59 citations · 80 across the 21 of their papers we have counts for
13 papers · 1 filter
Cross-correlating Squared kSZ and HI Intensity Fields: A Map-level ACT--MeerKAT Forecast
Yu-Er Jiang, Yun Liu, Yan Gong +5
The kinetic Sunyaev--Zel'dovich (kSZ) effect probes the line-of-sight momentum of free electrons, but its blackbody spectrum and velocity-dependent sign make it difficult to isolat…
ELUCID-DESI II. Revealing dark matter mass, tidal, and velocity (MTV) fields using galaxy group phase information
Qingyang Li, Xiaohu Yang, Wensheng Hong +24
We introduce a novel method for reconstructing the cosmic mass, tidal, and velocity (MTV) fields over the redshift range using the phase information of galaxy groups.…
Exploring Primordial Non-Gaussianity Measurements in the CSST Spectroscopic Survey
Jiangnan Duan, Yan Gong, Qi Xiong +5
Primordial non-Gaussianity (PNG) is a fundamental probe of the physics of the early Universe and inflation. Here we present a comprehensive study of the constraints on the local-ty…
Forecasting the Constraint on the Hu-Sawicki Modified Gravity in the CSST pt Photometric Survey
Jun-Hui Yan, Yan Gong, Qi Xiong +5
We forecast the constraint on the Hu-Sawicki model from the photometric survey operated by the Chinese Space Station Survey Telescope (CSST). The simulated pt data…
Exploring Cosmological Constraints of the Void-Lensing Cross-Correlation in the CSST Photometric Survey
Qi Xiong, Yan Gong, Junhui Yan +8
We investigate the cosmological constraints from the void-lensing cross-correlation assuming the CDM model for the Chinese Space Station Survey Telescope (CSST) photometric surv…
Cosmological Prediction from the joint observation of MeerKAT and CSST at = 0.4 1.2
Yu-Er Jiang, Yan Gong, Qi Xiong +10
Cross-correlating neutral hydrogen (HI) 21cm intensity mapping with galaxy surveys provides an effective probe of astrophysical and cosmological information. This work presents a c…
Constraints on the galaxy formation models during epoch of reionization with high redshift observations
Qing-Bo Ma, Xiao-Rong Chen, Ming Li +4
We use high resolution N-body dark matter simulations and L-Galaxies semi-analytical galaxy formation models to explore the high- galaxy properties and estimate the budget of io…
The Jiutian simulations for the CSST extra-galactic surveys
Jiaxin Han, Ming Li, Wenkang Jiang +23
We provide an overview of the Jiutian simulations, a hybrid simulation suite for the China Space Survey Telescope (CSST) extragalactic surveys. It consists of four complementary mo…
Exploring cosmological constraints of the weak gravitational lensing and galaxy clustering joint analysis in the CSST photometric survey
Qi Xiong, Yan Gong, Xingchen Zhou +10
We explore the joint weak lensing and galaxy clustering analysis from the photometric survey operated by the China Space Station Telescope (CSST), and study the strength of the cos…
2D watershed void clustering for probing the cosmic large-scale structure
Yingxiao Song, Yan Gong, Qi Xiong +5
Cosmic void has been proven to be an effective cosmological probe of the large-scale structure (LSS). However, since voids are usually identified in spectroscopic galaxy surveys, t…
Void Number Counts as a Cosmological Probe for the Large-Scale Structure
Yingxiao Song, Qi Xiong, Yan Gong +6
Void number counts (VNC) indicates the number of low-density regions in the large-scale structure (LSS) of the Universe, and we propose to use it as an effective cosmological probe…
Cosmological Prediction of the Void and Galaxy Clustering Measurements in the CSST Spectroscopic Survey
Yingxiao Song, Qi Xiong, Yan Gong +10
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 t…
Cosmological Forecast of the Void Size Function Measurement from the CSST Spectroscopic Survey
Yingxiao Song, Qi Xiong, Yan Gong +11
Void size function (VSF) contains 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 VSF…