First On-Site Data Analysis System for Subaru/Suprime-Cam

Details First On-Site Data Analysis System for Subaru/Suprime-Cam First On-Site Data Analysis System for Subaru/Suprime-Cam

Mar 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011pasj...63s.585f&link_type=abstract

Publications of the Astronomical Society of Japan, Vol.63, No.SP2, pp.585--603

Astronomy and Astrophysics

Astronomy

Astronomical Data Bases: Miscellaneous, Methods: Data Analysis, Techniques: Image Processing

Scientific paper

We developed an automated on-site quick analysis system for mosaic CCD data of Suprime-Cam, which is a wide-field camera mounted at the prime focus of the Subaru Telescope, Mauna Kea, Hawaii. The first version of the data-analysis system was constructed, and started to operate in general observations. This system is a new function of observing support at the Subaru Telescope to provide the Subaru user community with an automated on-site data evaluation, aiming at improvements of observers' productivity, especially in large imaging surveys. The new system assists the data evaluation tasks in observations by the continuous monitoring of the characteristics of every data frame during observations. The evaluation results and data frames processed by this system are also useful for reducing the data-processing time in a full analysis after an observation. The primary analysis functions implemented in the data-analysis system are composed of automated realtime analysis for data evaluation and on-demand analysis, which is executed upon request, including mosaicing analysis and flat making analysis. In data evaluation, which is controlled by the organizing software, the database keeps track of the analysis histories, as well as the evaluated values of data frames, including seeing and sky background levels; it also helps in the selection of frames for mosaicing and flat making analysis. We examined the system performance and confirmed an improvement in the data-processing time by a factor of 9 with the aid of distributed parallel data processing and on-memory data processing, which makes the automated data evaluation effective.

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