Frontiers in Astronomy and Space Sciences (May 2024)

Optimizing image processing for modern wide field surveys: enhanced data management based on the LSST science pipelines

  • Yuanyu Hong,
  • Yuanyu Hong,
  • Chao Yang,
  • Chao Yang,
  • Miaomiao Zhang,
  • Yanpeng Chen,
  • Yanpeng Chen,
  • Binyang Liu

DOI
https://doi.org/10.3389/fspas.2024.1402793
Journal volume & issue
Vol. 11

Abstract

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Introduction: In recent decades, numerous large survey projects have been initiated to enhance our understanding of the cosmos. Among these, the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) stands out as a flagship project of the Stage IV cosmology imaging surveys, offering an open-source framework for data management and processing adaptable to various instruments.Methods: In this paper, we introduce the ‘obs_mccd’ software package, designed to serve as a bridge linking raw data from generic mosaic-CCD instruments to the LSST data management framework. The package also facilitates the deployment of tailored configurations to the pipeline middleware. To validate our data processing pipeline, we processed a batch of realistic data from a commissioning wide-field telescope.Results: We established a prototype of the quality control (QC) system capable of assessing image quality parameters such as PSF size, ellipticity, and astrometric calibration. Our findings indicate that using a fifth-order polynomial for astrometric calibration effectively characterizes geometric distortion, achieving a median average geometric distortion residual of 0.011 pixel.Discussion: When comparing the performance of our pipeline to our in-house pipeline applied to the same dataset, we observed that our new ‘obs_mccd’ pipeline offers improved precision, reducing the median average geometric distortion residual from 0.016 pixel to 0.011 pixel. This enhancement in performance underscores the benefits of the obs_mccd package in managing and processing data from wide-field surveys, and it opens up new avenues for scientific exploration with smaller, flexible survey systems complementing the LSST.

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