Bouncing localized structures in a liquid-crystal light-valve experiment

Experimental evidence of bouncing localized structures in a nonlinear optical system is reported.Comment: 4 page

Spatiotemporal chaos induces extreme events in an extended microcavity laser

Extreme events such as rogue wave in optics and fluids are often associated with the merging dynamics of coherent structures. We present experimental and numerical results on the physics of extreme events appearance in a spatially extended semiconductor microcavity laser with intracavity saturable absorber. This system can display deterministic irregular dynamics only thanks to spatial coupling through diffraction of light. We have identified parameter regions where extreme events are encountered and established the origin of this dynamics in the emergence of deterministic spatiotemporal chaos, through the correspondence between the proportion of extreme events and the dimension of the strange attractor

JPEG steganography with particle swarm optimization accelerated by AVX

Digital steganography aims at hiding secret messages in digital data transmitted over insecure channels. The JPEG format is prevalent in digital communication, and images are often used as cover objects in digital steganography. Optimization methods can improve the properties of images with embedded secret but introduce additional computational complexity to their processing. AVX instructions available in modern CPUs are, in this work, used to accelerate data parallel operations that are part of image steganography with advanced optimizations.Web of Science328art. no. e544

The X-CLASS - redMaPPer galaxy cluster comparison: I. Identification procedures

We performed a detailed and, for a large part interactive, analysis of the matching output between the X-CLASS and redMaPPer cluster catalogues. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters respectively. X-ray cluster matching rates were analysed as a function of optical richness. In a second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10^{-15} erg s^{-1} cm^{-2} in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Main results show that neither of the wavebands misses any massive cluster (as coded by X-ray luminosity or optical richness). After correcting for obvious pipeline short-comings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~ 80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centers. The fraction of clusters totally dominated by AGN-type emission appears to be of the order of a few percent. Conversely ~ 40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the fact that the X-CLASS sample extends further out than redMaPPer (z<1 vs z<0.6); extending the correlation down to a richness of 5, raises the matching rate to ~ 65%.Comment: 15 pages, 20 figures, 2 table

Universal shape law of stochastic supercritical bifurcations: Theory and experiments

A universal law for the supercritical bifurcation shape of transverse one-dimensional (1D) systems in presence of additive noise is given. The stochastic Langevin equation of such systems is solved by using a Fokker-Planck equation leading to the expression for the most probable amplitude of the critical mode. From this universal expression, the shape of the bifurcation, its location and its evolution with the noise level are completely defined. Experimental results obtained for a 1D transverse Kerr-like slice subjected to optical feedback are in excellent agreement.Comment: 5 pages, 5 figure

Extreme events prediction from nonlocal partial information in a spatiotemporally chaotic microcavity laser

The forecasting of high-dimensional, spatiotemporal nonlinear systems has made tremendous progress with the advent of model-free machine learning techniques. However, in real systems it is not always possible to have all the information needed; only partial information is available for learning and forecasting. This can be due to insufficient temporal or spatial samplings, to inaccessible variables or to noisy training data. Here, we show that it is nevertheless possible to forecast extreme events occurrence in incomplete experimental recordings from a spatiotemporally chaotic microcavity laser using reservoir computing. Selecting regions of maximum transfer entropy, we show that it is possible to get higher forecasting accuracy using nonlocal data vs local data thus allowing greater warning times, at least twice the time horizon predicted from the nonlinear local Lyapunov exponent