Vortex deformation and breaking in superconductors: a microscopic description

Vortex breaking has traditionally been studied for non-uniform critical current densities, although it may also appear due to non-uniform pinning force distributions. In this article we study the case of a high-pinning/low-pinning/high-pinning layered structure. We have developed an elastic model for describing the deformation of a vortex in these systems in the presence of a uniform transport current density J for any arbitrary orientation of the transport current and the magnetic field. If J is above a certain critical value, J(c), the vortex breaks and a finite effective resistance appears. Our model can be applied to some experimental configurations where vortex breaking naturally exists. This is the case for YBa2Cu3O7-delta (YBCO) low-angle grain boundaries and films on vicinal substrates, where the breaking is experienced by Abrikosov-Josephson vortices (AJV) and Josephson string vortices (SV), respectively. With our model, we have experimentally extracted some intrinsic parameters of the AJV and SV, such as the line tension is an element of(l) and compared it to existing predictions based on the vortex structure.

Precise modal excitation in multimode fibre for control of modal dispersion and mode-group division multiplexing

Each mode of a multimode fibre is excited using binary phase patterns on a Spatial Light Modulator and verified by observation of the near-field leaving the fibre and analysis of the step response. © 2011 OSA.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Future, opportunities and challenges of inkjet technologies

Inkjet printing relies on the formation of small liquid droplets to deliver precise amounts of material to a substrate under digital control. Inkjet technology is becoming relatively mature and is of great industrial interest thanks to its flexibility for graphical printing and its potential use in less conventional applications such as additive manufacturing and the production of printed electronics and other functional devices. Its advantages over traditional methods of printing include the following: it produces little or no waste, it is versatile because several different methods exist, it is noncontact, and it does not require a master template so that printed patterns can be readily modified on demand. However, the technology is in need of further development to become mainstream in emerging applications such as additive manufacturing (3D printing). This review contains a description of conventional and less common inkjet methods and surveys the current applications of inkjet in industry. This is followed by specific examples of the barriers, limitations, and challenges faced by inkjet technology in both graphical printing and manufacturing. © 2013 by Begell House, Inc.

Frequency locked micro disk resonator for real time and precise monitoring of refractive index.

We experimentally demonstrate a frequency modulation locked servo loop, locked to a resonance line of an on-chip microdisk resonator in a silicon nitride platform. By using this approach, we demonstrate real-time monitoring of refractive index variations with a precision approaching 10(-7) RIU, using a moderate Q factor of 10(4). The approach can be applied for intensity independent, dynamic and precise index of refraction monitoring for biosensing applications.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

Precise modal excitation in multimode fibre for control of modal dispersion and mode-group division multiplexing

Each mode of a multimode fibre is excited using binary phase patterns on a Spatial Light Modulator and verified by observation of the near-field leaving the fibre and analysis of the step response. © 2011 OSA.

Towards a unified description of rocking structures

Numerous studies on the rigid rocking block have generated a wealth of knowledge about rocking behavior. However, evaluation of more complex rocking systems requires the derivation and solution of complicated equations of motion. This paper investigates the possibility of a unified description of several rocking systems through investigation of rocking mechanisms which describe the masonry wall and the masonry arch. Effective rocking parameters are derived for each of these structures, and the similarity of the rocking behavior is discussed. The error of the proposed approximation, which defines the limitations for this approach, is quantified for the example structures considered. Where appropriate, a unified description of rocking would allow the use of rocking spectra, which would be useful to readily predict the response of a wide array of rocking structures.