We apply a versatile numerical technique to establishing the existence of cavity solitons (CS) in a semiconductor microresonator with bulk GaAs or multiple quantum well GaAs/AlGaAs as its active layer. Based on a Newton method, our approach implies the evaluation of the linearized operator describing deviations from the exact stationary state. The eigenvalues of this operator determine the dynamical stability of the CS. A typical eigenspectrum contains a zero eigenvalue with which a “neutral mode” of the CS is associated. Such neutral modes are characteristic of models with translational symmetry. All other eigenvalues typically have negative real parts large enough to cause any excitations to die out in a few medium response times. The neutral mode thus dominates the response to external random or deterministic perturbations, and its excitation induces a simple translation of the CS, which are thus stable and robust. We show how to relate the speed with which a CS moves under external perturbations to the projection of the perturbations on to the neutral mode, and give some examples, including weak gradients on the driving field and interaction with other CS. Finally, we show that the separatrix between two stable coexisting solutions: the homogeneous solution and the CS is the intervening unstable CS solution. Our results are important with a view to future applications of CS to optical information processing.

In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brain scans (in the age range 7-64years). We introduce a structural connectivity model of the human brain: MRI scans are divided in rectangular boxes and Pearson's correlation is measured among them in order to obtain a complex network model. Brain connectivity is then characterized through few and easy-to-interpret centrality measures; finally, brain age is predicted by feeding a compact deep neural network. The proposed approach is accurate, robust and computationally efficient, despite the large and heterogeneous dataset used. Age prediction accuracy, in terms of correlation between predicted and actual age r=0.89and Mean Absolute Error MAE =2.19years, compares favorably with results from state-of-the-art approaches. On an independent test set including 262 subjects, whose scans were acquired with different scanners and protocols we found MAE =2.52. The only imaging analysis steps required in the proposed framework are brain extraction and linear registration, hence robust results are obtained with a low computational cost. In addition, the network model provides a novel insight on aging patterns within the brain and specific information about anatomical districts displaying relevant changes with aging.

We consider the paraxial model for a nonlinear resonator with a saturable absorber beyond the mean-field limit. For accessible parametric domains we observe total radiation confinement and the formation of 3D localized bright structures. Different from freely propagating light bullets, here the self-organization proceeds from the resonator feedback, combined with diffraction and nonlinearity. Such “cavity” light bullets can be independently excited and erased by appropriate pulses, and once created, they endlessly travel the cavity round-trip.

The VLF/LF radio signals method for studying preseimic activity is applied to the Abruzzo earthquake (M=6.3, 6 April 2009). The data collected by three receivers located in Moscow (Russia), Graz (Austria) and Bari (Italy) at about 3000 km, 1000 km and 500 km from the epicenter were used. The signals received from the Sardinia (20.27 kHz) and the Sicily (45.9 kHz) transmitters, both located in Italy, were compared with those received from the Iceland (37.5 kHz), the Great Britain (19.58 kHz) and the Germany (23.4 kHz) transmitters. The propagation paths of the two Italian transmitters cross the epicentral area (seismic paths) unlike the paths of the other three signals (control paths). Using two different analyses, that are the study of the night-time signal and the research of shifts in the evening terminator times, clear anomalies were revealed 2–8 days before the occurrence of the Abruzzo earthquake in the seismic paths, while no anomalies have been found in the control paths.

Cavity solitons are stationary self-organized bright intensity peaks which form over a homogeneous background in the section of broad area radiation beams. They are generated by shining a writing/erasing laser pulse into a nonlinear optical cavity, driven by a holding beam. The ability to control their location and their motion by introducing phase or amplitude gradients in the holding beam makes them interesting as mobile pixels for all-optical processing units. We show the generation of a number of cavity solitons in broad-area vertical cavity semiconductor microresonators electrically pumped above transparency but slightly below threshold. We analyze the switching process in details. The observed spots can be written, erased, and manipulated as independent objects, as predicted by the theoretical model. An especially tailored one is used to simulate the studied phenomena and to compare our simulations to the experimental findings with good agreement.