Data Association and Track Management for the Gaussian Mixture Probability Hypothesis Density Filter

The Gaussian mixture probability hypothesis density (GM-PHD) recursion is a closed-form solution to the probability hypothesis density (PHD) recursion, which was proposed for jointly estimating the time-varying number of targets and their states from a sequence of noisy measurement sets in the presence of data association uncertainty, clutter, and miss-detection. However the GM-PHD filter does not provide identities of individual target state estimates, that are needed to construct tracks of individual targets. In this paper, we propose a new multi-target tracker based on the GM-PHD filter, which gives the association amongst state estimates of targets over time and provides track labels. Various issues regarding initiating, propagating and terminating tracks are discussed. Furthermore, we also propose a technique for resolving identities of targets in close proximity, which the PHD filter is unable to do on its own.     

Time-dependent thermal X-ray afterglows from GRBS

Time-dependent thermal X-ray spectra are calculated from physically plausible conditions around GRB. It is shown that account for time-dependent ionization processes strongly affects the observed spectra of hot rarefied plasma. These calculations may provide an alternative explanation to the observed X-ray lines of early GRBs afterglows (such as GRB 011211). Our technique will allow one to obtain independent constraints on the GRB collimation angle and on the clumpiness of circumstellar matter.     

Magnetospheric Models and Trajectory Computations

The calculation of particle trajectories in the Earth's magnetic field has been a subject of interest since the time of Störmer. The fundamental problem is that the trajectory-tracing process involves using mathematical equations that have `no solution in closed form'. This difficulty has forced researchers to use the `brute force' technique of numerical integration of many individual trajectories to ascertain the behavior of trajectory families or groups. As the power of computers has improved over the decades, the numerical integration procedure has grown more tractable and while the problem is still formidable, thousands of trajectories can be computed without the expenditure of excessive resources. As particle trajectories are computed and the characteristics analyzed we can determine the cutoff rigidity of a specific location and viewing direction and direction and deduce the direction in space of various cosmic ray anisotropies. Unfortunately, cutoff rigidities are not simple parameters due to the chaotic behavior of the cosmic-ray trajectories in the cosmic ray penumbral region. As the computational problem becomes more manageable, there is still the issue of the accuracy of the magnetic field models. Over the decades, magnetic field models of increasing complexity have been developed and utilized. The accuracy of trajectory calculations employing contemporary magnetic field models is sufficient that cosmic ray experiments can be designed on the basis of trajectory calculations. However, the Earth's magnetosphere is dynamic and the most widely used magnetospheric models currently available are static. This means that the greatest uncertainly in the application of charged particle trajectories occurs at low energies.     

Problems with the concept of the inflationary universe

The picture of an exponentially increasing, “inflationary” phase of the early universe (Guth 1981; Linde 1982; Albrecht and Steinhardt 1982) may point the way to an understanding of our present universe without reference to extremely specific initial conditions. The model rests, however, on several assumptions which deserve critical examination.