The Square Kilometre Array (SKA)

Abstract:

We outline here a simple yet efficient method for finding optimized configurations of the elements of radio-astronomical interferometers with fixed pad locations. The method can be successfully applied, as we demonstrate, to define new configurations when changes to the array take place. This may include the addition of new pads or new antennas, or the loss of pads or antennas. Our method is based on identifying which placement of elements provides the most appropriate u-v plane sampling for astronomical imaging. © 2006. The American Astronomical Society. All rights reserved.

Abstract:

(Abridged) We have used the Rayner & Best (1989) smooth tests of goodness-of-fit to study the Gaussianity of the Very Small Array (VSA) data. Out of the 41 published VSA individual pointings dedicated to cosmological observations, 37 are found to be consistent with Gaussianity, whereas four pointings show deviations from Gaussianity. In two of them, these deviations can be explained as residual systematic effects of a few visibility points which, when corrected, have a negligible impact on the angular power spectrum. The non-Gaussianity found in the other two (adjacent) pointings seems to be associated to a local deviation of the power spectrum of these fields with respect to the common power spectrum of the complete data set, at angular scales of the third acoustic peak (l = 700-900). No evidence of residual systematics is found in this case, and unsubstracted point sources are not a plausible explanation either. If those visibilities are removed, a cosmological analysis based on this new VSA power spectrum alone shows no differences in the parameter constraints with respect to our published results, except for the physical baryon density, which decreases by 10 percent. Finally, the method has been also used to analyse the VSA observations in the Corona Borealis supercluster region (Genova-Santos et al. 2005), which show a strong decrement which cannot be explained as primordial CMB. Our method finds a clear deviation (99.82%) with respect to Gaussianity in the second-order moment of the distribution, and which can not be explained as systematic effects. A detailed study shows that the non-Gaussianity is produced in scales of l~500, and that this deviation is intrinsic to the data (in the sense that can not be explained in terms of a Gaussian field with a different power spectrum).