We study the surface brightness profiles of a sample of brightest cluster galaxies ( BCGs ) with 0.3 < z < 0.9 .
The BCGs are selected from the first Red-sequence Cluster Survey and an X-ray cluster survey .
The surface brightness profiles of the BCGs are measured using HST ACS images , and the majority of them can be well modeled by a single Sérsic profile with a typical Sérsic index n \sim 6 and a half-light radius \sim 30 kpc .
Although the single Sérsic model fits the profiles well , we argue that the systematics in the sky background measurement and the coupling between the model parameters make the comparison of the best-fit model parameters ambiguous .
Direct comparison of the BCG profiles , on the other hand , has revealed an inside-out growth for these most massive galaxies : as the mass of a BCG increases , the central mass density of the galaxy increases slowly ( \rho _ { 1 kpc } \propto M _ { * } ^ { 0.39 } ) , while the slope of the outer profile grows continuously shallower ( \alpha _ { r ^ { 1 / 4 } } \propto M _ { * } ^ { -2.5 } ) .
Such a fashion of growth continues down to the less massive early-type galaxies ( ETGs ) as a smooth function of galaxy mass , without apparent distinction between BCGs and non-BCGs .
For the very massive ETGs and BCGs , the slope of the Kormendy relation starts to trace the slope of the surface brightness profiles and becomes insensitive to subtle profile evolution .
These results are generally consistent with dry mergers being the major driver of the mass growth for BCGs and massive ETGs .
We also find strong correlations between the richness of clusters and the properties of BCGs : the more massive the clusters are , the more massive the BCGs ( M ^ { * } _ { bcg } \propto M _ { clusters } ^ { 0.6 } ) and the shallower their surface brightness profiles .
After taking into account the bias in the cluster samples , we find the masses of the BCGs have grown by at least a factor of 1.5 from z = 0.5 to z = 0 , in contrast to the previous findings of no evolution .
Such an evolution validates the expectation from the \Lambda CDM model .