A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION
We present a novel quantitative scheme of cluster classification based on the morphological properties that are manifested in X-ray images. We use a conventional radial surface brightness concentration parameter (c [subscript SB]) as defined previously by others and a new asymmetry parameter, which...
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IOP Publishing
2015
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Online Access: | http://hdl.handle.net/1721.1/93732 |
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author | Nurgaliev, D. Benson, Bradford A. Stubbs, C. W. Vikhlinin, A. McDonald, Michael A. Miller, Eric D |
author2 | MIT Kavli Institute for Astrophysics and Space Research |
author_facet | MIT Kavli Institute for Astrophysics and Space Research Nurgaliev, D. Benson, Bradford A. Stubbs, C. W. Vikhlinin, A. McDonald, Michael A. Miller, Eric D |
author_sort | Nurgaliev, D. |
collection | MIT |
description | We present a novel quantitative scheme of cluster classification based on the morphological properties that are manifested in X-ray images. We use a conventional radial surface brightness concentration parameter (c [subscript SB]) as defined previously by others and a new asymmetry parameter, which we define in this paper. Our asymmetry parameter, which we refer to as photon asymmetry (A [subscript phot]), was developed as a robust substructure statistic for cluster observations with only a few thousand counts. To demonstrate that photon asymmetry exhibits better stability than currently popular power ratios and centroid shifts, we artificially degrade the X-ray image quality by (1) adding extra background counts, (2) eliminating a fraction of the counts, (3) increasing the width of the smoothing kernel, and (4) simulating cluster observations at higher redshift. The asymmetry statistic presented here has a smaller statistical uncertainty than competing substructure parameters, allowing for low levels of substructure to be measured with confidence. A [subscript phot] is less sensitive to the total number of counts than competing substructure statistics, making it an ideal candidate for quantifying substructure in samples of distant clusters covering a wide range of observational signal-to-noise ratios. Additionally, we show that the asymmetry-concentration classification separates relaxed, cool-core clusters from morphologically disturbed mergers, in agreement with by-eye classifications. Our algorithms, freely available as Python scripts (https://github.com/ndaniyar/aphot), are completely automatic and can be used to rapidly classify galaxy cluster morphology for large numbers of clusters without human intervention. |
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institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T08:41:30Z |
publishDate | 2015 |
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spelling | mit-1721.1/937322022-09-30T10:32:14Z A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION Nurgaliev, D. Benson, Bradford A. Stubbs, C. W. Vikhlinin, A. McDonald, Michael A. Miller, Eric D MIT Kavli Institute for Astrophysics and Space Research McDonald, Michael A. Miller, Eric D. We present a novel quantitative scheme of cluster classification based on the morphological properties that are manifested in X-ray images. We use a conventional radial surface brightness concentration parameter (c [subscript SB]) as defined previously by others and a new asymmetry parameter, which we define in this paper. Our asymmetry parameter, which we refer to as photon asymmetry (A [subscript phot]), was developed as a robust substructure statistic for cluster observations with only a few thousand counts. To demonstrate that photon asymmetry exhibits better stability than currently popular power ratios and centroid shifts, we artificially degrade the X-ray image quality by (1) adding extra background counts, (2) eliminating a fraction of the counts, (3) increasing the width of the smoothing kernel, and (4) simulating cluster observations at higher redshift. The asymmetry statistic presented here has a smaller statistical uncertainty than competing substructure parameters, allowing for low levels of substructure to be measured with confidence. A [subscript phot] is less sensitive to the total number of counts than competing substructure statistics, making it an ideal candidate for quantifying substructure in samples of distant clusters covering a wide range of observational signal-to-noise ratios. Additionally, we show that the asymmetry-concentration classification separates relaxed, cool-core clusters from morphologically disturbed mergers, in agreement with by-eye classifications. Our algorithms, freely available as Python scripts (https://github.com/ndaniyar/aphot), are completely automatic and can be used to rapidly classify galaxy cluster morphology for large numbers of clusters without human intervention. National Aeronautics and Space Administration (Hubble Fellowship Grant HST-HF51308.01-A) 2015-02-03T16:54:16Z 2015-02-03T16:54:16Z 2013-12 2013-07 Article http://purl.org/eprint/type/JournalArticle 0004-637X 1538-4357 http://hdl.handle.net/1721.1/93732 Nurgaliev, D., M. McDonald, B. A. Benson, E. D. Miller, C. W. Stubbs, and A. Vikhlinin. “A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION.” The Astrophysical Journal 779, no. 2 (December 20, 2013): 112. © 2013 The American Astronomical Society en_US http://dx.doi.org/10.1088/0004-637x/779/2/112 The Astrophysical Journal Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf IOP Publishing American Astronomical Society |
spellingShingle | Nurgaliev, D. Benson, Bradford A. Stubbs, C. W. Vikhlinin, A. McDonald, Michael A. Miller, Eric D A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title | A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title_full | A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title_fullStr | A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title_full_unstemmed | A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title_short | A ROBUST QUANTIFICATION OF GALAXY CLUSTER MORPHOLOGY USING ASYMMETRY AND CENTRAL CONCENTRATION |
title_sort | robust quantification of galaxy cluster morphology using asymmetry and central concentration |
url | http://hdl.handle.net/1721.1/93732 |
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