essential for correctly interpreting current and future generations of galaxy surveys. Despite their significance in galaxy formation and cosmology, little to no work has been done to validate the predictions of these mocks for high-order clustering statistics.
Aims. We compare the predicting power of the latest generation of empirical models used in the creation of mock galaxy catalogues: a 13-parameter halo occupation distribution (HOD) and an extension of the SubHalo Abundance Matching technique (SHAMe).
Methos. We built GalaxyEmu-Planck, an emulator that makes precise predictions for the two-point correlation function, galaxy-galaxy lensing (restricted to distances greater than 1 h−1 Mpc in order to avoid baryonic effects), and other high-order statistics resulting from the evaluation of SHAMe and HOD models.
Results. We evaluated the precision of GalaxyEmu-Planck using two galaxy samples extracted from the FLAMINGO hydrodynamical simulation that mimic the properties of DESI-BGS and BOSS galaxies, finding that the emulator reproduces all the predicted statistics precisely. The HOD shows a comparable performance when fitting galaxy clustering and galaxy-galaxy lensing. In contrast, the SHAMe model shows better predictions for higher-order statistics, especially regarding the galaxy assembly bias level. We also tested the performance of the models after removing some of their extensions, finding that we can withdraw two (out of 13) of the HOD parameters without a significant loss of performance.
Conclusions. The results of this paper validate the current generation of empirical models as a way to reproduce galaxy clustering, galaxy-galaxy lensing, and other high-order statistics. The excellent performance of the SHAMe model with a small number of free parameters suggests that it is a valid method to extract cosmological constraints from galaxy clustering.
Key words: galaxies: formation / galaxies: statistics / large-scale structure of Universe
© The Authors 2024
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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