Cosmological Prediction of the Void and Galaxy Clustering Measurements in the CSST Spectroscopic Survey
Yingxiao Song, Qi Xiong, Yan Gong, Furen Deng, Kwan Chuen Chan, Xuelei, Chen, Qi Guo, Guoliang Li, Ming Li, Yun Liu, Yu Luo, Wenxiang Pei, and, Chengliang Wei

TL;DR
This paper demonstrates that void and galaxy clustering measurements from mock catalogs can effectively constrain cosmological parameters, with joint analysis improving accuracy by about 20%, highlighting the potential of voids as complementary probes in large-scale structure studies.
Contribution
The study introduces a simplified theoretical model using void effective radius and employs MCMC for cosmological constraints, validating the method with mock catalogs for the CSST survey.
Findings
The model accurately extracts cosmological information from power spectra.
Joint analysis improves parameter constraints by approximately 20%.
Void clustering measurements complement galaxy clustering in cosmological studies.
Abstract
The void power spectrum is related to the clustering of low-density regions in the large-scale structure (LSS) of the Universe, and can be used as an effective cosmological probe to extract the information of the LSS. We generate the galaxy mock catalogs from Jiutian simulation, and identify voids using the watershed algorithm for studying the cosmological constraint strength of the China Space Station Telescope (CSST) spectroscopic survey. The galaxy and void auto power spectra and void-galaxy cross power spectra at , 0.6, and 0.9 are derived from the mock catalogs. To fit the full power spectra, we propose to use the void average effective radius at a given redshift to simplify the theoretical model, and adopt the Markov Chain Monte Carlo (MCMC) technique to implement the constraints on the cosmological and void parameters. The systematical parameters, such as galaxy and void…
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Taxonomy
TopicsAstronomical Observations and Instrumentation · Stellar, planetary, and galactic studies · Astronomy and Astrophysical Research
