Tracing the high-z cosmic web with Quaia: catalogues of voids and clusters in the quasar distribution

Abstract

Understanding the formation and evolution of the cosmic web of galaxies is a fundamental goal of cosmology, using various tracers of the cosmic large-scale structure at an ever wider range of redshifts. Our principal aim is to advance the mapping of the cosmic web at high redshifts using observational and synthetic catalogues of quasars (QSOs), which offer a powerful probe of structure formation and the validity of the concordance cosmological model. In this analysis, we selected 708,483 QSOs at $0.8<z<2.2$ from the Quaia data set, allowing a reconstruction of the matter density field using 24,372 deg$^2$ sky area with a well-understood selection function, and thus going beyond previous studies. Using the REVOLVER method, we created catalogues of voids and clusters based on the estimation of the local density at QSO positions with Voronoi tessellation. We tested the consistency of Quaia data and 50 mock catalogues, including various parameters of the voids and clusters in data subsets, and also measurements of the density profiles of these cosmic super-structures at $100 h^{-1}$Mpc scales. We identified 12,842 voids and 41,111 clusters in the distribution of Quaia QSOs. The agreement between data and mocks is at a level of 5-10%, considering void and cluster radii, average inner density, and density profiles. In particular, we tested the role of survey mask proximity effects in the void and cluster detection, which albeit present, are consistent in simulations and observations. The largest voids and clusters reach $R_{eff} \approx 250 h^{-1}$Mpc and $150 h^{-1}$Mpc, respectively, but without evidence for ultra-large cosmic structures exceeding the dimensions of the largest structures in the mocks. As an important deliverable, we share our density field estimation, void catalogues, and cluster catalogues with the public, allowing various additional cross-correlation probes at high-z.

Figures (9)

• Figure 1: Left: Quaia selection function. This is the basis of our masking strategy. We also show the distribution of 4520 quasars in a narrow redshift slice at $1.8<z<1.81$ on top. Right: Redshift distribution of Quaia quasars, showing the good agreement with mocks.
• Figure 2: Redshift slice of the Quaia catalogue at $1.0 < z < 1.03$ in equatorial coordinates. Based on the Voronoi tessellation, the reconstructed local over-density ($\rho/\bar{\rho}$) at the quasar positions is colour-coded and the size of the points is also proportional to their density. Pixels of low completeness are excluded from the analysis using the angular selection function. The map shows large-scale clustering of quasars, without clearly outstanding features.
• Figure 3: Two-dimensional view of the Quaia dataset at $0.8 < z < 2.2$ with $-180^{\circ}<RA<180^{\circ}$, but only showing quasars with $-0.5^{\circ}<Dec<0.5^{\circ}$. The over-density ($\rho/\bar{\rho}$) colour-coding and marker sizes are the same as in Fig. \ref{['fig:quasar_density_in_slice']}.
• Figure 4: Void radii (left) and cluster radii distribution (right) in the Quaia catalogue. With full colours, we show structures that are far from the mask ($\texttt{EdgeFlag}=0$), while pale bars on top show the number of voids and clusters close to the survey edge ($\texttt{EdgeFlag}=1$). We found good agreement when comparing the observations with the mean and standard deviation of the mocks (black and grey data points). On the main panels, error bars correspond to the standard deviations of the 50 mock realizations. In the bottom panels, error bars for the mocks are again estimated from the 50 realisations, while for Quaia we used the binomial sample standard deviation $\sigma = \sqrt{p(1-p)/N}$ with $p=N_{\rm edge}/N_{\rm all}$ where $N$ is the number of voids in the bin. We also used these error estimations in Figs. \ref{['fig:delta_min']}-\ref{['fig:redshift']}.
• Figure 5: Distributions of minimum density in void centres (left) and maximum density in cluster centres (right) in the Quaia catalogue. We again compare structures near and far from the survey edges, and also assess consistency between data and mocks.