Please use this identifier to cite or link to this item: http://hdl.handle.net/2248/8579
Title: ASIVA – Platform for observational and computational analysis of stellar variables
Authors: Saleh, P. R
Singh, Tanveer
Hazarika, D
Rajkumari, Surabhi
Rajkumar, Saurabh
Das, Pritam
Parihar, P. S
Saikia, E
Keywords: Astronomical data analysis
Data reduction pipeline
Time series analysis
Variable star analysis
Issue Date: Oct-2024
Publisher: Elsevier B.V
Citation: New Astronomy, Vol. 111, 102232
Abstract: The astronomical data analysis consists of two crucial process; data reduction of the captured images and data analysis of the derived magnitudes. We present the platform ASIVA, a data analysis platform which comes along with a data reduction pipeline. The data reduction pipeline gives flexibility to analyse the FITS images and also perform image alignment for detecting the correct image coordinates for required objects. It can be custom scheduled with cron jobs so that it picks the latest data and appends the results accordingly. The data analysis platform allows user to effectively analyse the ensemble data and perform accurate data processing and grouping with ease. It is integrated with a custom algorithm to detect the variable stars from an ensemble with its relative standard deviations. The statistical, spectral and non-linear dynamics features can be extracted from time series data which can be eventually used for in-depth analysis. To validate the capability, we have analysed 15 nights of Orion Nebula Cluster field in I filter which had 1585 images. ASIVA reduces manual effort to a great extent thus saves analysis time and excludes human errors.
Description: Restricted Access
URI: http://hdl.handle.net/2248/8579
ISSN: 1384-1076
Appears in Collections:IIAP Publications

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