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Everything we’d like to do with LSST data, but we don’t know (yet) how

Published online by Cambridge University Press:  30 May 2017

Željko Ivezić ,
Andrew J. Connolly  and
Mario Jurić
Željko Ivezić
Affiliation:
Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195-1580, USA email: [email protected]
Andrew J. Connolly
Affiliation:
Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195-1580, USA email: [email protected]
Mario Jurić
Affiliation:
Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195-1580, USA email: [email protected]
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Abstract

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The Large Synoptic Survey Telescope (LSST), the next-generation optical imaging survey sited at Cerro Pachon in Chile, will provide an unprecedented database of astronomical measurements. The LSST design, with an 8.4m (6.7m effective) primary mirror, a 9.6 sq. deg. field of view, and a 3.2 Gigapixel camera, will allow about 10,000 sq. deg. of sky to be covered twice per night, every three to four nights on average, with typical 5-sigma depth for point sources of r=24.5 (AB). With over 800 observations in ugrizy bands over a 10-year period, these data will enable a deep stack reaching r=27.5 (about 5 magnitudes deeper than SDSS) and faint time-domain astronomy. The measured properties of newly discovered and known astrometric and photometric transients will be publicly reported within 60 sec after observation. The vast database of about 30 trillion observations of 40 billion objects will be mined for the unexpected and used for precision experiments in astrophysics. In addition to a brief introduction to LSST, we discuss a number of astro-statistical challenges that need to be overcome to extract maximum information and science results from LSST dataset.

Keywords

surveysgalaxiesstars: statistics
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S325: Astroinformatics , October 2016 , pp. 93 - 102
Copyright
Copyright © International Astronomical Union 2017 

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