부산대학교 도서관

Void size function (VSF) contains the information of the cosmic large-scale structure (LSS), and can be used to derive the properties of dark energy and dark matter. We predict the VSFs measured from the spectroscopic galaxy survey operated by the China Space Station Telescope (CSST), and study the strength of cosmological constraint. We employ a high-resolution Jiutian simulation to get galaxy samples based on an improved semi-analytical model, and then generate a mock galaxy catalog of the CSST spectroscopic survey according to the detection sensitivity. We identify voids from this galaxy catalog using the watershed algorithm without assuming a spherical shape, and estimate the VSFs at different redshift bins from $z=0.5$ to 1.1. To obtain a reliable and accurate fitting result, we propose a void selection method based on the ellipticity, for comparing to the theoretical model with a linear underdensity threshold of void formation $\delta_{\rm v}$ assuming the spherical evolution. We assume $\delta_{\rm v}$ is redshift-dependent and set it as a free parameter in each redshift bin. The Markov Chain Monte Carlo (MCMC) method is adopted to implement the constraints on the cosmological and void parameters. We find that the VSFs from the selected voids can be well fitted by the theoretical model, and could accurately reserve the cosmological information. Based on our estimation, the VSF measurement of the CSST spectroscopic survey can constrain the cosmological parameters to a few percent level. The best-fit values of $\delta_{\rm v}$ are ranging from $\sim-0.4$ to $-0.1$ as the redshift increases from 0.5 to 1.1, which has a distinct difference from the theoretical calculation with a constant $\delta_{\rm v}\simeq-2.7$ assuming the spherical evolution. Our method can provide a good reference for void identification and selection in the VSF analysis of the spectroscopic galaxy surveys.
Comment: 10 pages, 5 figures, 3 tables