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Title: Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

Abstract

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, butmore » masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 1014 and ≳ 20 percent for ≲ 1013.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3];  [3];  [4]; ORCiD logo [5]; ORCiD logo [6];  [7];  [1];  [8];  [9];  [10];  [11];  [12];  [3];  [13];  [14];  [15]
  1. Univ. of Toronto, ON (Canada). Dept. of Astronomy & Astrophysics
  2. Stanford Univ., CA (United States). Kavli Inst. for Particle Astrophysics and Cosmology; SLAC National Accelerator Lab., Menlo Park, CA (United States); Univ. of Copenhagen (Denmark). The Niels Bohr Inst., Dark Cosmology Centre
  3. Univ. of Nottingham (United Kingdom). School of Physics and Astronomy
  4. Inst. d' Astrophysique de Paris (France)
  5. Princeton Univ., NJ (United States). Dept. of Astrophysical Sciences; Leiden Univ. (Netherlands). Leiden Observatory
  6. Leibniz Inst. fur Astophysik Potsdam (AIP), Potsdam (Germany); Tartu Observatory, Toravere (Estonia)
  7. INAF-Osservatorio Astronomico di Trieste, Trieste (Italy)
  8. Inst. Nacional de Pesquisas Espaciais, S.J. Campos (Brazil)
  9. Leibniz Inst. fur Astophysik Potsdam (AIP), Potsdam (Germany)
  10. Tartu Observatory, Toravere (Estonia)
  11. Univ. of California, Santa Cruz, CA (United States); Freelance science journalist, San Diego, CA (United States)
  12. Swinburne Univ. of Technology, Hawthorn, VIC (Australia)
  13. Univ. of Western Australia, Crawley, WA (Australia). ICRAR, and ARC Centre of Excellence for All-Sky Astrophysics (CAASTRO)
  14. Stony Brook Univ., NY (United States). Dept. of Physics and Astronomy
  15. Ludwig-Maximilians Univ., Munich (Germany). Faculty of Physics
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); European Research Council (ERC); Science and Technology Facilities Council (STFC)
OSTI Identifier:
1437356
Grant/Contract Number:  
AC02-76SF00515; SEV-2012-0249; CE110001020; AST-1055081; 279396
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 475; Journal Issue: 1; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; galaxies: clusters: general; galaxies: groups: general; galaxies: haloes; galaxies: kinematics and dynamics; cosmological parameters; large-scale structure of Universe

Citation Formats

Old, L., Wojtak, R., Pearce, F. R., Gray, M. E., Mamon, G. A., Sifon, C., Tempel, E., Biviano, A., Yee, H. K. C., de Carvalho, R., Muller, V., Sepp, T., Skibba, R. A., Croton, D., Bamford, S. P., Power, C., von der Linden, A., and Saro, A. Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates. United States: N. p., 2017. Web. doi:10.1093/mnras/stx3241.
Old, L., Wojtak, R., Pearce, F. R., Gray, M. E., Mamon, G. A., Sifon, C., Tempel, E., Biviano, A., Yee, H. K. C., de Carvalho, R., Muller, V., Sepp, T., Skibba, R. A., Croton, D., Bamford, S. P., Power, C., von der Linden, A., & Saro, A. Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates. United States. doi:10.1093/mnras/stx3241.
Old, L., Wojtak, R., Pearce, F. R., Gray, M. E., Mamon, G. A., Sifon, C., Tempel, E., Biviano, A., Yee, H. K. C., de Carvalho, R., Muller, V., Sepp, T., Skibba, R. A., Croton, D., Bamford, S. P., Power, C., von der Linden, A., and Saro, A. Wed . "Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates". United States. doi:10.1093/mnras/stx3241. https://www.osti.gov/servlets/purl/1437356.
@article{osti_1437356,
title = {Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates},
author = {Old, L. and Wojtak, R. and Pearce, F. R. and Gray, M. E. and Mamon, G. A. and Sifon, C. and Tempel, E. and Biviano, A. and Yee, H. K. C. and de Carvalho, R. and Muller, V. and Sepp, T. and Skibba, R. A. and Croton, D. and Bamford, S. P. and Power, C. and von der Linden, A. and Saro, A.},
abstractNote = {With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 1014 and ≳ 20 percent for ≲ 1013.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.},
doi = {10.1093/mnras/stx3241},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 1,
volume = 475,
place = {United States},
year = {2017},
month = {12}
}

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Cited by: 7 works
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Figures / Tables:

Table 1 Table 1: Summary of the 23 cluster mass estimation methods. Listed is an acronym identifying the method, an indication of the main property used to undertake member galaxy selection and an indication of the method used to convert this membership list to a mass estimate. The type of observational datamore » required as input for each method is listed in the fourth column. Note that acronyms denoted with an asterisk indicate that the method did not use our initial object target list but rather matched these locations at the end of their analysis. Please see Tables A1 and A2 in the appendix for more details on each method.« less

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