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Astronomy

Surveying the Sky with the LSST: Software as the Instrument of the Next Decade

A plenary talk from SPIE Astronomical Telescopes + Instrumentation 2016

1 August 2016, SPIE Newsroom. DOI: 10.1117/2.3201607.17

Andrew Connolly, University of Washington (USA)The development of a new generation of telescopes, largescale detectors, and computational facilities has led to an era where it is now possible for deep optical surveys to survey a large fraction of the visible sky. One of the largest of these surveys, the Large Synoptic Survey Telescope (LSST), will comprise an 8.4 m primary mirror with a 9.6 square degree field-of-view and a 3.2 Gigapixel camera and begin operations at the end of this decade. Over the ten years of its  operation, the LSST will survey half of the sky in six optical colors, discovering 37 billion stars and galaxies and detecting about 10 million variable or transient sources every night.

In this plenary session,  Andrew Connolly of University of Washington,  describes the status of the LSST, its potential for studying the nature of dark matter and dark energy, for measuring the properties of our Galaxy, and for creating a census of our Solar System, and describes how advances in computational techniques for analyzing massive data streams might enable the LSST to meet its science objectives.

Andrew Connolly is a professor of astrophysics at the University of Washington, a Washington Research Foundation chair, and the director of the Center for Data Intensive Research in Astrophysics and Cosmology (DIRAC). His research focuses on  understanding the statistical evolution of our universe, by studying how structure forms and evolves on small and large scales-from the search for asteroids to the clustering of distant galaxies. He has been involved in the design and development of the Large Synoptic Sky Survey (LSST) for over a decade and has been working on bringing together computer scientists, statisticians, and astronomers to develop scalable algorithms and techniques for processing massive data streams.