info:eu-repo/semantics/masterThesis
3D modelling of near-earth asteroids using lightcurve database
Autor
Jonatan Michimani
Resumen
The record of catastrophic impacts of asteroids towards the Earth, indicates that such phenomena will, to a certainty, occur at some time in the future. Given this threat, the only convenient approach to elaborate a mitigation strategy is to know, as much as possible, the characteristics of the objects with high probability of striking the planet: Near-Earth Asteroids (NEAs). This work focuses on the asteroid characteristics that can be obtain through the synthesis of photometric data i.e. period of rotation, amplitude of the lightcurve, shape and direction of the spin axis or pole. The NEAs (25916) 2001 CP44, (1627) Ivar, (1036) Ganymed (1866) Sisyphus and (450894) 2008 BT 18 were selected to be observed during the months of March, April and May. Subsequent, lightcurve analysis was performed by means of the software MPO Canopus, and last, with the lightcurves available in the ALCDEF data base and the own data, the inversion method was run in MPO LCInvert software. Accordingly, first it is presented lightcurves of the observed objects as well as period of rotation and amplitude of the lightcurve. Asteroids (25916) 2001 CP44, (1627) Ivar, (1036) Ganymed and (1866) Sisyphus show results that are consistent with others previously published, however asteroid (450894) 2008 BT 18, due to its binary nature, did now show conclusive results. Shortly it is also presented the outcomes of the inversion process. For asteroids (25916) 2001 CP44, (1627) Ivar, (1036) Ganymed, the pole direction and shape are close to its true solution, on the other hand, the presented pole and shape of (1866) Sisyphus (450894) 2008 BT 18 are the best fit with the available data and further observations are needed to improve the solution. The results of the characterization process shows that the Schmidt Camera is a suitable instrument for asteroid photometry and hence, INAOE should keep on contributing to the effort of NEAs characterization.
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