Contatto di riferimento: Marcello Giroletti
Partecipanti: Dr. Jonathan Zwart (University of the Western Cape / University of Cape Town)
Abstract: To push radio-galaxy surveys deeper, one has three options: build a more sensitive telescope, observe for longer with an existing facility, or develop statistical techniques that model subtle noise biases in order to extract the maximum amount of astronomical information contained within.
Our chosen method of beating the survey threshold in this last way is fully bayesian stacking, which can not only be used to derive source counts vital for SKA forecasting work, but which also unlocks a plethora of other physics with existing data sets, including measurement of luminosity functions, star-formation rates and spectral-index distributions.
We have recently demonstrated the technique at 1.4 GHz in the XMM-LSS-VIDEO field, pushing existing VLA data two orders of magnitude deeper than before and doubling the number of source-count measurements in the microJy regime. I will outline the adopted approach and give an update on its application to counting SERVS-selected radio sources in the ELAIS-N1 field, where even deeper JVLA and GMRT total-intensity and polarization data are in hand. Along the way we will see how we are all bayesians.