Does the Borexino experiment have enough resolution to detect the neutrino flavor day-night asymmetry?

The Earth's density distribution can be approximately considered piecewise continuous at the scale of two-flavor oscillations of neutrinos with energies about 1 MeV. This quite general assumption appears to be enough to analytically calculate the day-night asymmetry factor. Using the explicit time averaging procedure, we show that, within the leading-order approximation, this factor is determined by the electron density immediately before the detector, i.e. in the Earth's crust. Within the approximation chosen, the resulting asymmetry factor does not depend either on the properties of the inner Earth's layers or on the substance and the dimensions of the detector. For beryllium neutrinos, we arrive at the asymmetry factor estimation of about $-4 \times 10^{-4}$, which is at least one order of magnitude beyond the present experimental resolution, including that of the Borexino experiment.Comment: 16 pages, 3 figures; Talk given at the 17th International Seminar on High Energy Physics "QUARKS'2012" (Yaroslavl, Russia, June 4-10, 2012); to appear in the Proceedings volum

Control of light polarization by voltage in excitonic metasurface devices

We propose active metasurface devices where the state of emitted light is controlled by voltage. Based on the simulations of expected emission spectra, we present the concept of a light emitting device with voltage controlled wavelength and degree of linear polarization of emission. The device combines the ability of metasurfaces to control light with a wavelength-tunable light source based on indirect excitons in coupled quantum well heterostructures

Resonant-state expansion of light propagation in nonuniform waveguides

A rigorous approach for precise and efficient calculation of light propagation along nonuniform waveguides is presented. Resonant states of a uniform waveguide, which satisfy outgoing-wave boundary conditions, form a natural basis for expansion of the local electromagnetic field. Using such an expansion at fixed frequency, we convert the wave equation for light propagation in a nonuniform waveguide into an ordinary second-order matrix differential equation for the expansion coefficients depending on the coordinate along the waveguide. We illustrate the method on several examples of nonuniform planar waveguides and evaluate its efficiency compared to the aperiodic Fourier modal method and the finite element method, showing improvements of one to four orders of magnitude. A similar improvement can be expected also for applications in other fields of physics showing wave phenomena, such as acoustics and quantum mechanics

Efficient quantitative hyperspectral image unmixing method for large-scale Raman micro-spectroscopy data analysis

Vibrational micro-spectroscopy is a powerful optical tool, providing a non-invasive label-free chemically specific imaging for many chemical and biomedical applications. However, hyperspectral image produced by Raman micro-spectroscopy typically consists of thousands discrete pixel points, each having individual Raman spectrum at thousand wavenumbers, and therefore requires appropriate image unmixing computational methods to retrieve non-negative spatial concentration and corresponding non-negative spectra of the image biochemical constituents. Here, we present a new efficient Quantitative Hyperspectral Image Unmixing (Q-HIU) method for large-scale Raman micro-spectroscopy data analysis. This method enables to simultaneously analyse multi-set Raman hyperspectral images in three steps: (i) Singular Value Decomposition with innovative Automatic Divisive Correlation which autonomously filters spatially and spectrally uncorrelated noise from data; (ii) a robust subtraction of fluorescent background from the data using a newly developed algorithm called Bottom Gaussian Fitting; (iii) an efficient Quantitative Unsupervised/Partially Supervised Non-negative Matrix Factorization method, which rigorously retrieves non-negative spatial concentration maps and spectral profiles of the samples' biochemical constituents with no a priori information or when one or several samples’ constituents are known. As compared with state-of-the-art methods, our approach allows to achieve significantly more accurate results and efficient quantification with several orders of magnitude shorter computational time as verified on both artificial and real experimental data. We apply Q-HIU to the analysis of large-scale Raman hyperspectral images of human atherosclerotic aortic tissues and our results show a proof-of-principle for the proposed method to retrieve and quantify the biochemical composition of the tissues, consisting of both high and low concentrated compounds. Along with the established hallmarks of atherosclerosis including cholesterol/cholesterol ester, triglyceride and calcium hydroxyapatite crystals, our Q-HIU allowed to identify the significant accumulations of oxidatively modified lipids co-localizing with the atherosclerotic plaque lesions in the aortic tissues, possibly reflecting the persistent presence of inflammation and oxidative damage in these regions, which are in turn able to promote the disease pathology. For minor chemical components in the diseased tissues, our Q-HIU was able to detect the signatures of calcium hydroxyapatite and β-carotene with relative mean Raman concentrations as low as 0.09% and 0.04% from the original Raman intensity matrix with noise and fluorescent background contributions of 3% and 94%, respectively