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COSMOS: Stochastic Bias from Measurements of Weak Lensing and Galaxy Clustering

Jullo, Eric and Rhodes, Jason and Kiessling, Alina and Taylor, James E. and Massey, Richard and Bergé, Joel and Schimd, Carlo and Kneib, Jean-Paul and Scoville, Nick (2012) COSMOS: Stochastic Bias from Measurements of Weak Lensing and Galaxy Clustering. Astrophysical Journal, 750 (1). Art. No. 37. ISSN 0004-637X. doi:10.1088/0004-637X/750/1/37.

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In the theory of structure formation, galaxies are biased tracers of the underlying matter density field. The statistical relation between galaxy and matter density field is commonly referred to as galaxy bias. In this paper, we test the linear bias model with weak-lensing and galaxy clustering measurements in the 2 deg^2 COSMOS field. We estimate the bias of galaxies between redshifts z = 0.2 and z = 1 and over correlation scales between R = 0.2 h^(–1) Mpc and R = 15 h^(–1) Mpc. We focus on three galaxy samples, selected in flux (simultaneous cuts I_(814W) < 26.5 and K_s < 24) and in stellar mass (10^9 < M_* < 10^(10) h^(–2) M_☉ and 10^(10) < M_* < 10^(11) h^(–2) M_☉). At scales R > 2 h^(–1) Mpc, our measurements support a model of bias increasing with redshift. The Tinker et al. fitting function provides a good fit to the data. We find the best-fit mass of the galaxy halos to be log (M_(200)/h^(–1) M_☉) = 11.7^(+0.6)_(–1.3) and log (M_(200)/h^(–1) M_☉) = 12.4^(+0.2)_(–2.9), respectively, for the low and high stellar-mass samples. In the halo model framework, bias is scale dependent with a change of slope at the transition scale between the one and the two halo terms. We detect a scale dependence of bias with a turndown at scale R = 2.3 ± 1.5 h^(–1) Mpc, in agreement with previous galaxy clustering studies. We find no significant amount of stochasticity, suggesting that a linear bias model is sufficient to describe our data. We use N-body simulations to quantify both the amount of cosmic variance and systematic errors in the measurement.

Item Type:Article
Related URLs:
URLURL TypeDescription
Jullo, Eric0000-0002-9253-053X
Rhodes, Jason0000-0002-4485-8549
Massey, Richard0000-0002-6085-3780
Kneib, Jean-Paul0000-0002-4616-4989
Scoville, Nick0000-0002-0438-3323
Additional Information:© 2012 American Astronomical Society. Received 2011 March 25; accepted 2012 February 22; published 2012 April 13. We thank the referee for his insightful comments that led to a significant improvement of the paper. It is also a pleasure to thank Chris Hirata and Fabian Schmidt for useful discussions and helpful suggestions. We also gratefully thank Alexie Leauthaud for her help and advice and for providing the COSMOS lensing catalog. This work was done in part at JPL, operated by Caltech under a contract for NASA. E.J. acknowledges support from the Jet Propulsion Laboratory, in contract with the California Institute of Technology, and the NASA Postdoctoral Program. R.M. is supported by an STFC Advanced Fellowship. This work uses observations obtained with the Hubble Space Telescope. The HST COSMOS Treasury program was supported through NASA grant HST-GO-09822. It is also a pleasure to thank Chris Hirata, Fabian Schmidt and Christopher Bonnett for useful discussions and helpful suggestions. Support for Program No. HST-AR-12136.01-A was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555.
Group:COSMOS, Infrared Processing and Analysis Center (IPAC)
Funding AgencyGrant Number
NASA Postdoctoral ProgramUNSPECIFIED
Science and Technology Facilities Council (STFC)UNSPECIFIED
Subject Keywords: cosmology: observations; gravitational lensing: weak; large-scale structure of universe
Issue or Number:1
Record Number:CaltechAUTHORS:20120523-113027587
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Official Citation: COSMOS: Stochastic Bias from Measurements of Weak Lensing and Galaxy Clustering Eric Jullo et al. 2012 ApJ 750 37
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:31617
Deposited On:23 May 2012 20:50
Last Modified:09 Nov 2021 19:56

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