Galaxy halo truncation and Giant Arc Surface Brightness Reconstruction in the Cluster MACSJ1206.2-0847
Thomas Eichner, Stella Seitz, Sherry H. Suyu, Aleksi Halkola, Keiichi, Umetsu, Adi Zitrin, Dan Coe, Anna Monna, Piero Rosati, Claudio Grillo, Italo, Balestra, Marc Postman, Anton Koekemoer, Wei Zheng, Ole H{\o}st, Doron Lemze,, Tom Broadhurst, Leonidas Moustakas, Larry Bradley

TL;DR
This study models the mass distribution of galaxy cluster MACSJ1206.2-0847, focusing on galaxy halo properties and surface brightness reconstruction of a giant arc, revealing tidally stripped halos and detailed source morphology.
Contribution
It provides a detailed analysis of galaxy halo properties within a cluster using strong lensing and surface brightness reconstruction, a novel approach for this cluster.
Findings
Galaxy halos are tidally stripped with halo sizes around 26 kpc.
The cluster mass distribution is well modeled with an NFW profile.
Reconstructed source galaxy shows spiral arms and older central components.
Abstract
In this work we analyze the mass distribution of MACSJ1206.2-0847, especially focusing on the halo properties of its cluster members. The cluster appears relaxed in its X-ray emission, but has significant amounts of intracluster light which is not centrally concentrated, suggesting that galaxy-scale interactions are still ongoing despite the overall relaxed state. The cluster lenses 12 background galaxies into multiple images and one galaxy at into a giant arc and its counterimage. The multiple image positions and the surface brightness distribution (SFB) of the arc which is bent around several cluster members are sensitive to the cluster galaxy halo properties. We model the cluster mass distribution with a NFW profile and the galaxy halos with two parameters for the mass normalization and extent of a reference halo assuming scalings with their observed NIR--light. We match…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
