Спектры поглощения пробного сигнала и резонансной флуоресценции для излучателей при их взаимодействии с локальным окружением в прозрачных средах

The current paper demonstrates theoretical analysis of two types of spectral curves for several configurations of system of two-level light emitters, considering the influence of local field and close environment inside a transparent medium. Probe field absorption spectra and resonant fluorescence spectra are calculated under excitation of a strong monochromatic cw laser. The sensitivity of absorption and emission optical spectroscopy method is compared for revealing the effects of the medium on individual emitters and their ensembles. Spectral curves were calculated for model emitters considering local field influence of a transparent dielectric medium and local electron-phonon interactions, which determined the response of the emitters to an external laser field and effective relaxation mechanisms. The calculation formalism is based on a semiclassical approach, while the relaxation processes associated with the phonon contribution are introduced phenomenologically with references to other studies.

PECULIAR PROPERTIES OF ELECTROMAGNETIC RADIATION PROPAGATION IN PHOTONIC CRYSTALLINE METAL-DIELECTRIC SYSTEMS BASED ON OPALS

The article studies the propagation of electromagnetic waves in metal-dielectric systems based on opals. We revealed anomalous transmission and absorption of light by hybrid plasmon- photonic layered heterostructures associated with the excitation of surface plasmon polaritons propagating along the metal-dielectric interface. The position of maxima in the reflection spectra of nanocomposites, obtained by filling the opal matrix with metal by the electrothermodiffusion method, is explained by the Bragg diffraction, and the asymmetric form of the spectral curves is attributed to the Fano resonance.

Interpretation of the Reflectance Spectra of Lithium (Li) Minerals and Pegmatites: A Case Study for Mineralogical and Lithological Identification in the Fregeneda-Almendra Area

Reflectance spectroscopy has been used to identify several deposit types. However, applications concerning lithium (Li)-pegmatites are still scarce. Reflectance spectroscopic studies complemented by microscopic and geochemical studies were employed in the Fregeneda–Almendra (Spain–Portugal) pegmatite field to analyze the spectral behavior of Li-minerals and field lithologies. The spectral similarity of the target class (Li-pegmatites) with other elements was also evaluated. Lepidolite was discriminated from other white micas and the remaining Li-minerals. No diagnostic feature of petalite and spodumene was identified, since their spectral curves are dominated by clays. Their presence was corroborated (by complementary techniques) in petalite relics and completely replaced crystals, although the clay-related absorption depths decrease with Li content. This implies that clays can be used as pathfinders only in areas where argillic alteration is not prevalent. All sampled lithologies present similar water and/or hydroxide features. The overall mineral assemblage is very distinct, with lepidolite, cookeite, and orthoclase exclusively identified in Li-pegmatite (being these minerals crucial targets for Li-pegmatite discrimination in real-life applications), while chlorite and biotite can occur in the remaining lithologies. Satellite data can be used to discriminate Li-pegmatites due to distinct reflectance magnitude and mineral assemblages, higher absorptions depths, and distinct Al–OH wavelength position. The potential use of multi- and hyperspectral data was evaluated; the main limitations and advantages were discussed. These new insights on the spectral behavior of Li-minerals and pegmatites may aid in new Li-pegmatite discoveries around the world.

A support theorem for\break the Hitchin fibration: The case of GL n and K C

We compute the supports of the perverse cohomology sheaves of the Hitchin fibration for GL n {\mathrm{GL}_{n}} over the locus of reduced spectral curves. In contrast to the case of meromorphic Higgs fields we find additional supports at the loci of reducible spectral curves. Their contribution to the global cohomology is governed by a finite twist of Hitchin fibrations for Levi subgroups. The corresponding summands give non-trivial contributions to the cohomology of the moduli spaces for every n ≥ 2 {n\geq{2}} . A key ingredient is a restriction result for intersection cohomology sheaves that allows us to compare the fibration to the one defined over versal deformations of spectral curves.

Compressed Sensing Technology for Spectral Reconstruction Based on Maximum Entropy Criterion

In order to choose the related sampling ratio in the information-poor and information-rich spectral fragments, this paper attempts to recover the spectral reflectance by compressed sensing technology based on maximum entropy criterion. The maximum entropy threshold method is the criterion that the optimal threshold is determined to segment the information content of spectral curves. The spectral reflectance in each sub-spectral fragment is reconstructed by compressed sensing. The wavelet orthogonal matrix performs a sparse representation of each segmented spectral curve. Undersampling spectral curve be collected by random gaussian measurement matrix. The orthogonal matching pursuit algorithm recovers sparse original signals from undersampling observed signals. In this paper, the four standard color blocks of Munsell and the spectral curves of five types of ground objects in the hyperspectral data set are used as the exper-imental objects. The reconstructed results are evaluated by spectral curve reconstruction, root mean square error and information entropy difference. The experimental results show that our approach improves the reconstruction accuracy of spectral reflectance effectively, compared with the traditional method.

Spectral Curves for the Derivative Nonlinear Schrödinger Equations

Currently, in nonlinear optics, models associated with various types of the nonlinear Schrödinger equation (scalar (NLS), vector (VNLS), derivative (DNLS)), as well as with higher and mixed equations from the corresponding hierarchies are usually studied. Typical tools for solving the problem of propagation of optical nonlinear waves are the forward and inverse nonlinear Fourier transforms. One of the methods for reconstructing a periodic nonlinear signal is based on the use of spectral data in the form of spectral curves. In this paper, we study the properties of the spectral curves for all the derivatives NLS equations simultaneously. For all the main DNLS equations (DNLSI, DNLSII, DNLSIII), we have obtained unified Lax pairs, unified hierarchies of evolutionary and stationary equations, as well as unified equations of spectral curves of multiphase solutions. It is shown that stationary and evolutionary equations have symmetries, the presence of which leads to the existence of holomorphic involutions on spectral curves. Because of this symmetry, spectral curves of genus g are covers over other curves of genus M and N=g−M, where M is a number of phase of solutions. We also showed that the number of the genus g of the spectral curve is related to the number of phases M of the solution of one of the two formulas: g=2M or g=2M+1. The third section provides examples of the simplest solutions.

Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging

The identification of hazardous chemicals based on hyperspectral imaging is an important emergent means for the prevention of explosion accidents and the early warning of secondary hazards. In this study, we used a combination of spectral curve matching based on full-waveform characteristics and spectral matching based on spectral characteristics to identify the hazardous chemicals, and proposed a method to quantitatively characterize the matching degree of the spectral curves of hazardous chemicals. The results showed that the four hazardous chemicals, sulfur, red phosphorus, potassium permanganate, and corn starch had bright colors, distinct spectral curve characteristics, and obvious changes in reflectivity, which were easy to identify. Moreover, the matching degree of their spectral curves was positively correlated with their reflectivity. However, the spectral characteristics of carbon powder, strontium nitrate, wheat starch, and magnesium–aluminum alloy powder were not obvious, with no obvious characteristic peaks or trends of change in reflectivity. Except for the reflectivity and the matching degree of the carbon powder being maintained at a low level, the reflectivity of the remaining three samples was relatively close, so that it was difficult to identify with the spectral curves alone, and color information should be considered for further identification.

Strategies for the Development of Spectral Models for Soil Organic Matter Estimation

Visible (V), Near Infrared (NIR) and Short Waves Infrared (SWIR) spectroscopy has been indicated as a promising tool in soil studies, especially in the last decade. However, in order to apply this method, it is necessary to develop prediction models with the capacity to capture the intrinsic differences between agricultural areas and incorporate them in the modeling process. High quality estimates are generally obtained when these models are applied to soil samples displaying characteristics similar to the samples used in their construction. However, low quality predictions are noted when applied to samples from new areas presenting different characteristics. One way to solve this problem is by recalibrating the models using selected samples from the area of interest. Based on this premise, the aim of this study was to use the spiking technique and spiking associated with hybridization to expand prediction models and estimate organic matter content in a target area undergoing different uses and management. A total of 425 soil samples were used for the generation of the state model, as well as 200 samples from a target area to select the subsets (10 samples) used for model recalibration. The spectral readings of the samples were obtained in the laboratory using the ASD FieldSpec 3 Jr. Sensor from 350 to 2500 nm. The spectral curves of the samples were then associated to the soil attributes by means of a partial least squares regression (PLSR). The state model obtained better results when recalibrated with samples selected through a cluster analysis. The use of hybrid spectral curves did not generate significant improvements, presenting estimates, in most cases, lower than the state model applied without recalibration. The use of the isolated spiking technique was more effective in comparison with the spiked and hybridized state models, reaching r2, square root of mean prediction error (RMSEP) and ratio of performance to deviation (RPD) values of 0.43, 4.4 g dm−3, and 1.36, respectively.