REAL-TIME ANALYSIS OF LARGE ASTRONOMICAL IMAGES

Abstract

Forthcoming instruments designed for high-cadence large-area surveys, such as the Dark Energy Survey and Large Synoptic Survey Telescope, will generate several GB of data products every few minutes during survey operations. Since such surveys are designed to operate with minimal observer interaction, automated real-time analysis of these large images is necessary to ensure uninterrupted production of science-quality data. We describe a software infrastructure suite designed to support such surveys, focusing particularly on ImageHealth, a tool for near-real-time processing of large images. These image manipulation and analysis algorithms were applied to simulated data from the Dark Energy Survey, as well as observed data collected by the Y4KCam on the CTIO 1 m telescope and the Mosaic camera on the Blanco telescope. The accuracy and speed of the ImageHealth code in particular were benchmarked against results from SourceExtractor, a standard image analysis tool ubiquitous in the astronomical community. ImageHealth is shown to provide comparable accuracy to SourceExtractor when examining bright objects in the focal plane, but with significantly shorter execution time. Based on the importance of real-time analysis in reaching the Dark Energy Survey's science goals, ImageHealth and other aspects of this analysis package were incorporated (in modified form) into the Survey Image System Process Integration, the Dark Energy Camera software control environment. The original ImageHealth code, however, is completely instrument-independent, and is freely available for use within other observational data-taking environments.