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Exploring the Structure and Assembly of Galaxies at the Heart of the Coma Cluster

  • Timothy Weinzirl
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Part of the Springer Theses book series (Springer Theses)

Abstract

We constrain the assembly history of galaxies in the projected central 0.5 Mpc of the Coma cluster by performing structural decomposition on 69 massive \((M_{\star } \geq 10^{9}\ M_{\odot })\) galaxies using high-resolution F814W images from the HST Treasury Survey of Coma. Each galaxy is modeled with up to three Sérsic components having a free Sérsic index n. After excluding the two cDs in the projected central 0.5 Mpc of Coma, 57 % of the galactic stellar mass in the projected central 0.5 Mpc of Coma resides in classical bulges/ellipticals while 43 % resides in cold disk-dominated structures. Most of the stellar mass in Coma may have been assembled through major (and possibly minor) mergers. Hubble types are assigned based on the decompositions, and we find a strong morphology-density relation; the ratio of (E+S0):spirals is (91.0 %):9.0 %. In agreement with earlier work, the size of outer disks in Coma S0s/spirals is smaller compared with lower-density environments captured with the Sloan Digital Sky Survey. Among similar-mass clusters from a hierarchical semi-analytic model, no single cluster can simultaneously match all the global properties of the Coma cluster. The model strongly overpredicts the mass of cold gas and underpredicts the mean fraction of stellar mass locked in hot components over a wide range of galaxy masses. We suggest that these disagreements with the model result from missing cluster physics (e.g., ram-pressure stripping), and certain bulge assembly modes (e.g., mergers of clumps). Overall, our study of Coma underscores that galaxy evolution is not solely a function of stellar mass, but also of environment.

Keywords

Outer Disk Low Density Environments (LDEs) Galaxy Stellar Mass Function Nuclear Point Source Classical Bulges 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Timothy Weinzirl
    • 1
  1. 1.Department of AstronomyUniversity of Texas at AustinAustinUSA

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