Two of the most important components driving galaxy evolution are the underlying dark matter distribution in which galaxies reside, and neutral hydrogen, the basic baryonic fuel out of which stars and galaxies are made. Yet despite the importance of these components, and rapid advances in predictions from theoretical modelling, our observational knowledge remains extremely limited. ASKAP will radically change this with its unprecedented survey speed.
The Deep Investigation of Neutral Gas Origins survey on ASKAP (DINGO; Meyer, 2009; Duffy et al., 2012) and the Galaxy And Mass Assembly survey (GAMA; Driver et al., 2009) offer the unique opportunity to link the neutral atomic hydrogen content of galaxies (traced by DINGO) with their dark matter halos (traced by GAMA) over cosmologically representative volumes beyond the local Universe. DINGO will have seven times the spatial resolution, twenty times the sensitivity and sample gas seven times further away, compared to previous surveys.
However, in the SKA era, we need to process more data than ever before, indeed more than ever collected before. Spectral line projects, such as DINGO, impose the greatest demands on computing resources. In ICRAR we are tackling this Data Intensive Astronomy problem by exploring how we can manage this flood of information. This PhD project will investigate how we can utilise a public cloud to provide the phenomenal computing power required. This project is supported by the largest provider of cloud computing, Amazon. This is a radically new approach to how radio astronomy data reduction has been done previously and we will need to learn what the advantages and the difficulties are of this approach are. The student will investigate the available cloud services, ideas and methods, demonstrating new approaches to frontier data products.