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Galaxy properties in clusters. II. Backsplash Galaxies

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arxiv 1402.3594 v1 pith:3WQ6VVM6 submitted 2014-02-14 astro-ph.CO astro-ph.GA

Galaxy properties in clusters. II. Backsplash Galaxies

classification astro-ph.CO astro-ph.GA
keywords galaxiesclusterssamplevelocitycentralmasspropertiesbacksplash
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We explore the properties of galaxies on the outskirts of clusters and their dependence on recent dynamical history in order to understand the real impact that the cluster core has on the evolution of galaxies. We analyse the properties of more than 1000 galaxies brighter than $M_{^{0.1}r}$=-19.6 on the outskirts of 90 clusters ($1<r/r_{vir}<2$) in the redshift range $0.05<z<0.10$. Using the line of sight velocity, we selected high and low velocity subsamples. Theoretical predictions indicate that a significant fraction of the first subsample should be backsplash galaxies, that is, objects that have already orbited near the cluster centre. A significant proportion of the sample of high relative velocity HV galaxies seems to be composed of infalling objects. Our results suggest that, at fixed stellar mass, late type galaxies in the low velocity LV sample are systematically older, redder and have formed fewer stars during the last 3 Gyrs than galaxies in the HV sample. This result is consistent with models that assume that the central regions of clusters are effective in quenching the star formation by means of processes such as ram pressure stripping or strangulation. At fixed stellar mass, LV galaxies show some evidence of having higher surface brightness and smaller size than HV galaxies. These results are consistent with the scenario where galaxies that have orbited the central regions of clusters are more likely to suffer tidal effects, producing loss of mass as well as a redistribution of matter towards more compact configurations. Finally, we found a higher fraction of ET galaxies in the LV sample, supporting the idea that the central region of clusters of galaxies may contribute to the transformation of morphological types towards earlier types.

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  1. Identifying backsplash galaxies using machine learning

    astro-ph.GA 2026-07 conditional novelty 6.0

    Machine learning trained on The Three Hundred simulations identifies backsplash galaxies in cluster outskirts with ~75% purity/completeness, and has been applied to HI-tail galaxies in Virgo.