Inverse methods for asteroid orbit computation

Statistical asteroid-orbit-computation methods have proven important for applications such as computing the collision probability, performing dynamical classification, identifying asteroids, and aiding the recovery of lost objects. These methods will be of major importance during the Gaia mission (to be launched in 2012). Here we discuss these methods and some of their applications and potentials. As earlier, we examine the Bayesian a posteriori probability density of the orbital elements using Monte-Carlo methods that map the discretized volume of solutions in the orbital-element phase space. In particular, we use the Markov-chain Monte-Carlo (MCMC) method to map the phase space. The marginal orbital-element distributions then serve as a base for applications as collision probability computation, dynamical classification and others. A number of recent applications are presented. Importance of the method for the Gaia mission is also described.