Redshift Evolution and Covariances for Joint Lensing and Clustering Studies with DESI Y1
Monthly Notices of the Royal Astronomical Society(2024)
Stanford Univ | Swinburne Univ Technol | Perimeter Inst Theoret Phys | Univ Michigan | Ohio State Univ | Univ Calif Santa Cruz | Lawrence Berkeley Natl Lab | Boston Univ | Argonne Natl Lab | UCL | IPN | Univ Los Andes | Univ Texas Dallas | Inst Estudis Espacials Catalunya IEEC | Univ Portsmouth | Aix Marseille Univ | Univ Autonoma Barcelona | NSFs NOIRLab | Chinese Acad Sci | Kansas State Univ | Sejong Univ | CIEMAT | Max Planck Inst Extraterr Phys | Ohio Univ | Univ Nacl Autonoma Mex
Abstract
Galaxy-galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy-halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N-body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in 0.4
MoreTranslated text
Key words
methods: numerical,methods: statistical,galaxies: haloes,large-scale structure of Universe
PDF
View via Publisher
AI Read Science
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2010
被引用312 | 浏览
2011
被引用53 | 浏览
2011
被引用672 | 浏览
2015
被引用102 | 浏览
2015
被引用17 | 浏览
2019
被引用61 | 浏览
2018
被引用112 | 浏览
2020
被引用23 | 浏览
2019
被引用148 | 浏览
2020
被引用976 | 浏览
2021
被引用20 | 浏览
2021
被引用81 | 浏览
2021
被引用47 | 浏览
2021
被引用36 | 浏览
2023
被引用24 | 浏览
2022
被引用39 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话