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We study the irreversible growth of magnetic thin films under the influence of spatially periodic fields by means of extensive Monte Carlo simulations. We find first-order pseudo-phase transitions that separate a dynamic...

"We discuss the connections between Brownian ratchets (BR) and stochastic resonance (SR). We consider a periodic potential energy landscape with no left–right symmetry that is driven by an external force which can be ...

"We investigate the influence of an anonymous leader on a collective of self-propelled robots using Kilobot experiments and numerical simulations. {Each robot possesses a binary internal state that determines the directi...

"We present experimental results on the information transmission and storage via stochastic resonance in circuits designed and built around Schmitt triggers (STs). First, we investigate the performance of a transmission ...

"We recently showed that a ring of two bistable oscillators is capable of storing a single bit of information via stochastic resonance. Memory performance was characterized in terms of the probability of erroneous bit de...

"The increasing capacity of modern computers, driven by Moore’s Law, is accompanied by smaller noise margins and higher error rates. In this paper we propose a memory device, consisting of a ring of two identical overd...

"In this paper we analyze the properties of a chain of forward-coupled bi-stable over-damped oscillators. It is well known that this system displays stochastic resonance and behaves as a transmission line when an adequat...

Abstract Recently a surface plasmon resonance (SPR) optical sensor, based on the Otto configuration — the Otto chip — has been developed. One essential step in the quality control of the fabrication process is charac...

Stern-Gerlach interferometer (SGI) is a kind of matter-wave interferometer driven by magnetic field and has been proposed for various gravity experiments. Stochastic noises can lead to decoherence problems of SGI via var...

The problem of stochastic averaging of the decayed dynamics of the output state population of a one-step transformation process with constant deterministic forward transition rate and randomly varying return transition r...

The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain ...