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Published April 20, 2018 | Published + Accepted Version
Journal Article Open

Unveiling the Dynamical State of Massive Clusters through the ICL Fraction

Abstract

We have selected a sample of 11 massive clusters of galaxies observed by the Hubble Space Telescope in order to study the impact of the dynamical state on the intracluster light (ICL) fraction, the ratio of total integrated ICL to the total galaxy member light. With the exception of the Bullet cluster, the sample is drawn from the Cluster Lensing and Supernova Survey and the Frontier Fields program, containing five relaxed and six merging clusters. The ICL fraction is calculated in three optical filters using the CHEFs ICL estimator, a robust and accurate algorithm free of a priori assumptions. We find that the ICL fraction in the three bands is, on average, higher for the merging clusters, ranging between ~7% and 23%, compared with the ~2%–11% found for the relaxed systems. We observe a nearly constant value (within the error bars) in the ICL fraction of the regular clusters at the three wavelengths considered, which would indicate that the colors of the ICL and the cluster galaxies are, on average, coincident and, thus, so are their stellar populations. However, we find a higher ICL fraction in the F606W filter for the merging clusters, consistent with an excess of lower-metallicity/younger stars in the ICL, which could have migrated violently from the outskirts of the infalling galaxies during the merger event.

Additional Information

© 2018 The American Astronomical Society. Received 2018 January 31; revised 2018 March 6; accepted 2018 March 13; published 2018 April 17. We thank the referee for constructive comments that helped to improve the original manuscript. Y.J.-T. would like to thank Dr. Marc Postman for his support, help, and encouragement during her stay at the STScI, which made this work possible. We gratefully acknowledge the computational support of Dr. Fernando Roig. Y.J.-T. also acknowledges financial support from the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ; fellowship Nota 10, PDR-10) through grant E-26/202.835/2016 and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES; Science without Borders program, Young Talent Fellowship, BJT) through grant A062/2013. R.A.D. acknowledges support from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) through BP grant 312307/2015-2 and the Financiadora de Estudos e Projetos (FINEP) grant REF. 1217/13-01.13.0279.00. Both Y.J.-T. and R.A.D. also acknowledge support from the Spanish National Research Council (CSIC; I-COOP+2016 program) through grant COOPB20263 and the Spanish Ministry of Economy, Industry, and Competitiveness (MINECO) through grants AYA2013-48623-C2-1-P and AYA2016-81065-C2-1-P. K.U. acknowledges support from the Ministry of Science and Technology of Taiwan (grant MOST 103-2628-M-001-003-MY3) and from the Academia Sinica Investigator Award. M.M. acknowledges support from the Italian Ministry of Foreign Affairs and International Cooperation, Directorate General for Country Promotion.

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Published - Jiménez-Teja_2018_ApJ_857_79.pdf

Accepted Version - 1803.04981.pdf

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August 19, 2023
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