Two-Level Laser-like Emission by the Interaction of Self-Induced Transparency Solitons and Surface Anderson Localizations of Light

Self-induced transparency pulses propagating in a random medium embedded in a two-level system can transfer energy to localized Anderson states. This allows the onset of two-level laser-like action.Comment: 5 pages, 5 figures, revised versio

Purely nonlinear disorder-induced localizations and their parametric amplification

We investigate spatial localization in a quadratic nonlinear medium in the presence of randomness. By means of numerical simulations and theoretical analyses we show that, in the down conversion regime, the transverse random modulation of the nonlinear susceptibility generates localizations of the fundamental wave that grow exponentially in propagation. The localization length is optically controlled by the pump intensity which determines the amplification rate. The results also apply to cubic nonlinearities.Comment: 5 pages, 5 figure

Laser propulsion of nanobullets by adiabatic compression of surface plasmon polaritons

Laser propulsion and guide of nanosized objects is fundamental for a wide number of applications. These applications are often limited by the fact that the optical forces acting on nanoparticles are almost negligible even in the favorable case of metallic particles and hence large laser powers are needed to accelerate and guide nanosize devices in practical applications. Furthermore, metallic nanoparticles exhibit strong absorption bands and scattering and this makes more difficult controlling nanopropulsion. Thus, finding some mechanism enhancing the optomechanical interaction at the nanoscale controlled by laser is specifically challenging and pivotal. Here, we demonstrate a novel physical effect where the well-known adiabatic localization of the enhanced plasmonic surface field on the apex of metallic nanocones produces a significant optical pressure employable as a propulsive mechanism. The proposed method gives the possibility to develop new photonics devices to accelerate metallic nanobullets over long distances for a variety of applications

Bibliometric indicators: the origin of their log-normal distribution and why they are not a reliable proxy for an individual scholar’s talent

There is now compelling evidence that the statistical distributions of extensive individual bibliometric indicators collected by a scholar, such as the number of publications or the total number of citations, are well represented by a Log-Normal function when homogeneous samples are considered. A Log-Normal distribution function is the normal distribution for the logarithm of the variable. In linear scale it is a highly skewed distribution with a long tail in the high productivity side. We are still lacking a detailed and convincing ab-initio model able to explain observed Log-Normal distributions-this is the gap this paper sets out to fill. Here, we propose a general explanation of the observed evidence by developing a straightforward model based on the following simple assumptions: (1) the materialist principle of the natural equality of human intelligence, (2) the success breeds success effect, also known as Merton effect, which can be traced back to the Gospel parables about the Talents (Matthew) and Minas (Luke), and, (3) the recognition and reputation mechanism. Building on these assumptions we propose a distribution function that, although mathematically not identical to a Log-Normal distribution, shares with it all its main features. Our model well reproduces the empirical distributions, so the hypotheses at the basis of the model are not falsified. Therefore the distributions of the bibliometric parameters observed might be the result of chance and noise (chaos) related to multiplicative phenomena connected to a publish or perish inflationary mechanism, led by scholars' recognition and reputations. In short, being a scholar in the right tail or in the left tail of the distribution could have very little connection to her/his merit and achievements. This interpretation might cast some doubts on the use of the number of papers and/or citations as a measure of scientific achievements. A tricky issue seems to emerge, that is: what then do bibliometric indicators really measure? This issue calls for deeper investigations into the meaning of bibliometric indicators. This is an interesting and intriguing topic for further research to be carried out within a wider interdisciplinary investigation of the science of science, which may include elements and investigation tools from philosophy, psychology and sociology

Time-resolved dynamics of granular matter by random laser emission

Because of the huge commercial importance of granular systems, the second-most used material in industry after water, intersecting the industry in multiple trades, like pharmacy and agriculture, fundamental research on grain-like materials has received an increasing amount of attention in the last decades. In photonics, the applications of granular materials have been only marginally investigated. We report the first phase-diagram of a granular as obtained by laser emission. The dynamics of vertically-oscillated granular in a liquid solution in a three-dimensional container is investigated by employing its random laser emission. The granular motion is function of the frequency and amplitude of the mechanical solicitation, we show how the laser emission allows to distinguish two phases in the granular and analyze its spectral distribution. This constitutes a fundamental step in the field of granulars and gives a clear evidence of the possible control on light-matter interaction achievable in grain-like system.Comment: 16 pages, 7 figure

On the number of limit cycles in asymmetric neural networks

The comprehension of the mechanisms at the basis of the functioning of complexly interconnected networks represents one of the main goals of neuroscience. In this work, we investigate how the structure of recurrent connectivity influences the ability of a network to have storable patterns and in particular limit cycles, by modeling a recurrent neural network with McCulloch-Pitts neurons as a content-addressable memory system. A key role in such models is played by the connectivity matrix, which, for neural networks, corresponds to a schematic representation of the "connectome": the set of chemical synapses and electrical junctions among neurons. The shape of the recurrent connectivity matrix plays a crucial role in the process of storing memories. This relation has already been exposed by the work of Tanaka and Edwards, which presents a theoretical approach to evaluate the mean number of fixed points in a fully connected model at thermodynamic limit. Interestingly, further studies on the same kind of model but with a finite number of nodes have shown how the symmetry parameter influences the types of attractors featured in the system. Our study extends the work of Tanaka and Edwards by providing a theoretical evaluation of the mean number of attractors of any given length $L$ for different degrees of symmetry in the connectivity matrices.Comment: 35 pages, 12 figure

Random walk of solitary and shock waves in nonlocal disordered media

We study the random walk of solitons and characteristic lines of shock fronts in the presence of disorder for the one-dimensional nonlinear Schr¨ odinger equation in Kerr-like media. We analyze the interplay of nonlocality and randomness, and the way their competition affects strongly coherent nonlinear waves is theoretically and numerically investigated

Effect of dilution in asymmetric recurrent neural networks

We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measures the fraction of neuron couples that are connected, and the network asymmetry measures to what extent the underlying connectivity matrix is asymmetric. For each given neural network, we study the dynamical evolution of all the different initial conditions, thus characterizing the full dynamical landscape without imposing any learning rule. Because of the deterministic dynamics, each trajectory converges to an attractor, that can be either a fixed point or a limit cycle. These attractors form the set of all the possible limit behaviors of the neural network. For each network, we then determine the convergence times, the limit cycles' length, the number of attractors, and the sizes of the attractors' basin. We show that there are two network structures that maximize the number of possible limit behaviors. The first optimal network structure is fully-connected and symmetric. On the contrary, the second optimal network structure is highly sparse and asymmetric. The latter optimal is similar to what observed in different biological neuronal circuits. These observations lead us to hypothesize that independently from any given learning model, an efficient and effective biologic network that stores a number of limit behaviors close to its maximum capacity tends to develop a connectivity structure similar to one of the optimal networks we found.Comment: 31 pages, 5 figure

Shaken Granular Lasers

Granular materials have been studied for decades, also driven by industrial and technological applications. These very simple systems, composed by agglomerations of mesoscopic particles, are characterized, in specific regimes, by a large number of metastable states and an extreme sensitivity (e.g., in sound transmission) on the arrangement of grains; they are not substantially affected by thermal phenomena, but can be controlled by mechanical solicitations. Laser emission from shaken granular matter is so far unexplored; here we provide experimental evidence that it can be affected and controlled by the status of motion of the granular, we also find that competitive random lasers can be observed. We hence demonstrate the potentialities of gravity affected moving disordered materials for optical applications, and open the road to a variety of novel interdisciplinary investigations, involving modern statistical mechanics and disordered photonics.Comment: 4 pages, 3 figures. To be published in Physical Review Letter