Properties of the Intergalactic Magnetic Field Constrained by Gamma-ray Observations of Gamma-Ray Bursts

The magnetic field in intergalactic space gives important information about magnetogenesis in the early universe. The properties of this field can be probed by searching for radiation of secondary e$^+$e$^-$ pairs created by TeV photons, that produce GeV range radiation by Compton-scattering cosmic microwave background (CMB) photons. The arrival times of the GeV "echo" photons depend strongly on the magnetic field strength and coherence length. A Monte Carlo code that accurately treats pair creation is developed to simulate the spectrum and time-dependence of the echo radiation. The extrapolation of the spectrum of powerful gamma-ray bursts (GRBs) like GRB 130427A to TeV energies is used to demonstrate how the IGMF can be constrained if it falls in the $10^{-21}$ - $10^{-17}$ G range for 1 Mpc coherence length.Comment: 8 pages, 6 figure

Gamma-Ray Bursts: Temporal Scales and the Bulk Lorentz Factor

For a sample of Swift and Fermi GRBs, we show that the minimum variability timescale and the spectral lag of the prompt emission is related to the bulk Lorentz factor in a complex manner: For small $\Gamma$'s, the variability timescale exhibits a shallow (plateau) region. For large $\Gamma$'s, the variability timescale declines steeply as a function of $\Gamma$ ($\delta T\propto\Gamma^{-4.05\pm0.64}$). Evidence is also presented for an intriguing correlation between the peak times, t$_p$, of the afterglow emission and the prompt emission variability timescale.Comment: Accepted for publication in Ap

Simultaneous Search and Monitoring by Unmanned Aerial Vehicles

Simultaneous Search and Monitoring (SSM) is studied in this paper for a single Unmanned Aerial Vehicle (UAV) searcher and multiple moving ground targets. Searching for unknown targets and monitoring known targets are two intrinsically related problems, but have mostly been addressed in isolation. We combine the two problems with a joint objective function in a Partially Observable Markov Decision Process (POMDP). An online policy planning approach is proposed to plan a reactive policy to solve the POMDP, using both MonteCarlo sampling and Simulated Annealing. The simulation result shows that the searcher will successfully find unknown targets without losing known ones. We demonstrate, with a theoretical proof and comparative simulations, that the proposed approach can deliver a better performance than conventional foresight optimization methods

Symbiotic relationship between robots - a ROS ARDrone/YouBot library

A Symbiotic relationship between robots is theoretically developed. It is characterised by sharing sensory information and tightly coordinating operational logic by taking care of each other’s needs during missions. The system is characterised by an intertwined reasoning system while having separate conditioning and execution of plans to achieve subgoals to support each other. The results are illustrated on strong operational inter-dependence of a rover and a drone through shared logical inference. The drone uses the rover as a landing pad and the rover uses the drone to complements its sensor system by information gathering. There is a GitHub library provided in association with the demonstration for generic use of adding cameras and cooperation logic to a AR.Drone 2.0 and a KUKA youBot system. The benefits of symbiotic relationship are quantitatively evaluated on the demonstration example