Thermalization through parton transport

A radiative transport model is used to study kinetic equilibration during the early stage of a relativistic heavy ion collision. The parton system is found to be able to overcome expansion and move toward thermalization via parton collisions. Scaling behaviors show up in both the pressure anisotropy and the energy density evolutions. In particular, the pressure anisotropy evolution shows an approximate alpha_s scaling when radiative processes are included. It approaches an asymptotic time evolution on a time scale of 1 to 2 fm/c. The energy density evolution shows an asymptotic time evolution that decreases slower than the ideal hydro evolution. These observations indicate that partial thermalization can be achieved and viscosity is important for the evolution during the early longitudinal expansion stage of a relativistic heavy ion collision.Comment: Presented at the 10th International Conference on Nucleus-Nucleus Collisions (NN2009), Beijing, China, 16-21 Aug 200

Your Actions Tell Where You Are: Uncovering Twitter Users in a Metropolitan Area

Twitter is an extremely popular social networking platform. Most Twitter users do not disclose their locations due to privacy concerns. Although inferring the location of an individual Twitter user has been extensively studied, it is still missing to effectively find the majority of the users in a specific geographical area without scanning the whole Twittersphere, and obtaining these users will result in both positive and negative significance. In this paper, we propose LocInfer, a novel and lightweight system to tackle this problem. LocInfer explores the fact that user communications in Twitter exhibit strong geographic locality, which we validate through large-scale datasets. Based on the experiments from four representative metropolitan areas in U.S., LocInfer can discover on average 86.6% of the users with 73.2% accuracy in each area by only checking a small set of candidate users. We also present a countermeasure to the users highly sensitive to location privacy and show its efficacy by simulations.Comment: Accepted by IEEE Conference on Communications and Network Security (CNS) 201