Comment on the existence of a long range correlation in the geomagnetic disturbance storm time (Dst) index

Very recently (Banerjee et al. in Astrophys. Space, doi:1007/s10509-011-0836-1, 2011) the statistics of geomagnetic Disturbance storm (Dst) index have been addressed, and the conclusion from this analysis suggests that the underlying dynamical process can be modeled as a fractional Brownian motion with persistent long-range correlations. In this comment we expose several misconceptions and flaws in the statistical analysis of that work. On the basis of these arguments, the former conclusion should be revisited.

Site-controlled Ag nanocrystals grown by molecular beam epitaxy-Towards plasmonic integration technology

We demonstrate site-controlled growth of epitaxial Ag nanocrystals on patterned GaAs substrates by molecular beam epitaxy with high degree of long-range uniformity. The alignment is based on lithographically defined holes in which position controlled InAs quantum dots are grown. The Ag nanocrystals self-align preferentially on top of the InAs quantum dots. No such ordering is observed in the absence of InAs quantum dots, proving that the ordering is strain-driven. The presented technique facilitates the placement of active plasmonic nanostructures at arbitrarily defined positions enabling their integration into complex devices and plasmonic circuits.

Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons.

We study the dynamical states of a small-world network of recurrently coupled excitable neurons, through both numerical and analytical methods. The dynamics of this system depend mostly on both the number of long-range connections or ?shortcuts?, and the delay associated with neuronal interactions. We find that persistent activity emerges at low density of shortcuts, and that the system undergoes a transition to failure as their density reaches a critical value. The state of persistent activity below this transition consists of multiple stable periodic attractors, whose number increases at least as fast as the number of neurons in the network. At large shortcut density and for long enough delays the network dynamics exhibit exceedingly long chaotic transients, whose failure times follow a stretched exponential distribution. We show that this functional form arises for the ensemble-averaged activity if the failure time for each individual network realization is exponen- tially distributed