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

Anton Rudakovskyi, Franco Vazza, Maksym Tsizh

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 $σ_8$ 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 $σ_8$. 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.

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 and with 21 physical model variations (including variations of 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 . Moreover, we find that this network analysis approach can allow us to distinguish the presence of PMFs with initial strength from the scenarios with much weaker PMFs.

Paper Structure

This paper contains 14 sections, 4 equations, 14 figures, 1 table.

Figures (14)

  • Figure 1: Distribution of baryonic matter density for one of our simulated volumes, for 16 model variations (out of a total of 21 variations) explored in the MAKITRA suite at $z=0.2$. The side of each box is $150$ Mpc, and the colorbar gives the number density in [$\rm g/cm^3$].
  • Figure 2: Distribution of the mean magnetic field strength as a function of the baryonic matter over density at $z=0.2$, for runs with magnetic field variations. The coloured areas show the approximate range of lower limits on PMFs from $\gamma$-ray observations, and the maximum magnetic field in filaments derived by radio observations, while the hatched area shows the approximate density range of clusters, where our simulation struggles to resolve dynamo amplification properly. The additional dashed line shows the $B\propto n^{2/3}$ scaling expected for pure isotropic compression of magnetic field lines.
  • Figure 3: Halo mass distribution functions for our runs and $z=0.2$, considering the total (baryons+DM) $M_{200}$ masses. Most of the magnetic field variations (solid and dashed lines) are indistinguishable from the baseline model, unlike variations in $\sigma_8$ (dotted lines). The mass functions for runs B12, B13 and B16 are not shown for clarity, as they are indistinguishable from all others.
  • Figure 4: The halo-halo correlation functions $\xi_{hh}$ are computed in real space using the Landy–Szalay estimator. The error bars represent cosmic variance and correspond to the standard deviations calculated for the same distance bins across simulations with different random seeds. We show here, for clarity, only a subset of models, representing the most extreme variations of models in MAKITRA, to show that even in these cases, the correlation functions are basically indistinguishable.
  • Figure 5: Cumulative distributions of the degree metric for different simulation sets at $z = 0.2$. We consider the uniform PMF scenario with a magnetic field strength of $B = 10^{-10}\,\text{G}$ and $\sigma_8=0.8$ as the fiducial (dashed line) in all panels. Left: Uniform PMF scenarios B409, B209, B09, B16, $\sigma_8=0.7$, and the fiducial scenario. Middle: Non-uniform PMF scenarios with power spectrum index $n$ compared to the fiducial scenario (only the two extreme spectral indices are shown for clarity). Right: Different $\sigma_8$ scenarios with a uniform magnetic field of strength 0.1 nG compared to the fiducial scenario.
  • ...and 9 more figures