Speaker
Description
Keywords: Near-Earth Objects, Astrometry, Orbit determination
The increasing availability of astrometric data from a wide range of observatories requires a full statistical evaluation of their performances to ensure reliable orbit determination for small bodies, particularly Near-Earth Objects (NEOs). This study presents a systematic statistical analysis of astrometric post-fit residuals for more than 2,500 observatory codes available from Minor Planet Center (MPC)
https://minorplanetcenter.net/iau/lists/ObsCodesF.html.
The MPC, which operates at the Smithsonian Astrophysical Observatory (SAO), collects and provides astrometric observations of small Solar System bodies, including asteroids, comets, and NEOs, along with Potentially Hazardous Objects (PHAs). As the primary repository of astrometry, the MPC plays a crucial role for NASA, ESA, and other institutions in facilitating orbital calculations and long-term monitoring of PHAs.
This study leverages the complete set of post-fit residuals for over 450 million observations submitted to the MPC. Using this extensive data set, we evaluate variations in astrometric error distributions caused by factors such as pixel resolution, telescope aperture, object brightness, stellar catalog used for the astrometric reduction of the observations. We mostly focused on the performance of various survey telescopes, as they contribute the most to the astrometric data.
We conducted a statistical analysis of the post-fit residuals for these surveys. When uncertainty estimates were available, we compared
our results with the submitted uncertainties, providing an additional layer of validation and information on the quality of their reported data. This method has already proven quite useful, for example in the case of the TESS observations.
The MPC published more than 30 million TESS observations over the past couple of years. During a preliminary analysis performed on TESS observations, a bias was identified in the post-fit residuals,
probably due to timing errors, as shown in Fig. 1. Thanks to the result of this analysis, it was possible to fix the bug and to improve the quality of the observations.
These results advance the characterization of uncertainties for ground- and space-based telescopes and create a new approach for improving future orbit determination methodologies.