Generation of entangled coherent states via cross-phase-modulation in a double electromagnetically induced transparency regime

The generation of an entangled coherent state is one of the most important ingredients of quantum information processing using coherent states. Recently, numerous schemes to achieve this task have been proposed. In order to generate travelling-wave entangled coherent states, cross-phase-modulation, optimized by optical Kerr effect enhancement in a dense medium in an electromagnetically induced transparency (EIT) regime, seems to be very promising. In this scenario, we propose a fully quantized model of a double-EIT scheme recently proposed [D. Petrosyan and G. Kurizki, Phys. Rev. A 65, 33 833 (2002)]: the quantization step is performed adopting a fully Hamiltonian approach. This allows us to write effective equations of motion for two interacting quantum fields of light that show how the dynamics of one field depends on the photon-number operator of the other. The preparation of a Schrodinger cat state, which is a superposition of two distinct coherent states, is briefly exposed. This is based on nonlinear interaction via double EIT of two light fields (initially prepared in coherent states) and on a detection step performed using a 50:50 beam splitter and two photodetectors. In order to show the entanglement of an entangled coherent state, we suggest to measure the joint quadrature variance of the field. We show that the entangled coherent states satisfy the sufficient condition for entanglement based on quadrature variance measurement. We also show how robust our scheme is against a low detection efficiency of homodyne detectors.

Subwavelength resolution for horizontal and vertical polarization by coupled arrays of oblate nanoellipsoids

A structure comprising a coupled pair of two-dimensional arrays of oblate plasmonic nanoellipsoids in a dielectric host medium is proposed as a superlens in the optical domain for both horizontal and vertical polarizations. By means of simulations it is demonstrated that a structure formed by silver nanoellipsoids is capable of restoring subwavelength features of the object for both polarizations at distances larger than half wavelength. The bandwidth of subwavelength resolution is in all cases very large (above 13%). (C) 2009 Optical Society of America

Atomic oxygen formation in a radio-frequency driven micro-atmospheric pressure plasma jet

Atomic oxygen formation in a radio-frequency driven micro-atmospheric pressure plasma jet is investigated using both advanced optical diagnostics and numerical simulations of the dynamic plasma chemistry. Laser spectroscopic measurements of absolute densities of ground state atomic oxygen reveal steep gradients at the interface between the plasma core and the effluent region. Spatial profiles resolving the interelectrode gap within the core plasma indicate that volume processes dominate over surface reactions. Details of the production and destruction processes are investigated in numerical simulations benchmarked by phase-resolved optical emission spectroscopy. The main production mechanisms are electron induced and hence most efficient in the vicinity of the plasma boundary sheath, where electrons are energized. The destruction is driven through chemical heavy particle reactions. The resulting spatial profile of atomic oxygen is relatively flat. The power dependence of the atomic oxygen density obtained by the numerical simulation is in very good agreement with the laser spectroscopic measurements.

Spitzer measurements of atomic and molecular abundances in the Type IIPSN 2005af

We present results based on mid-infrared (3.6-30 mm) observations with the Spitzer Space Telescope of the nearby Type IIP supernova 2005af. We report the first ever detection of the SiO molecule in a Type IIP supernova. Together with the detection of the CO fundamental, this is an exciting finding as it may signal the onset of dust condensation in the ejecta. From a wealth of fine-structure lines we provide abundance estimates for stable Ni, Ar, and Ne that, via spectral synthesis, may be used to constrain nucleosynthesis models.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.