Gravitational Wave Astronomy and the Big Data Challenge

Dr Kendall Ackley


The uniquely sensitive Laser Interferometric Gravitational-Wave Observatory (LIGO) facilities have begun routinely detecting signal traces from distant massive black hole and neutron star mergers, some of which happened hundreds of millions of years ago. Representing a multi-layered data analysis problem for real-time and offline analyses, with the aid of computing clusters around the world, successful attempts to extract minute gravitational wave signatures from detector noise have become reality.

On 17 August 2017, LIGO detected its first signal from less massive objects thought to be neutron stars, reinforced by the observation of a coincident weak gamma-ray burst by the Fermi satellite.  Neither instrument has good spatial resolution, and with LIGO being an all-sky instrument, the challenges for astronomers to find the single light-emitting source amongst billions of objects in the sky that is associated with a particular event is not to be understated. Thus began a race of astronomical facilities around the world to be the first to detect the electromagnetic counterpart signal of the event.

The fact that the source was detected within hours of the first alert on the first ever occasion established and validated the field of multi-messenger gravitational wave astronomy, which had been a growing initiative, practically overnight. I will give insights into how this feat was accomplished and, as we begin to build larger and more sensitive telescopes, how we plan to manage the massive in-flux of nightly data, and how we utilise machine-learning to help us accomplish the most data-intensive tasks in an automated fashion.


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