Multi-color detection of gravitational arcs
  Strong gravitational lensing provides fundamental insights into the
understanding of the dark matter distribution in massive galaxies, galaxy
clusters and the background cosmology. Despite their importance, the number of
gravitational arcs discovered so far is small. The urge for more complete,
large samples and unbiased methods of selecting candidates is rising. A number
of methods for the automatic detection of arcs have been proposed in the
literature, but large amounts of spurious detections retrieved by these methods
forces observers to visually inspect thousands of candidates per square degree
in order to clean the samples. This approach is largely subjective and requires
a huge amount of eye-ball checking, especially considering the actual and
upcoming wide field surveys, which will cover thousands of square degrees. In
this paper we study the statistical properties of colours of gravitational arcs
detected in the 37 deg^2 of the CARS survey. We have found that most of them
lie in a relatively small region of the (g'-r',r'-i') colour-colour diagram. To
explain this property, we provide a model which includes the lensing optical
depth expected in a LCDM cosmology that, in combination with the sources'
redshift distribution of a given survey, in our case CARS, peaks for sources at
redshift z~1. By further modelling the colours derived from the SED of the
galaxies dominating the population at that redshift, the model well reproduces
the observed colours. By taking advantage of the colour selection suggested by
both data and model, we show that this multi-band filtering returns a sample
83% complete and a contamination reduced by a factor of ~6.5 with respect to
the single-band arcfinder sample. New arc candidates are also proposed.
