Optimizing Automated Classification of Variable Stars in New Synoptic Surveys
نویسندگان
چکیده
منابع مشابه
New Approaches to Object Classification in Synoptic Sky Surveys
Digital synoptic sky surveys pose several new object classification challenges. In surveys where real-time detection and classification of transient events is a science driver, there is a need for an effective elimination of instrument-related artifacts which can masquerade as transient sources in the detection pipeline, e.g., unremoved large cosmic rays, saturation trails, reflections, crossta...
متن کاملAutomated classification of variable stars for ASAS data
With the advent of surveys generating multi-epoch photometry and their discoveries of large numbers of variable stars, the classification of the obtained times series has to be automated. We have developed a classification algorithm for the periodic variable stars using a Bayesian classifier on a Fourier decomposition of the light curve. This algorithm is applied to ASAS (All Sky Automated Surv...
متن کاملThe Automated Detection and Classification of Variable Stars
Variable stars have been an incredibly important discovery since the early days of astronomy. Certain types of variable stars, such as Cepheids, can give not only great insight into the inner dynamics of stars, but also essential parameters of the star, such as luminosity, mass, and the distance from the observer. The number of discovered variable stars has risen dramatically over time, and sev...
متن کاملAutomated classification of variable stars for ASAS 1-2 data
With the advent of surveys generating multi-epoch photometry and the discovery of large numbers of variable stars, the classification of these stars has to be automatic. We have developed such a classification procedure for about 1700 stars from the variable star catalogue of ASAS 1-2 (All Sky Automated Survey, Pojmański 2000) by selecting the periodic ones and by applying an unsupervised Bayes...
متن کاملTowards an Automated Classification of Transient Events in Synoptic Sky Surveys
We describe the development of a system for an automated, iterative, real‐time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly using Bayesian approaches, due to the sparse nature, heterogeneity, and variable incompleteness of the available data. The classifications are improved itera...
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ژورنال
عنوان ژورنال: Publications of the Astronomical Society of the Pacific
سال: 2012
ISSN: 0004-6280,1538-3873
DOI: 10.1086/664960