摘要
The measurement of cosmological distances using baryon acoustic oscillations(BAO)is crucial for studying the universe’s expansion.The China Space Station Telescope(CSST)galaxy redshift survey,with its vast volume and sky coverage,provides an opportunity to address key challenges in cosmology.However,redshift uncertainties in galaxy surveys can degrade both angular and radial distance estimates.In this study,we forecast the precision of BAO distance measurements using mock CSST galaxy samples,applying a two-point correlation function(2PCF)wedge approach to mitigate redshift errors.We simulate redshift uncertainties of σ_(0)=0.003 andσ_(0)=0.006,representative of expected CSST errors,and examine their effects on the BAO peak and distance scaling factors,α_(⊥)andα_(||),across redshift bins within 0.0<z≤1.0.The wedge 2PCF method proves more effective in detecting the BAO peak compared with the monopole 2PCF,particularly forσ_(0)=0.006.Constraints on the BAO peaks show thatα_(⊥)is well constrained around 1.0,regardless of σ_(0),with precision between 1%and 3%across redshift bins.In contrast,α_(||)measurements are more sensitive to increases inσ_(0).Forσ_(0)=0.003,the results remain close to the fiducial value,with uncertainties ranging between 4%and 9%;forσ_(0)=0.006,significant deviations from the fiducial value are observed.We also study the ability to measure parameters(Ω_(m),H_(0)r_(d))using distance measurements,proving robust constraints as a cosmological probe under CSST-like redshift uncertainties.These findings demonstrate that the CSST survey enables few-percent precision measurements of D_(A)using the wedge 2PCF method,highlighting its potential to place tight constraints on the universe’s expansion history and contribute to high-precision cosmological studies.
基金
supported by the National SKA Program of China(Grant Nos.2022SKA0110200 and 2022SKA0110202)
the National Key Research and Development Program of China(Grant Nos.2023YFA1607800,2023YFA1607802,2023YFA1607804,and 2022YFF0503400)
the National Natural Science Foundation of China(Grant Nos.12103037 and12273020)
the 111 Project(Grant No.B20019)
Shanghai Natural Science Foundation(Grant No.19ZR1466800)
the science research grants from the China Manned Space Project(Grant Nos.CMS-CSST-2021-A02,CMS-CSST-2021-A03,and CMS-CSST-2021-B01)
the Fundamental Research Funds for the Central Universities(Grant No.XJS221312)
supported by Science Research Project of Hebei Education Department No.BJK2024134
supported by the High-Performance Computing Platform of Xidian University。
