Research On Data Processing Pipeline For Photometry Of 1.26m Telescope

The 1.26 m optical/infrared telescope is a telescope system jointly operated and maintained by the National Astronomical Observatory and Guangzhou University,and photometric observation is one of the important means of observation for this telescope.The system has a high volume of data output and there have been problems with long data processing cycles and manual interventions in the data reducing process.In order to improve the processing capability of the telescope's observation data,this paper focuses on three issues related to the automatic processing pipeline of the telescope's photometric data: 1)The study analyzed the 1.26 m telescope observation model,and based on the existing software resources and the network star catalog query service,a stable and reliable automated Photometry Pipeline-PP was developed and implemented,which can automatically complete the reconstruction of the FITS file header information,the extraction of image star source information and the matching of the online star catalog,the growth curve method to calculate the optimal aperture,automatic photometry,zero point calculation,time-varying data output and other steps,and finally obtain accurate scientific data.The entire pipeline is characterized by a high degree of automation,no human intervention in the process,and fast operation.2)The research analyzed the problems of the automatic photometry pipeline in the case of poor image quality,and found that PP has a high success rate and better results when processing observation images with a high signal-to-noise ratio and a large number of sources(no less than 10-20 real sources).However,for some of the data with poorer image quality,the processing failure rate is higher,reducing output of valid scientific data,which does not meet the needs of scientific research.The reason for this is that observational images with a small number of sources in the field of view or with a small number of sources due to a low signal-to-noise ratio do not meet the requirement for the number of stars to be matched in the image.3)The method of improving the detection success rate and centering accuracy of stars by image filtering is investigated to ensure that as many stars as possible are used in the image matching step to solve the problem of image matching,and the paper preliminarily tests the detection rate and centering accuracy of the method for weak signals.Overall,this paper achieves a stable and reliable automated photometric data processing pipeline,which realizes and solves the key problems,and the processing results have been applied to relevant scientific research,significantly accelerating the data processing efficiency and improving the scientific output of the 1.26 m telescope and get the good results.