DMTN-080: Coaddition Artifact Rejection and CompareWarp
- Department of Astrophysical Sciences, Princeton University
LSST images will be contaminated with transient artifacts, such as optical ghosts, satellite trails, and cosmic rays, and with transient astronomical sources, such as asteroid ephemerides. We developed and tested an algorithm to find and reject these artifacts during coaddition, in order to produce clean coadds to be used for deep detection and preliminary object characterization. This algorithm, CompareWarpAssembleCoadd, uses the time-series of PSF-matched warped images to identify transient artifacts. It detects artifact candidates on the image differences between each PSF-matched warp and a static sky model. These artifact candidates include both true transient artifacts and difference-image false positives such as difficult-subtract-sources and variable sources such as stars and quasars. We use the feature that true transients appear at a given position in the difference images in only a small fraction (configurable) of visits, whereas variable sources and difficult-to-subtract sources appear in most difference images. In this report, we present a description of the method and an evaluation using Hyper SuprimeCam PDR1 data.
- Research Organization:
- NSF-DOE Vera C. Rubin Observatory
- Sponsoring Organization:
- U.S. National Science Foundation; U.S. Department of Energy Office of Science
- DOE Contract Number:
- AC02-76SF00515
- OSTI ID:
- 2583441
- Report Number(s):
- Vera C. Rubin Observatory Data Management Technical Note DMTN-080
- Country of Publication:
- United States
- Language:
- English
SDSS data management and photometric quality assessment
|
journal | October 2004 |
Detection and removal of artifacts in astronomical images
|
journal | July 2016 |
The Hyper Suprime-Cam software pipeline
|
journal | October 2017 |
DMTN-015: Flavors of Coadds
|
dataset | January 2016 |
| RTN-095: The Vera C. Rubin Observatory Data Preview 1 | dataset | July 2025 |
DMTN-197: Streak Masking in DM Image Processing
|
dataset | January 2021 |
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