The IMACS Cluster Building Survey: V. Further Evidence for Starburst Recycling from Quantitative Galaxy Morphologies
Louis E. Abramson (1,2), Alan Dressler (2), Michael D. Gladders (1),, Augustus Oemler (2), Bianca M. Poggianti (3), Andrew Monson (2), Eric Persson, (2), Benedetta Vulcani (4) ((1) University of Chicago/KICP, (2) Carnegie, Observatories, (3) Padova Astronomical Observatory/INAF

TL;DR
This study uses galaxy imaging to analyze morphologies and supports the idea that starbursts are mainly triggered by minor mergers and are part of a recycling process between starforming and quiescent galaxies, with environment playing a limited role.
Contribution
It provides quantitative morphological evidence supporting the recycling model of starbursts and poststarbursts across different environments at intermediate redshifts.
Findings
Starburst and starforming galaxies show structural similarities outside cluster cores.
Poststarburst and passive galaxies are structurally linked, supporting evolutionary connections.
Most starbursts are triggered by minor mergers, not major disruptive events.
Abstract
Using and band imaging obtained as part of the IMACS Cluster Building Survey (ICBS) we measure S\'ersic indices for 2160 field and cluster galaxies at . Using both mass- and magnitude-limited samples, we compare the distributions for spectroscopically determined passive, continuously starforming, starburst, and poststarburst systems and show that previously established spatial and statistical connections between these types extend to their gross morphologies. Outside of cluster cores, we find close structural ties between starburst and continuously starforming, as well as poststarburst and passive types, but not between starbursts and poststarbursts. These results independently support two conclusions presented in Paper II of this ICBS series (Dressler et al.): 1) most starbursts are the product of a non-disruptive triggering mechanism that is insensitive to…
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.
