Plasmonic nanostructures with local temporal response: a platform for time-varying photonics

This work is devoted to the development of an approach for implementation and designing time-varying media. A mechanism based on the use of plasmonic nanostructures with a reduced plasmon lifetime is proposed. It is shown that such nanostructures can be used to enhance the strength and speed of modulation of the refractive index ofnonlinear media. This is achieved through decreasing of the spectral dispersion of the real permittivity. Plasmonic materials with peculiar optical properties, such as flatdispersion in the near-infrared range, were synthesized. For this purpose, we prepared TiON thin films and performed thermal post-treatment for fine-tuning permittivity of TiON. It has been shown that the proposed materials allow one to achieve an ultrashort plasmon lifetime on the order of 0.1 fs, which is an order of magnitude shorter than in the case of traditional plasmonic materials

Fractional derivative for finding width, amplitude and shape of overlapping peaks

This work describes a technique based on fractional derivative for finding the overlapping peaks spectral parameters. This is due to positive effects of the fractional derivative caused by the behavior of its zero-crossing and maximal amplitude. A power of the method is demonstrated for synthetic data by using the well-known distributions such as Lorentzian, Gaussian ones and for experimental infra-red spectra coming from molecular spectroscopy. It is shown that recorded spectra are approximated with the Tsallis distribution in the best way, compared to the distributions above mentioned

Self-similar fluctuations in a turbulent plasma

In the paper one of possible reasons for explanation of strange transport in the turbulent plasma in the presence of a fluctuating magnetic field is discussed. A model of self-similar fluctuations in the magnetic field is investigated in terms of the microscopic theory based on a kinetic diffusion equation for plasmas. A problem of non-Markovian evolution for fluctuations in a magnetic field is discussed and the appearance of anomalous transport is illustrated. It is shown this particular class is of special interest for the description of subdiffusive process

A simple method to extract spectral parameters using fractional derivative spectrometry

The nonlinear fitting method, based on the ordinary least squares approach, is one of several methods that have been applied to fit experimental data into well-known profiles and to estimate their spectral parameters. Besides linearization measurement errors, the main drawback of this approach is the high variance of the spectral parameters to be estimated. This is due to the overlapping of individual components, which leads to ambiguous fitting. In this paper, we propose a simple mathematical tool in terms of a fractional derivative (FD) to determine the overlapping band spectral parameters. This is possible because of several positive effects of FD connected with the behavior of its zero-crossing and maximal amplitude. For acquiring a stable and unbiased FD estimate, we utilize the statistical regularization method and the regularized iterative algorithm when a priori constraints on a sought derivative are available. Along with the well-known distributions such as Lorentzian, Gaussian and their linear combinations, the Tsallis distribution is used as a model to correctly assign overlapping bands. To demonstrate the power of the method, we estimate unresolved band spectral parameters of synthetic and experimental infra-red spectra. © 2003 Elsevier B.V. All rights reserved

Spectral line shape identification by using fractional derivative spectrometry

Before it is difficult to say about a peak shape without conducting additional research. Conventional nonlinear fitting methods based on the OLS approach are unsuitable to unambiguously assign the overlapped peaks. This implies that a composite band can be decomposed into elementary components of a given shape with the same integral reconstruction error with a large number of ways. A main drawback of this approach is the high variance of the spectral parameters to be estimated. This is due to the overlapping of individual components, which leads to the ambiguous fitting. In this paper we develop a simple mathematical tool in terms of fractional derivative (FD) to determine the overlapping peaks spectral parameters. It is possible due to several positive effects of FD connected with the behavior of its zero-crossing and maximal amplitude. For acquiring a stable and unbiased FD estimate we utilize the statistical regularization method. Along with the well-known distributions such as Lorentzian, Gaussian and their linear combinations the Tsallis distribution is used as a model to correctly resolve overlapped peaks. As exhaustive examples demonstrating a power of the method we estimate unresolved bands spectral parameters of synthetic and experimental infra-red spectra

Electrochemical design of plasmonic nanoantennas for tip-enhanced optical spectroscopy and imaging performance

Optical nanoantennas play a crucial role in controlling near-fields on the nanoscale and being counterparts of commonly used conventional optical components such as lens, prisms, gratings, etc. for shaping the wavefront of light in the far-field. In this paper we highlight a dc-pulsed voltage electrochemical etching method with a self-tuneable duty cycle for highly reproducible design of plasmonic (metallic) nanoantennas. With the method, we introduce such concepts as design, optimization and figure-ofmerit for evaluating fabrication efficiency. The ability of the nanoantennas to enhance and localize the optical fields beyond the diffraction limit is statistically studied with Rayleigh scattering from the tip apex and tipenhanced Raman spectroscopy of a single walled carbon nanotubes bundle

Strong focusing higher-order laser modes: Transverse and longitudinal optical fields

© Published under licence by IOP Publishing Ltd. The distribution of transverse and longitudinal optical fields in tightly focused higher-order laser beams is investigated. Polarization-dependent fingerprints of transverse and longitudinal optical fields are experimentally captured by means of photoinduced surface deformations in azobenzene polymer thin films

Seismic pattern recognition by Wavelet based-higher order statistics

In this work we develop an approach for detecting nonlinearity in chaotic dynamical systems using the higher order statistics and wavelet analysis. A special attention is paid to the consideration of three-wave interaction in a quadratically coupled medium. The knowledge of nonlinearities allows one to extract order parameters both for reconstruction of a dynamical system and for the study of transient processes between oscillatory regimes. To demonstrate a power of this approach we verify the latter for real data coming from the seismology. © 2005 American Institute of Physics

Solving inverse problems in applied spectroscopy with random fractal noise

In the framework of the statistical regularization method new algorithms of solving inverse problems in applied spectroscopy in the presence of correlated fractal noises are suggested. Statistical properties of fractal noises are investigated in terms of R/S-analysis. As an example illustrating the efficiency of the algorithms suggested the smoothing problem of experimental data is considered. (C) 2000 Elsevier Science Ltd. All rights reserved. | In the framework of the statistical regularization method new algorithms of solving inverse problems in applied spectroscopy in the presence of correlated fractal noises are suggested. Statistical properties of fractal noises are investigated in terms of R/S-analysis. As an example illustrating the efficiency of the algorithms suggested the smoothing problem of experimental data is considered