The network analysis of the cosmic web as a tool to constrain cosmology and cosmic magnetism

Abstract

Context. The spatial distribution of haloes in the Cosmic Web encodes a wealth of information about the underlying cosmological model. These haloes can be represented as nodes of a graph, whose structural properties reflect cosmological parameters. Aims. Using our new MAKITRA suite of cosmological magneto-hydrodynamical simulations covering a total volume of $(300\,\text{Mpc})^3$ and with 21 physical model variations (including variations of $\sigma_8$ and of different models of primordial magnetic fields, PMFs), we investigate the sensitivity of network-based statistics describing the Cosmic Web to variations in cosmological and PMF scenarios. Methods. We focus on several complementary metrics that characterise the spatial distribution of dark and baryonic matter haloes: two-point correlation functions, network-centrality statistics, and counts-in-cell measurements. We first compare the halo-halo correlation functions across different cosmological models. For the network analysis, we represent haloes as vertices of the Cosmic Web and compute multiple centrality measures, whose cumulative distributions we evaluate for universes with varying PMF strengths. Finally, we quantify halo abundances within randomly placed spheres of fixed radius to assess differences between scenarios. Results. First, we find that the statistics of the centralities of the network can serve as a novel sensitive probe of the cosmological parameter $\sigma_8$. Moreover, we find that this network analysis approach can allow us to distinguish the presence of PMFs with initial strength $\approx\,4 \text{nG}$ from the scenarios with much weaker PMFs.