2011A&A...534A..35C

We use the surface brightness fluctuation (SBF) technique to derive the distances and analyse the radial behaviour of stellar populations in a sample of 12 elliptical galaxies. The data are I-band images collected with the FORS1 camera at the Very Large Telescope (VLT), drawn from the ESO archive. The main purpose of our analysis is to carry out the study of SBF magnitudes without relying on additional colour information that is normally required in SBF studies. We measure I-band SBF magnitudes and SBF variations with galaxy radii, which is useful for stellar population studies. Unlike typical applications of the SBF technique, the absolute SBF magnitudes needed to evaluate the distance moduli are derived using the fluctuation star count, N. The distances obtained using the N calibration taken from the literature show a good agreement with available estimates. We find a median ∼0.2mag difference between our and literature distance moduli, with the only exception of NGC5090, which shows the I-band SBF ∼1mag brighter than expected. The median statistical and systematic errors are ∼0.2 and ∼0.1mag, respectively. On these grounds we consider the test of deriving SBF distances based on the N calibration to be successful. Taking into account that some of the previously estimated distances were made as long as 15 years ago, the new measurements provide an updated sketch on distances for a set of galaxies towards the region of the Great Attractor. Furthermore, gauging the SBF of the unresolved stellar systems has returned negative SBF radial gradients in the inner regions of five galaxies: a feature already known and explained by lower metallicity at larger galactic radii. Somehow unexpectedly, though, we detect positive SBF gradients at large radii (>20kpc) in nine targets. This behaviour, if it is not caused by some unaccounted observational bias, could be explained at least partly as a statistical effect on the stellar counts at these radii. Additional (near-IR) observations are necessary to confirm the real existence of this feature and to allow us to reach more robust conclusions.