Baryon content in a sample of 91 galaxy clusters selected by the South Pole Telescope at 0.2 < z < 1.25

Creators: Chiu, I.; Eifler, T. F.; DES Collaboration

Abstract

We estimate total mass (M_(500)), intracluster medium (ICM) mass (M_(ICM)), and stellar mass (M⋆) in a Sunyaev–Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses M_(500) ≳ 2.5 × 10^(14) M⊙ and redshift 0.2 < z < 1.25 from the 2500 deg^2 South Pole Telescope SPT-SZ survey. The total masses M_(500) are estimatedfrom the SZE observable, the ICM masses M_(ICM) are obtained from the analysis of Chandra X-ray observations, and the stellar masses M⋆ are derived by fitting spectral energy distribution templates to Dark Energy Survey griz optical photometry and WISE or Spitzer near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass, and the cold baryonic fraction with cluster halo mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past ≈9 Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low-density environment or field surrounding the parent haloes, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called 'missing baryons' outside cluster virial regions.

Additional Information

© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices). Accepted 2018 May 14. Received 2018 May 10; in original form 2017 November 2. Published: 16 May 2018. IC thanks Chien-Ho Lin, Keiichi Umetsu, Yen-Ting Lin, and James Chan for support and useful discussions during this work. We thank the anonymous referee for the constructive comments that lead to the improvement of this paper. We acknowledge the support by the DFG Cluster of Excellence 'Origin and Structure of the Universe', the DLR award 50 OR 1205 that supported IC during his PhD project, and the Transregio program TR33 'The Dark Universe'. The data processing has been carried out on the computing facilities of the Computational Center for Particle and Astrophysics (C2PAP), located at the Leibniz Supercomputer Center (LRZ) in Garching. The South Pole Telescope is supported by the National Science Foundation through grant PLR-1248097. Partial support is also provided by the NSF Physics Frontier Center grant PHY-1125897 to the Kavli Institute of Cosmological Physics at the University of Chicago, the Kavli Foundation and the Gordon and Betty Moore Foundation grant GBMF 947. This paper has gone through internal review by the DES collaboration. 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, Texas A&M University, and the OzDES Membership Consortium. The DES data management system is supported by the National Science Foundation under Grant Number AST-1138766. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2012-39559, ESP2013-48274, FPA2013-47986, and Centro de Excelencia Severo Ochoa SEV-2012-0234. 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. This work is based in part on archival data obtained with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. This publication makes use of data products from the Wide-field Infrared Survey Explorer (Wright et al. 2010), which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This publication also makes use of data products from NEOWISE, which is a project of the Jet Propulsion Laboratory/California Institute of Technology, funded by the Planetary Science Division of the National Aeronautics and Space Administration. This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalog, and software provided by the Chandra X-ray Center (CXC) in the application packages CIAO, CHIPS, and SHERPA. This research made use of ds9, a tool for data visualization supported by the Chandra X-ray Science Center (CXC) and the High Energy Astrophysics Science Archive Center (HEASARC) with support from the JWST Mission office at the Space Telescope Science Institute for 3D visualization. This paper includes data gathered with the Blanco 4 m telescope, located at the Cerro Tololo Inter-American Observatory in Chile, which is part of the U.S. National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA), under contract with the NSF. This work includes data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under ESO programme ID 179.A-2005 and data products produced by TERAPIX and the Cambridge Astronomy Survey Unit on behalf of the UltraVISTA consortium. This work made use of the IPYTHON package (Pérez & Granger 2007), SciPy (Jones et al. 2001), TOPCAT, an interactive graphical viewer and editor for tabular data (Taylor 2005), matplotlib, a PYTHON library for publication quality graphics (Hunter 2007), Astropy, a community-developed core PYTHON package for Astronomy (Astropy Collaboration 2013), Sherpa (Freeman, Doe & Siemiginowska 2001), XSPEC (Arnaud 1996), NumPy (Van Der Walt, Colbert & Varoquaux 2011).

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