2012MNRAS.419.3354F

The European Southern Observatory's (ESO) Visible and Infrared Survey Telescope for Astronomy (VISTA) is a 4-m class survey telescope for wide-field near-infrared imaging. VISTA is currently running a suite of six public surveys, which will shortly deliver their first Europe wide public data releases to ESO. The VISTA Kilo-degree Infrared Galaxy survey (VIKING) forms a natural intermediate between current wide shallow and deeper more concentrated surveys, by targeting two patches totalling 1500 deg² in the Northern and Southern hemispheres with measured 5σ limiting depths of Z ≃ 22.4, Y ≃ 21.4, J ≃ 20.9, H ≃ 19.9 and K_s ≃ 19.3 (Vega). This architecture forms an ideal working parameter space for the discovery of a significant sample of 6.5 ≤ z ≤ 7.5 quasars. In the first data release, priority has been placed on small areas encompassing a number of fields well sampled at many wavelengths, thereby optimizing science gains and synergy whilst ensuring a timely release of the first products. For rare object searches, e.g. high-z quasars, this policy is not ideal since photometric selection strategies generally evolve considerably with the acquisition of data. Without a reasonably representative data set sampling many directions on the sky, it is not clear how a rare object search can be conducted in a highly complete and efficient manner.

In this paper, we alleviate this problem by supplementing initial data with a realistic model of the spatial, luminosity and colour distributions of sources known to heavily contaminate photometric quasar selection spaces, namely dwarf stars of spectral types M, L and T. We use this model along with a subset of available data to investigate contamination of quasar selection space by cool stars and galaxies and lay down a set of benchmark selection constraints that limit contamination to reasonable levels whilst maintaining high completeness as a function of both magnitude and redshift. We review recent follow-up imaging of the first VIKING high-z quasar candidates and find that the results lend considerable support for the choice of selection constraints. The methods outlined here are also applicable to rare object searches in a number of other ongoing and forthcoming projects.