A Study on Quantitative Assessment of Usability and Stability for deepCR Cosmic Ray Identification Methods in CSST Survey Data Processing

The deepCR cosmic ray identification method could effectively remove cosmic rays from the Hubble Space Telescope (HST). However, there needs to be more quantitative analysis on whether this method can meet the China Space Telescope (CSST) requirements. In this paper, we analyze the deepCR cosmic ray method in-depth using real observational data from the Hubble Telescope. We conducted an empirical study of its stability and usability. The results show that deepCR performs well in identifying the cosmic ray in the sky background region, but its sensitivity decreases as it approaches to the centre of star. We analyze the correlation between the cosmic ray density and the photometric accuracy, demonstrating that when the cosmic ray density reaches 9%, alomost all stars(100%) are contaminated by cosmic rays; when the cosmic ray density reaches 14%, there are abnormal photometric results(20%-50%) for stars with different contour areas. The analysis shows that the deepCR cosmic ray identification model is relatively stable and can be applied over a longer period of time after one model. However, it still faces a series of problems in application scenarios, such as high-precision photometry, which need to be addressed in the near future.