Issue |
A&A
Volume 645, January 2021
|
|
---|---|---|
Article Number | A82 | |
Number of page(s) | 11 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202039332 | |
Published online | 14 January 2021 |
Remarks on generating realistic synthetic meteoroid orbits
Astronomical Observatory Institute, Faculty of Physics, A. Mickiewicz University, ul. Sloneczna 36, 60-286 Poznań, Poland
e-mail: jopek@amu.edu.pl
Received:
3
September
2020
Accepted:
4
November
2020
Context. To identify the real associations of small bodies, we can use synthetic sets of orbits generated by various methods. These are not perfect methods, therefore the assessment of their quality is an essential task.
Aims. In this study, we compared five methods for generating synthetic meteoroid orbits. Three of them (ME0, KD10, and KDns) had already been proposed in the literature, while two additional ones (ME1 and ME4) are new methods.
Methods. As far as possible, the synthetic orbits were compared with the orbits of the observed meteoroids. For quantitative comparison, we applied a few tests: the χ2-distance and the nearest neighbor NNN tests used in previous works, and one-dimensional χ2 and Kolmogorov-Smirnov (K-S) tests, as well as a two-dimensional K-S test implemented in this study. To estimate a general property of the orbital sample, we proposed the use of the entropy HN of the data set based on the nearest neighbor distances. Finally, we did a cluster analysis of the synthetic orbits. We calculated and compared the values of the orbital similarity thresholds.
Results. We showed that generating “realistic” meteoroid orbits and testing their quality is a complex issue. An assessment of the quality of the generated orbits depends on the type of test applied, and it refers to the sample of the observed orbits used. Different tests give different assessments. However, in practice, the investigated methods produced similar results if they were applied correspondingly.
Key words: methods: data analysis / methods: numerical / methods: statistical / meteorites / meteors, meteoroids
© ESO 2021
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