Simulating the LOcal Web (SLOW)

Context. Large-scale agglomerations of galaxy clusters are the most massive structures in the Universe. To what degree they are actually bound against an accelerating expansion of the background cosmology is of significant cosmological as well as astrophysical interest. In this study, we introduce a crossmatched set of superclusters from the SLOW constrained simulations of the local ( z < 0.05) Universe. These simulations combine a central region constrained by local velocity field data and realistic baryonic physics models within a 500 Mpc/h Box to reproduce the locally observed large-scale structure in detail. Aims. Identifying the local superclusters provides estimates on the efficacy of the constraints in reproducing the local large-scale structure accurately. The simulated counterparts can help to identify possible future observational targets containing interesting features, such as bridges between pre-merging and merging galaxy clusters and collapsing filaments, and provide comparisons for current observations. By numerically determining the collapse volumes for the simulated counterparts, we further elucidate the dynamics of cluster-cluster interactions in those regions. Methods. Starting from observational catalogs of local superclusters and the most massive clusters from the SLOW simulations already identified in previous works, we searched for simulated counterparts of supercluster members of six regions. We evaluated the significance of these detections by comparing the observed geometries to supercluster regions in random simulations. We then ran an N-body version of the SLOW initial conditions into the far future and determined which of the member clusters are gravitationally bound to the host superclusters. Furthermore we computed masses and density contrasts for the collapse regions. Results. We demonstrate that the SLOW constrained simulation of the local Universe accurately reproduces local supercluster regions not only in terms of the mass of their members but also in the individual clusters’ 3D geometrical arrangement relative to each other. We furthermore find the bound regions of the local superclusters to be consistent in both size and density contrast with previous theoretical studies. This will allow us to connect future numerical zoom-in studies of the clusters to the large-scale environments and specifically the supercluster environments these local galaxy clusters evolve in. The zoom-ins will focus on ICM properties, turbulence, and nonthermal emission and build on the existing work concerned with the environments of local galaxy clusters.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2025-09-01
DOI
https://doi.org/10.1051/0004-6361/202453421
Citations
2
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.97

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article

Simulating the LOcal Web (SLOW)

Ildar Khabibullin, E. Hernández-Martínez, Rhea–Silvia Remus, N. Aghanim et al.
2 citations
Astronomy and Astrophysics
Distributed and Parallel Computing Systems
2.97
article

Simulating the LOcal Web (SLOW)

Ildar Khabibullin, E. Hernández-Martínez, Rhea–Silvia Remus, N. Aghanim, Jenny G. Sorce, K. Dolag, Benjamin Seidel
article en
2 citations

Abstract

Context. Large-scale agglomerations of galaxy clusters are the most massive structures in the Universe. To what degree they are actually bound against an accelerating expansion of the background cosmology is of significant cosmological as well as astrophysical interest. In this study, we introduce a crossmatched set of superclusters from the SLOW constrained simulations of the local ( z < 0.05) Universe. These simulations combine a central region constrained by local velocity field data and realistic baryonic physics models within a 500 Mpc/h Box to reproduce the locally observed large-scale structure in detail. Aims. Identifying the local superclusters provides estimates on the efficacy of the constraints in reproducing the local large-scale structure accurately. The simulated counterparts can help to identify possible future observational targets containing interesting features, such as bridges between pre-merging and merging galaxy clusters and collapsing filaments, and provide comparisons for current observations. By numerically determining the collapse volumes for the simulated counterparts, we further elucidate the dynamics of cluster-cluster interactions in those regions. Methods. Starting from observational catalogs of local superclusters and the most massive clusters from the SLOW simulations already identified in previous works, we searched for simulated counterparts of supercluster members of six regions. We evaluated the significance of these detections by comparing the observed geometries to supercluster regions in random simulations. We then ran an N-body version of the SLOW initial conditions into the far future and determined which of the member clusters are gravitationally bound to the host superclusters. Furthermore we computed masses and density contrasts for the collapse regions. Results. We demonstrate that the SLOW constrained simulation of the local Universe accurately reproduces local supercluster regions not only in terms of the mass of their members but also in the individual clusters’ 3D geometrical arrangement relative to each other. We furthermore find the bound regions of the local superclusters to be consistent in both size and density contrast with previous theoretical studies. This will allow us to connect future numerical zoom-in studies of the clusters to the large-scale environments and specifically the supercluster environments these local galaxy clusters evolve in. The zoom-ins will focus on ICM properties, turbulence, and nonthermal emission and build on the existing work concerned with the environments of local galaxy clusters.

Astronomy and AstrophysicsVol. 702
Centre National de la Recherche Scientifique (FR), Université Paris-Saclay (FR), Institut d'Astrophysique Spatiale (FR), Max Planck Institute for Astrophysics (DE), École Centrale de Lille (FR), Ludwig-Maximilians-Universität München (DE)
Horizon 2020
Openalex Percentile: Top 7%
Distributed and Parallel Computing Systems
2.97
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