SIMBAD references

2022MNRAS.512.1916D - Mon. Not. R. Astron. Soc., 512, 1916-1923 (2022/May-2)

The intracluster light on Frontier Fields clusters Abell 370 and Abell S1063.

DE OLIVEIRA N.O.L., JIMENEZ-TEJA Y. and DUPKE R.

Abstract (from CDS):

We analysed the contribution of the intracluster light (ICL) to the total luminosity of two massive galaxy clusters observed by the Hubble Space Telescope within the Frontier Fields program, Abell 370 (z ∼ 0.375) and Abell S1063 (z ∼ 0.348), in order to correlate it with the dynamical stage of these systems. We applied an algorithm based on the Chebyshev-Fourier functions called CICLE, specially developed to disentangle the ICL from the light of galaxies and measure the ICL fraction. We measured the ICL fraction in three broad-band optical filters, F435W, F606W, and F814W, without assuming any prior hypothesis about the ICL physical properties or morphology. The results obtained from the ICL fraction vary between ∼7-25 per cent, and ∼3-22 per cent for both A370 and AS1063, respectively, which are consistent with theoretical predictions for the total amount of ICL obtained by ICL formation and evolution simulations. We found enhanced ICL fractions in the intermediate filter F606W for both clusters and we suggest that this is due to the presence of an excess of younger/lower metallicity stars in the ICL compared to the cluster galaxies. We conclude that both Abell 370 and Abell S1063 are merging systems since they exhibit a similar feature as merging CLASH and Frontier Fields clusters sub-sample previously analysed. We compare these results to the dynamical indicators obtained through different methods and we reinforce the use of ICL as a new and independent method to determine the dynamical state of clusters of galaxies.

Abstract Copyright: © 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society

Journal keyword(s): galaxies: clusters: individual: Abell 370 - galaxies: clusters: individual: Abell S1063 - galaxies: evolution

Simbad objects: 14

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