Reprocessing the NEAT Dataset: Preliminary Results
arXiv:2503.20032 · doi:10.3847/PSJ/adbca1
Abstract
We have created a new image analysis pipeline to reprocess images taken by the Near Earth Asteroid Tracking survey and have applied it to ten nights of observations. This work is the first large-scale reprocessing of images from an asteroid discovery survey in which thousands of archived images are re-calibrated, searched for minor planets, and resulting observations are reported to the Minor Planet Center. We describe the software used to extract, calibrate, and clean sources from the images, including specific techniques that accommodate the unique features of these archival images. This pipeline is able to find fainter asteroids than the original pipeline.
13 pages, 7 figures
References in corpus (12)
- Astropy: A Community Python Package for Astronomy
- The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package
- The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
- Gaia Data Release 3: Summary of the content and survey properties
- Astrometry.net: Blind astrometric calibration of arbitrary astronomical images
- astroquery: An Astronomical Web-Querying Package in Python
- Debiased orbit and absolute-magnitude distributions for near-Earth objects
- SSOS: A Moving Object Image Search Tool for Asteroid Precovery
- Surveys, Astrometric Follow-up & Population Statistics
- Mining the ESO WFI and INT WFC archives for known Near Earth Asteroids. Mega-Precovery software
- Mining archival data from wide-field astronomical surveys in search of near-Earth objects
- FindPOTATOs: Minor Planet Observation Linking Software