Exploring Cosmological Constraints of the Void-Lensing Cross-Correlation in the CSST Photometric Survey

TL;DR

The paper develops a framework to constrain cosmology using the cross-correlation between cosmic voids and weak lensing in the CSST photometric survey, modeled with the Halo Void Dust Model under the $w$CDM paradigm and inferred via MCMC. By constructing realistic Jiutian-based mocks and identifying 2D voids in seven photo-$z$ tomographic bins, the authors measure the void–lensing angular cross-power spectrum and propagate a jackknife + pseudo-$C_{\ell}$ covariance into a robust likelihood. They demonstrate that void–lensing can yield competitive or tighter constraints on $h$, $\Omega_m$, and $w$ compared to WL alone for a 100 deg$^2$ field, and highlight the potential for substantial improvements when CSST surveys cover the full area. The results establish void-lensing as a valuable, complementary cosmological probe for future Stage-IV surveys targeting the high-redshift universe.

Abstract

We investigate the cosmological constraints from the void-lensing cross-correlation assuming the $w$CDM model for the Chinese Space Station Survey Telescope (CSST) photometric survey. Using Jiutian simulations, we construct a mock galaxy catalog to $z=3$ covering 100 deg$^2$, which incorporates the instrumental and observational effects of the CSST. We divide the galaxy sample into seven photometric-redshift (photo-$z$) tomographic bins and identify 2D voids within each bin using the Voronoi tessellation and watershed algorithm. We measure the angular cross-power spectrum between the void distribution and the weak lensing signal, and estimate the covariance matrix via jackknife resampling combined with pseudo-$C_{\ell}$ approach to account for the partial sky correction. We employ the Halo Void Dust Model (HVDM) to model the void-matter cross-power spectrum and adopt the Markov Chain Monte Carlo (MCMC) technique to implement the constraints on the cosmological and void parameters. We find that our method can accurately extract the cosmological information, and the constraint accuracies of some cosmological parameters from the void-lensing analysis are comparable or even tighter than the weak lensing only case. This demonstrates that the void-lensing serves as an effective cosmological probe and a valuable complement to galaxy photometric surveys, particularly for the Stage-IV surveys targeting the high-redshift Universe.

Figures (8)

• Figure 1: The mock galaxy redshift distributions in the CSST photometric survey. The solid curves denote the redshift distributions of the seven photo-$z$ bins, which are obtained by stacking samples drawn from the redshift PDF of each individual galaxy.
• Figure 2: Schematic illustration of the procedure for identifying 2D voids from the galaxy catalog. (a) A slice of galaxies from a small region of the mock catalog, where black dots indicate galaxy positions. (b) The 2D Voronoi tessellation constructed from the galaxy distribution, with each galaxy assigned to a Voronoi cell. (c) Voronoi cells colored by the local density. (d) Identified zones (2D void candidates without pruning), where crosses mark the cores (local density minima) of the zones and colors distinguish different zones.
• Figure 3: The mock CSST void-lensing cross-power spectra for the seven tomographic bins in 100 deg$^2$. The blue solid curves show the results of the best-fitting theoretical model, and the data points are the mock data. The blue data points denote the signal-to-noise ratio (SNR) $<1$, which are discarded in the constraint process. The gray regions show the small scales that are excluded with $k_{\text{max}} = 0.3\,$Mpc$^{-1}h$. We also discard the cross-power spectra with low amplitudes, and only consider the void-lensing power spectrum for the case $i < j$ in the analysis, where $i$ and $j$ denote the tomographic bins of the void and weak lensing samples, respectively
• Figure 4: The normalized full covariance matrix, shown in terms of the correlation coefficient $C_{ij}/\sqrt{C_{ii}C_{jj}}$, where $C_{ij}$ are the elements of the covariance matrix, estimated from jackknife realizations. The $C_{\text{v}\kappa}$ values in the data vector are ordered according to their redshift bin combinations $(m, n)$.
• Figure 5: Constraints on the five cosmological parameters derived from the CSST void-lensing analysis over a 100 deg$^2$ survey area. The shaded regions represent the 1$\sigma$ (68.3%) and 2$\sigma$ (95.5%) confidence levels. The vertical and horizontal dotted lines indicate the fiducial values of these parameters.