Statistics – Computation
Scientific paper
Aug 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005dps....37.0302m&link_type=abstract
American Astronomical Society, DPS meeting #37, #03.02; Bulletin of the American Astronomical Society, Vol. 37, p.622
Statistics
Computation
Scientific paper
The classical methods of orbit determination cannot cope with the data flow expected from the next generation surveys. The main problem is that the detections of each object within one night do not define an orbit, but only contain information to estimate a four parameters attributable, containing two angles and two angular rates. Orbit determination requires the identification of two or more attributables which can be fit together. The identification problem has a computational complexity growing very steeply with the number N of observable objects, thus with the limiting magnitude of the survey.
New algorithms have been invented to cope even with millions of objects observed per night; they use the concept of admissible region of solar system orbits compatible with a given attributable and the sampling of this region with virtual asteroids selected by means of a triangulation (Milani et al., CMDA vol. 90, 2004). Then the list of attributables of another observing night is scanned looking for possible identification, by using algorithms of complexity N log(N); when one is found, a preliminary orbit is computed and it is used as first guess for differential corrections, either full or constrained (Milani et al., Astron. Astrophys. vol. 431, 2005). These new algorithms have been introduced and tested on a preliminary Pan-STARRS simulation, with very good results; see Milani et al. (Icarus, 2005, in press).
I will discuss the implications of the new orbit determination algorithms and of the recent survey simulation results for the performance of the future surveys. I will also comment on the new understanding of the populations of small bodies of the solar system which will be possible as soon as some of the new surveys is operational.
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