Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data

DES Collaboration

doi:10.1093/mnras/sty2802

Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data

DES Collaboration

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Abstract

Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using counts-in-cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification data from the Dark Energy Survey.We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, cosmic microwave background lensing, and shear + clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion δ_g = Σ³ _k=0(b_k/k!)δ^k, finding a non-zero value for b₂ at the 3σ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large-scale regime (> 30 h^-1 Mpc).

Original language	English
Pages (from-to)	1435-1451
Number of pages	17
Journal	Monthly Notices of the Royal Astronomical Society
Volume	482
Issue number	2
DOIs	https://doi.org/10.1093/mnras/sty2802
State	Published - Jan 11 2019

Funding

We would like to thank Jonathan Loveday for carefully reading the manuscript and providing invaluable feedback that improved the overall quality of this work. We thank Anna M. Porredon for providing theoretical correlation functions for checking purposes and Cora Uhlemann for her insightful comments. We acknowledge the use of data from the MICE simulations, publicly available at http://www.ice.cat/mice.We also acknowledge the use of SCIPY, NUMPY, ASTROPY, HEALPY, EMCEE, and IPYTHON for this work. FJS acknowledges support from the U.S. Department of Energy. Funding for the DES projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico, and the Ministério da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft, and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l'Espai (IEEC/CSIC), the Institut de Física d'Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, the Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, TexasA&MUniversity, and theOzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management system is supported by the National Science Foundation under grant numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. The IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478.We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020, and the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq grant 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. TheUnited StatesGovernment retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. We are grateful for the extraordinary contributions of our CTIO colleagues and the DECam Construction, Commissioning, and Science Verification teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DES Data Management group We acknowledge the use of data from the MICE simulations, publicly available at http://www.ice.cat/mice. We also acknowledge the use of SCIPY, NUMPY, ASTROPY, HEALPY, EMCEE, and IPYTHON for this work. FJS acknowledges support from the U.S. Department of Energy. Funding for the DES projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundac¸ão Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Con-selho Nacional de Desenvolvimento Científico e Tecnológico, and the Ministério da Ciência, Tecnologia e Inovac¸ão, the Deutsche Forschungsgemeinschaft, and the Collaborating Institutions in the Dark Energy Survey. The DES data management system is supported by the National Science Foundation under grant numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. The IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Frame-work Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020, and the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq grant 465376/2014-2). Based in part on observations at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Funders	Funder number
Australian Research Council Centre of Excellence for All-sky Astrophysics	CE110001020
Collaborating Institutions in the Dark Energy Survey
European Union’s Seventh Frame-work Programme
FP7/2007
Fermi Research Alliance, LLC	DE-AC02-07CH11359
INCT
Kavli Institute of Cosmological Physics at the University of Chicago
Ministry of Science and Education of Spain
Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University
National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign
U.S. National Science Foundation
National Science Foundation	AST-1138766, AST-1536171
U.S. Department of Energy
Stanford University
Office of Science
High Energy Physics
University of Pennsylvania
Ohio State University
University of Michigan
University of Portsmouth
Higher Education Funding Council for England
Center for Cosmology and Astroparticle Physics, Ohio State University
Instituto Nacional de Ciência e Tecnologia Midas
Engineering Research Centers	240672, 306478, 291329
Science and Technology Facilities Council
University of Cambridge
European Commission
European Research Council	FP7/2007-2013
University of Nottingham
University of Sussex
University of Edinburgh
Deutsche Forschungsgemeinschaft
Generalitat de Catalunya
Ministerio de Economía y Competitividad	SEV-2016-0588, SEV-2016-0597, ESP2015-66861, MDM-2015-0509, FPA2015-68048, AYA2015-71825
Conselho Nacional de Desenvolvimento Científico e Tecnológico	465376/2014-2
Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
Financiadora de Estudos e Projetos
Ministério da Ciência e Tecnologia
European Regional Development Fund
National Science Foundation

Keywords

Cosmological parameters
Cosmology: observations
Dark energy
Large-scale structure of Universe

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10.1093/mnras/sty2802

Cite this

@article{53f0d6eb689042f4acc26c525f2569e4,

title = "Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data",

abstract = "Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using counts-in-cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification data from the Dark Energy Survey.We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, cosmic microwave background lensing, and shear + clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion δg = Σ3 k=0(bk/k!)δk, finding a non-zero value for b2 at the 3σ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large-scale regime (> 30 h-1 Mpc).",

keywords = "Cosmological parameters, Cosmology: observations, Dark energy, Large-scale structure of Universe",

author = "{DES Collaboration} and Salvador, {A. I.} and S{\'a}nchez, {F. J.} and A. Pagul and J. Garc{\'i}a-Bellido and E. Sanchez and A. Pujol and J. Frieman and E. Gaztanaga and Ross, {A. J.} and I. Sevilla-Noarbe and Abbott, {T. M.C.} and S. Allam and J. Annis and S. Avila and E. Bertin and D. Brooks and Burke, {D. L.} and {Carnero Rosell}, A. and {Carrasco Kind}, M. and J. Carretero and Castander, {F. J.} and Cunha, {C. E.} and {De Vicente}, J. and Diehl, {H. T.} and P. Doel and Evrard, {A. E.} and P. Fosalba and D. Gruen and Gruendl, {R. A.} and J. Gschwend and G. Gutierrez and Hartley, {W. G.} and Hollowood, {D. L.} and James, {D. J.} and K. Kuehn and N. Kuropatkin and O. Lahav and M. Lima and M. March and Marshall, {J. L.} and F. Menanteau and R. Miquel and Romer, {A. K.} and A. Roodman and V. Scarpine and R. Schindler and M. Smith and M. Soares-Santos and F. Sobreira and E. Suchyta",

note = "Publisher Copyright: {\textcopyright} 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.",

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doi = "10.1093/mnras/sty2802",

language = "English",

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T1 - Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data

AU - DES Collaboration

AU - Salvador, A. I.

AU - Sánchez, F. J.

AU - Pagul, A.

AU - García-Bellido, J.

AU - Sanchez, E.

AU - Pujol, A.

AU - Frieman, J.

AU - Gaztanaga, E.

AU - Ross, A. J.

AU - Sevilla-Noarbe, I.

AU - Abbott, T. M.C.

AU - Allam, S.

AU - Annis, J.

AU - Avila, S.

AU - Bertin, E.

AU - Brooks, D.

AU - Burke, D. L.

AU - Carnero Rosell, A.

AU - Carrasco Kind, M.

AU - Carretero, J.

AU - Castander, F. J.

AU - Cunha, C. E.

AU - De Vicente, J.

AU - Diehl, H. T.

AU - Doel, P.

AU - Evrard, A. E.

AU - Fosalba, P.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - Gschwend, J.

AU - Gutierrez, G.

AU - Hartley, W. G.

AU - Hollowood, D. L.

AU - James, D. J.

AU - Kuehn, K.

AU - Kuropatkin, N.

AU - Lahav, O.

AU - Lima, M.

AU - March, M.

AU - Marshall, J. L.

AU - Menanteau, F.

AU - Miquel, R.

AU - Romer, A. K.

AU - Roodman, A.

AU - Scarpine, V.

AU - Schindler, R.

AU - Smith, M.

AU - Soares-Santos, M.

AU - Sobreira, F.

AU - Suchyta, E.

PY - 2019/1/11

Y1 - 2019/1/11

N2 - Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using counts-in-cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification data from the Dark Energy Survey.We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, cosmic microwave background lensing, and shear + clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion δg = Σ3 k=0(bk/k!)δk, finding a non-zero value for b2 at the 3σ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large-scale regime (> 30 h-1 Mpc).

AB - Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using counts-in-cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification data from the Dark Energy Survey.We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, cosmic microwave background lensing, and shear + clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion δg = Σ3 k=0(bk/k!)δk, finding a non-zero value for b2 at the 3σ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large-scale regime (> 30 h-1 Mpc).

KW - Cosmological parameters

KW - Cosmology: observations

KW - Dark energy

KW - Large-scale structure of Universe

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U2 - 10.1093/mnras/sty2802

DO - 10.1093/mnras/sty2802

M3 - Article

AN - SCOPUS:85057141707

SN - 0035-8711

VL - 482

SP - 1435

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JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

IS - 2

ER -

Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data

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