ATLAS: Big Data in a Small Package?

Abstract

For even small astronomy projects, the petabyte scale is now upon us. The Asteroid Terrestrial-impact Last Alert System (Tonry 2011) will survey the entire visible sky from Hawaii multiple times per night to search for near-Earth asteroids on impact trajectories. While the ATLAS optical system is modest by modern astronomical standards — two 0.5 m F/2.0 telescopes — each night the ATLAS system will measure nearly 10⁹ astronomical sources to a photometric accuracy of <5%, totaling 10¹² individual observations over its initial 3-year mission. This ever-growing dataset must be searched in real-time for moving objects and transients then archived for further analysis, and alerts for newly discovered near-Earth asteroids (NEAs) disseminated within tens of minutes from detection. ATLAS's all-sky coverage ensures it will discover many ‘rifle shot’ near-misses moving rapidly on the sky as they shoot past the Earth, so the system will need software to automatically detect highly-trailed sources and discriminate them from the thousands of low-Earth orbit (LEO) and geosynchronous orbit (GEO) satellites ATLAS will see each night. Additional interrogation will identify interesting phenomena from millions of transient sources per night beyond the solar system. The data processing and storage requirements for ATLAS demand a ‘big data’ approach typical of commercial internet enterprises. We describe our experience in deploying a nimble, scalable and reliable data processing infrastructure, and suggest ATLAS as steppingstone to data processing capability needed as we enter the era of LSST.