Membership analysis of open cluster and Variable stars
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Study of Open Star Clusters (OSCs) is a prerequisite for understanding the structure of Galactic disk and evolution of Galaxy. As a consequence, search of stellar variability within OSCs are commonly used to provide an effective tool to stellar evolution history and sites of stellar formation. Variable stars identify by time series data. The time series data of each night is standardized through a set of standard data of photometry. The comprehensive studies have been carried out by the using the data of PPMXL, 2MASS catalogues with the standardized UBVRI data set. These data sets also provide...
Study of Open Star Clusters (OSCs) is a prerequisite for understanding the structure of Galactic disk and evolution of Galaxy. As a consequence, search of stellar variability within OSCs are commonly used to provide an effective tool to stellar evolution history and sites of stellar formation. Variable stars identify by time series data. The time series data of each night is standardized through a set of standard data of photometry. The comprehensive studies have been carried out by the using the data of PPMXL, 2MASS catalogues with the standardized UBVRI data set. These data sets also provide the details of stellar proper motion. The statistical analyses of these datasets provide the various probabilities of clusters' members. In this book, we explore various membership probabilities and hypothesis technique to identify the most probable members in an OSC. We propose the mechanism/hueristion than can be corelate various parameters of OSCs with the stellar evolution. Our performance results indicate clear benefit is using the present membership algorithm over previous one. The secondary standardization method is helpful to identify the dependent frequencies of the variable stars.
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