Asteroid orbital ranging using Markov-Chain Monte Carlo

We present a novel Markov-Chain Monte-Carlo orbitalranging method (MCMC) for poorly observed single-apparition asteroids with two or more observations. We examine the Bayesian a posteriori probability density of the orbital elementsusing methods that map a volume of orbitsin the orbital-element phase space. In particular, we use the MCMC method to sample the phase spacein an unbiased way. We study the speed of convergence and also the efficiency of the new method for the initial orbit computation problem. We present the results of the MCMC ranging method applied to three objects from different dynamical groups. We conclude that the method is applicable to initial orbitcomputation for near-Earth, main-belt, and transneptunian objects.