Spatiotemporal Patterns and Predictability of Cyberattacks

Y.C.L. was supported by Air Force Office of Scientific Research (AFOSR) under grant no. FA9550-10-1-0083 and Army Research Office (ARO) under grant no. W911NF-14-1-0504. S.X. was supported by Army Research Office (ARO) under grant no. W911NF-13-1-0141. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Brownian Motion in a Speckle Light Field: Tunable Anomalous Diffusion and Deterministic Optical Manipulation

The motion of particles in random potentials occurs in several natural phenomena ranging from the mobility of organelles within a biological cell to the diffusion of stars within a galaxy. A Brownian particle moving in the random optical potential associated to a speckle, i.e., a complex interference pattern generated by the scattering of coherent light by a random medium, provides an ideal mesoscopic model system to study such phenomena. Here, we derive a theory for the motion of a Brownian particle in a speckle and, in particular, we identify its universal characteristic timescale levering on the universal properties of speckles. This theoretical insight permits us to identify several interesting unexplored phenomena and applications. As an example of the former, we show the possibility of tuning anomalous diffusion continuously from subdiffusion to superdiffusion. As an example of the latter, we show the possibility of harnessing the speckle memory effect to perform some basic deterministic optical manipulation tasks such as guiding and sorting by employing random speckles, which might broaden the perspectives of optical manipulation for real-life applications by providing a simple and cost-effective technique

Uncertainty damping in kinetic traffic models by driver-assist controls

In this paper, we propose a kinetic model of traffic flow with uncertain binary interactions, which explains the scattering of the fundamental diagram in terms of the macroscopic variability of aggregate quantities, such as the mean speed and the flux of the vehicles, produced by the microscopic uncertainty. Moreover, we design control strategies at the level of the microscopic interactions among the vehicles, by which we prove that it is possible to dampen the propagation of such an uncertainty across the scales. Our analytical and numerical results suggest that the aggregate traffic flow may be made more ordered, hence predictable, by implementing such control protocols in driver-assist vehicles. Remarkably, they also provide a precise relationship between a measure of the macroscopic damping of the uncertainty and the penetration rate of the driver-assist technology in the traffic stream