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Application of multivariate analysis methods to search for variable stars in the Pi of the Sky experiment
Author(s): Lukasz Obara
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Paper Abstract

The purpose of this article is to present novel algorithm for searching variable stars in the Pi of the Sky data, based on Multivariate Analysis (MVA). Pi of the Sky is a system of wide field-of-view robotic telescopes, which search for short timescale astrophysical phenomena, especially for prompt optical emission from GRB. The system was designed for autonomous operation, monitoring a large fraction of the sky with 12m -13m range and time resolution of the order of 1 - 100 seconds. Dedicated photometric algorithm was implemented in the LUIZA framework and optimized on a sample of test sky images. It was then used on a ”training” image sample, which was obtained by modifying the test sample of images, using different patterns of variability to selected constant stars. Different statistical estimators were considered to find the most efficient algorithm, based on MVA method, for variable star identification. Analysis of the test results indicated that most efficient candidate star selection can be based on the so called Boosted Decision Tree (BDT) approach. The algorithm is then used to search for variable star candidates in the actual data. New results of the analysis and three candidate stars found are presented.

Paper Details

Date Published: 7 August 2017
PDF: 8 pages
Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017, 1044544 (7 August 2017); doi: 10.1117/12.2280842
Show Author Affiliations
Lukasz Obara, Univ. of Warsaw (Poland)


Published in SPIE Proceedings Vol. 10445:
Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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