TY - JOUR
T1 - Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1
AU - Yuan, Sihan
AU - Blake, Chris
AU - Krolewski, Alex
AU - Lange, Johannes
AU - Elvin-Poole, Jack
AU - Leauthaud, Alexie
AU - DeRose, Joseph
AU - Aguilar, Jessica Nicole
AU - Ahlen, Steven
AU - Beltz-Mohrmann, Gillian
AU - Brooks, David
AU - Claybaugh, Todd
AU - de la Macorra, Axel
AU - Doel, Peter
AU - Placida Emas, Ni Putu Audita
AU - Ferraro, Simone
AU - Forero-Romero, Jaime E.
AU - Garcia-Quintero, Cristhian
AU - Gaztañaga, Enrique
AU - Gontcho, Satya Gontcho A.
AU - Hadzhiyska, Boryana
AU - Heydenreich, Sven
AU - Honscheid, Klaus
AU - Ishak, Mustapha
AU - Joudaki, Shahab
AU - Jullo, Eric
AU - Kisner, Theodore
AU - Kremin, Anthony
AU - Lambert, Andrew
AU - Landriau, Martin
AU - Manera, Marc
AU - Meisner, Aaron
AU - Miquel, Ramon
AU - Nie, Jundan
AU - Palanque-Delabrouille, Nathalie
AU - Poppett, Claire
AU - Porredon, Anna
AU - Rezaie, Mehdi
AU - Ross, Ashley J.
AU - Rossi, Graziano
AU - Ruggeri, Rossana
AU - Sanchez, Eusebio
AU - Saulder, Christoph
AU - Seo, Hee Jong
AU - Silber, Joseph Harry
AU - Tarln, Gregory
AU - Vargas-Magaña, Mariana
AU - Weaver, Benjamin Alan
AU - Xhakaj, Enia
AU - Zhou, Zhimin
N1 - Publisher Copyright:
© 2024 The Author(s).
PY - 2024/9/1
Y1 - 2024/9/1
N2 - 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 < z < 0.8, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width ∆z = 0.1, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of 0.1h−1 Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.
AB - 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 < z < 0.8, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width ∆z = 0.1, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of 0.1h−1 Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.
KW - galaxies: haloes
KW - large-scale structure of Universe
KW - methods: numerical
KW - methods: statistical
KW - UKRI
KW - STFC
UR - http://www.scopus.com/inward/record.url?scp=85201060370&partnerID=8YFLogxK
U2 - 10.1093/mnras/stae1792
DO - 10.1093/mnras/stae1792
M3 - Article
AN - SCOPUS:85201060370
SN - 0035-8711
VL - 533
SP - 589
EP - 607
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
IS - 1
ER -