Reducing the extinction risk of stochastic populations via non-demographic noise

We consider non-demographic noise in the form of uncertainty in the reaction step size, and reveal a dramatic effect this noise may have on the stability of self-regulating populations. Employing the reaction scheme mA->kA, but allowing, e.g., the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly reduce the population's extinction risk compared to the fixed k case. Our analysis is tested against numerical simulations, and by using empirical data of different species, we argue that certain distributions may be more evolutionary beneficial than others.Comment: 9 pages, 8 figures. Accepted for publication as a Rapid Communication in Phys. Rev.

Fixation in Evolutionary Games under Non-Vanishing Selection

One of the most striking effect of fluctuations in evolutionary game theory is the possibility for mutants to fixate (take over) an entire population. Here, we generalize a recent WKB-based theory to study fixation in evolutionary games under non-vanishing selection, and investigate the relation between selection intensity w and demographic (random) fluctuations. This allows the accurate treatment of large fluctuations and yields the probability and mean times of fixation beyond the weak selection limit. The power of the theory is demonstrated on prototypical models of cooperation dilemmas with multiple absorbing states. Our predictions compare excellently with numerical simulations and, for finite w, significantly improve over those of the Fokker-Planck approximation.Comment: 4 figures, to appear in EPL (Europhysics Letters

Integrating Sensor-Network Research and Development into a Software Engineering Curriculum

The emergence of a sensor-networked world produces a clear and urgent need for well-planned, safe and secure software engineering. It is the role of universities to prepare graduates with the knowledge and experience to enter the work-force with a clear understanding of software design and its application to the future safety of computing. The snBench (Sensor Network WorkBench) project aims to provide support to the programming and deployment of Sensor Network Applications, enabling shared sensor embedded spaces to be easily tasked with various sensory applications by different users for simultaneous execution. In this report we discus our experience using the snBench research project as the foundation for semester-long project in a graduate level software engineering class at Boston University (CS511)

Stochastic Model of Breakdown Nucleation under Intense Electric Fields

Plastic response due to dislocation activity under intense electric fields is proposed as a source of breakdown. A model is formulated based on stochastic multiplication and arrest under the stress generated by the field. A critical transition in the dislocation population is suggested as the cause of protrusion formation leading to subsequent arcing. The model is studied using Monte Carlo simulations and theoretical analysis, yielding a simplified dependence of the breakdown rates on the electric field. These agree with experimental observations of field and temperature breakdown dependencies.Comment: 6 pages, 4 figures + Supplemental Materia