Statistics with Large Astronomical Data Sets

• Activity Number: 433
• Type: Invited
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistical Learning and Data Mining
• Author(s): Alex Szalay*+
• Companies: Johns Hopkins University
• Keywords: astro-statistics ; big data

Abstract

Astronomy surveys are collecting data from hundreds of millions to billions of celestial objects. These data are accessible through large public databases. These surveys are taken at different wavelengths, and one needs to perform statistical cross-matches to associate the detections with real physical objects. During the statistical analyses of the data astronomers are realizing that with billions of objects statistical noise is less of a problem, but systematic errors are becoming more important. We will discuss various ways, like optimal subspace filtering, of how the known systematic errors can be removed. Finally, as the amount of data collected is going to explode further, it is timely to consider how we could collect less, by focusing on parts of the data with the highest information content. The talk will present examples of these challenges.