Towards a rigorous treatment of the Jeans-Landau-Teller method for the energy exchanges of harmonic oscillators

For classical Hamiltonian systems containing an harmonic oscillator of high frequency, one has the problem of controlling the energy exchange between the oscillator and the remaining slow degrees of freedom; under very general conditions, such an exchange turns out to be exponentially small with the frequency of the oscillator. In the Jeans-Landau-Teller method, one aims to prove the exponential dependence, and to estimate the coefficient of the exponential, by exploiting the analyticity properties of the solution of the differential equations describing the motion of the system. However, in practice, since the exact solution is not known, such properties are inferred from those of an approximate solution, with no control of the difference; this fact might a priori even invalidate the exponential dependence itself. In the present paper a rigorous treatment is given, for a particular model of interest in the domain of atomic collisions, by keeping control of the difference between the exact and the approximate solution.     

Clustering of financial time series

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.     

Scaling, Optimality, and Landscape Evolution

A nonlinear model is studied which describes the evolution of a landscape under the effects of erosion and regeneration by geologic uplift by mean of a simple differential equation. The equation, already in wide use among geomorphologists and in that context obtained phenomenologically, is here derived by reparametrization invariance arguments and exactly solved in dimension d=1. Results of numerical simulations in d=2 show that the model is able to reproduce the critical scaling characterizing landscapes associated with natural river basins. We show that configurations minimizing the rate of energy dissipation (optimal channel networks) are stationary solutions of the equation describing the landscape evolution. Numerical simulations show that a careful annealing of the equation in the presence of additive noise leads to configurations very close to the global minimum of the dissipated energy, characterized by mean field exponents. We further show that if one considers generalized river network configurations in which splitting of the flow (i.e., braiding) and loops are allowed, the minimization of the dissipated energy results in spanning loopless configurations, under the constraints imposed by the continuity equations. This is stated in the form of a general theorem applicable to generic networks, suggesting that other branching structures occurring in nature may possibly arise as optimal structures minimizing a cost function.     

Poincaré-Invariant Markov Processes and Gaussian Random Fields on Relativistic Phase Space

We give a complete characterization, including a Lévy–Itô decomposition, of Poincaré-invariant Markov processes on , the relativistic phase space in 1+1 spacetime dimensions. Then, by means of such processes, we construct Poincaré-invariant Gaussian random fields, and we prove a no-go theorem for the random fields corresponding to Brownian motions on .     

Cladding mode reorganization in high-refractive-index-coated long-period gratings: effects on the refractive-index sensitivity

We theoretically and experimentally investigated the reorganization of cladding modes in high-refractive-index- (HRI-) coated long-period gratings (LPGs), focusing on the influence of refractive-index sensitivity. When azimuthally symmetric nanoscale HRI coatings are deposited along LPG devices, a significant modification of the distribution of cladding modes occurs, depending on the layers' features (refractive index and thickness) and on the external refractive index. In particular, if these parameters are properly chosen, a transition between cladding modes and overlay modes occurs. Numerical and experimental effects of the mode transition on the sensitivity of the surrounding refractive index are described.     

Structural characterization of nanopatterned surfaces

In this work, chemically and topographically nanopatterned surfaces were produced by a top-down processing approach for biosensing devices. The nanopatterning was the result of the combination of plasma polymerisation (pp) of biofunctional materials and colloidal lithography techniques. The morphological and chemical properties induced by the plasma deposition-etching treatment were characterised by optical method combining ellipsometry and Fourier Transform Infrared spectroscopy studies. This method supported by atomic force microscopy measurements, allowed the full optical characterization of each step of the top-down process. The optical characterization of the end-up nanopatterned samples demonstrated that the chosen process is able to produce well-defined nanostructured surfaces with controlled chemical and morphological properties.     

Entanglement and factorized ground states in two-dimensional quantum antiferromagnets

Making use of exact results and quantum Monte Carlo data for the entanglement of formation, we show that the ground state of anisotropic two-dimensional S=1/2 antiferromagnets in a uniform field takes the classical-like form of a product state for a particular value and orientation of the field, at which the purely quantum correlations due to entanglement disappear. Analytical expressions for the energy and the form of such states are given, and a novel type of exactly solvable two-dimensional quantum models is therefore singled out. Moreover, we show that the field-induced quantum phase transition present in the models is unambiguously characterized by a cusp minimum in the pairwise-to-global entanglement ratio R, marking the quantum-critical enhancement of multipartite entanglement.     

Discrete negative refraction in photonic crystal waveguide arrays

We report a systematic analysis of anomalous refractive effects at interfaces between two photonic crystal waveguide arrays. Discrete negative refraction can be easily predicted from the sign of the coupling coefficient between adjacent waveguides, regardless of handedness of propagation.     

Bistable and self-tunable negative-index metamaterial at optical frequencies

We introduce a metamaterial design composed of square plasmonic loops loaded by Kerr nonlinearities that combines enhanced nonlinear response with strong artificial magnetism, ensuring a negative refractive index with bistable and self-tunable response. We verify with full-wave simulations that positive-to-negative switching of refractive index may be obtained with moderate loss. The design of a finite-size metamaterial prism is also presented, supporting at the same frequency, and for the same light intensity, positive or inverted Snell refraction as a function of its previous excitation history.     

Iron–cobalt nanocrystalline alloy supported on a cubic mesostructured silica matrix: FeCo/SBA-16 porous nanocomposites

A series of novel nanocomposites constituted of FeCo nanoparticles dispersed in an ordered cubic Im3m mesoporous silica matrix (SBA-16) have been successfully synthesized using the wet impregnation method. SBA-16, prepared using the non-ionic Pluronic 127 triblock copolymer as a structure-directing agent, is an excellent support for catalytic nanoparticles because of its peculiar three-dimensional cage-like structure, high surface area, thick walls, and high thermal stability. Low-angle X-ray diffraction, N₂ physisorption, and transmission electron microscopy analyses show that after metal loading, calcination at 500 °C, and reduction in H₂ flux at 800 °C, the nanocomposites retain the well-ordered structure of the matrix with cubic symmetry of pores. FeCo alloy nanoparticles with spherical shape and narrow size distribution (4–8 nm) are homogeneoulsy distributed throughout the matrix and they seem in a large extent to be allocated inside the pores.