The Link Between Morphology and Structure of Brightest Cluster Galaxies:
  Automatic Identification of cDs
  We study a large sample of 625 low-redshift brightest cluster galaxies (BCGs)
and link their morphologies to their structural properties. We derive visual
morphologies and find that ~57% of the BCGs are cD galaxies, ~13% are
ellipticals, and ~21% belong to the intermediate classes mostly between E and
cD. There is a continuous distribution in the properties of the BCG's
envelopes, ranging from undetected (E class) to clearly detected (cD class),
with intermediate classes (E/cD and cD/E) showing the increasing degrees of the
envelope presence. A minority (~7%) of BCGs have disk morphologies, with
spirals and S0s in similar proportions, and the rest (~2%) are mergers. After
carefully fitting the galaxies light distributions by using one-component
(Sersic) and two-component (Sersic+Exponential) models, we find a clear link
between the BCGs morphologies and their structures and conclude that a
combination of the best-fit parameters derived from the fits can be used to
separate cD galaxies from non-cD BCGs. In particular, cDs and non-cDs show very
different distributions in the $R_e$--$RFF$ plane, where $R_e$ is the effective
radius and $RFF$ (the residual flux fraction) measures the proportion of the
galaxy flux present in the residual images after subtracting the models. In
general, cDs have larger $R_e$ and $RFF$ values than ellipticals. Therefore we
find, in a statistically robust way, a boundary separating cD and non-cD BCGs
in this parameter space. BCGs with cD morphology can be selected with
reasonably high completeness (~75%) and low contamination (~20%). This
automatic and objective technique can be applied to any current or future BCG
sample with good quality images.
