The Square Kilometre Array (SKA) South Africa project plans to explore space using data analytics, in collaboration with IBM.
The project office said big data analytics might help the SKA precursor telescope, MeerKAT, tackle vast data volumes for enhanced images of the sky.
The partnership aims to develop a next-generation big data analytics platform, with self-tuning and self-learning capabilities to better analyse large volumes of radio astronomy data. The proposed software may help automate the process of analysing antenna-collected data, allowing astronomers to more effectively observe objects in space.
The MeerKAT is the largest and most sensitive radio telescope of its kind in the Southern Hemisphere. “Like other radio telescopes, it will require expert data analysis to make high-quality maps of the sky. MeerKAT will consist of 64 dish antennas, each 13.5m in diameter, sensitive to emission from cosmic sources at centimetre wavelengths. Huge volumes of data need to be combined to make detailed images of radio emission from distant objects like black holes, spinning neutron stars, planets, and galaxies. It will also map primeval gas before the galaxies formed, as observed at the edge of the visible universe,” said SKA SA.
The analysis of MeerKAT data is a major challenge. “A number of subtle effects need to be corrected to make clear and accurate images from interferometers like MeerKAT,” said SKA SA scientist Jasper Horrell. “These include variations in the instrument itself and effects such as those introduced by the earth’s ionosphere. More intelligent software is needed to enable astronomers to process and analyse the enormous data rates that will be produced by MeerKAT and future radio telescopes.
The project explains that the current method of analysis requires direct interaction with a computer for hours or days before the images can be used for research purposes. This practice is time-consuming and requires experienced astronomers, making the radio sky accessible to only a few experts.
“The proposed joint research project between SKA SA and IBM is to combine available radio astronomy analysis software with machine-learning techniques currently under development at IBM Research. Beginning with components from IBM’s Infosphere software for big data and IBM’s SPSS software for predictive analysis, the initial phase is intended to program computers to self-learn, adapt, and fine-tune the analysis of radio telescope data under the watchful eye of an astronomer.”
IBM researcher Alain Biem said the goal of the proposed project is to teach a computer to make perfect images on its own.
IBM is also collaborating with Australia on its SKA project, saying the SKA will generate more data in one hour than the World Wide Web.
It partnered with Western Australia’s International Centre for Radio Astronomy Research on the technology needed to manage the vast amounts of data produced by the SKA. The aim of the collaboration is to research and develop systems that transfer, manage, process and store this unprecedented amount of continuous and unstructured radio astronomical data.
SA is bidding against Australia to host the SKA. A decision on the host site will be announced on 4 April, at the earliest. It will consist of about 3 000 dish-shaped antennae and other hybrid receiving technologies.