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Title: How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

Abstract

ABSTRACT Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy–halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function wp(rp), the galaxy–galaxy lensing signal ΔΣ(rp), the void probability function VPF(r), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P(N2/N5). We find that despite the frequent use of the combination wp(rp) + ΔΣ(rp) in interpreting galaxy data, the count statistics, P(NCIC) and P(NCIA), are generally more efficient in constraining galaxy assembly bias whenmore » combined with wp(rp). Constraints based upon wp(rp) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of wp(rp) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy–halo connection.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2];  [3];  [4];  [5]; ORCiD logo [6]
  1. Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA, Pittsburgh Particle Physics, Astrophysics, and Cosmology Center (PITT PACC), University of Pittsburgh, Pittsburgh, PA 15260, USA
  2. Department of Astronomy, Yale University, PO Box 208101, New Haven, CT 06511, USA
  3. Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA, McWilliams Center for Cosmology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  4. Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA, Argonne National Laboratory, Argonne, IL 60539, USA
  5. Argonne National Laboratory, Argonne, IL 60539, USA
  6. McWilliams Center for Cosmology, Carnegie Mellon University, Pittsburgh, PA 15213, USA, Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1545973
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Published Article
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Name: Monthly Notices of the Royal Astronomical Society Journal Volume: 488 Journal Issue: 3; Journal ID: ISSN 0035-8711
Publisher:
Oxford University Press
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Wang, Kuan, Mao, Yao-Yuan, Zentner, Andrew R., van den Bosch, Frank C., Lange, Johannes U., Schafer, Chad M., Villarreal, Antonio S., Hearin, Andrew P., and Campbell, Duncan. How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics. United Kingdom: N. p., 2019. Web. doi:10.1093/mnras/stz1733.
Wang, Kuan, Mao, Yao-Yuan, Zentner, Andrew R., van den Bosch, Frank C., Lange, Johannes U., Schafer, Chad M., Villarreal, Antonio S., Hearin, Andrew P., & Campbell, Duncan. How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics. United Kingdom. doi:10.1093/mnras/stz1733.
Wang, Kuan, Mao, Yao-Yuan, Zentner, Andrew R., van den Bosch, Frank C., Lange, Johannes U., Schafer, Chad M., Villarreal, Antonio S., Hearin, Andrew P., and Campbell, Duncan. Tue . "How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics". United Kingdom. doi:10.1093/mnras/stz1733.
@article{osti_1545973,
title = {How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics},
author = {Wang, Kuan and Mao, Yao-Yuan and Zentner, Andrew R. and van den Bosch, Frank C. and Lange, Johannes U. and Schafer, Chad M. and Villarreal, Antonio S. and Hearin, Andrew P. and Campbell, Duncan},
abstractNote = {ABSTRACT Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy–halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function wp(rp), the galaxy–galaxy lensing signal ΔΣ(rp), the void probability function VPF(r), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P(N2/N5). We find that despite the frequent use of the combination wp(rp) + ΔΣ(rp) in interpreting galaxy data, the count statistics, P(NCIC) and P(NCIA), are generally more efficient in constraining galaxy assembly bias when combined with wp(rp). Constraints based upon wp(rp) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of wp(rp) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy–halo connection.},
doi = {10.1093/mnras/stz1733},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 3,
volume = 488,
place = {United Kingdom},
year = {2019},
month = {6}
}

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DOI: 10.1093/mnras/stz1733

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emcee : The MCMC Hammer
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EVOLUTION OF THE STELLAR-TO-DARK MATTER RELATION: SEPARATING STAR-FORMING AND PASSIVE GALAXIES FROM z = 1 TO 0
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Toward a Halo Mass Function for Precision Cosmology: The Limits of Universality
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Properties of galaxy groups in the Sloan Digital Sky Survey -- I. The dependence of colour, star formation and morphology on halo mass
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On halo formation times and assembly bias
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Halo Occupation Distribution Modeling of Clustering of Luminous red Galaxies
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Color dependence in the spatial distribution of satellite galaxies
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Galaxy triplets in Sloan Digital Sky Survey Data Release 7 - I. Catalogue: Galaxy triplets in SDSS DR7
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Redshift-space clustering of SDSS galaxies – luminosity dependence, halo occupation distribution, and velocity bias
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Constraining the Luminous red Galaxy halo Occupation Distribution Using Counts-In-Cylinders
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The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: baryon acoustic oscillations in the Data Release 9 spectroscopic galaxy sample
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The Scale Dependence of Relative Galaxy Bias: Encouragement for the “Halo Model” Description
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Notes on bias in Estimation
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The Dependence on Environment of the Color-Magnitude Relation of Galaxies
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Beyond assembly bias: exploring secondary halo biases for cluster-size haloes
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The importance of satellite quenching for the build-up of the red sequence of present-day galaxies
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Gravitationally Consistent halo Catalogs and Merger Trees for Precision Cosmology
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The Rockstar Phase-Space Temporal halo Finder and the Velocity Offsets of Cluster Cores
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The 2dF Galaxy Redshift Survey: correlation functions, peculiar velocities and the matter density of the Universe
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The Excursion set Theory of halo mass Functions, halo Clustering, and halo Growth
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