Decay and storage of multiparticle entangled states of atoms in collective thermostat

We derive a master equation describing the collective decay of two-level atoms inside a single mode cavity in the dispersive limit. By considering atomic decay in the collective thermostat, we found a decoherence-free subspace of the multiparticle entangled states of the W-like class. We present a scheme for writing and storing these states in collective thermostat

On Multiparticle Entanglement via Resonant Interaction between Light and atomic Ensembles

Multiparticle entangled states generated via interaction between narrow-band light and an ensemble of identical two-level atoms are considered. Depending on the initial photon statistics, correlation between atoms and photons can give rise to entangled states of these systems. It is found that the state of any pair of atoms interacting with weak single-mode squeezed light is inseparable and robust against decay. Optical schemes for preparing entangled states of atomic ensembles by projective measurement are described.Comment: 11 pages, 1 figure, revtex

Adaptive neuro-fuzzy classifier for evaluating the technology effectiveness based on the modified Wang and Mendel fuzzy neural production MIMO-network

The paper describes practical results gained during synthesis of the classification model for estimating technology effectiveness when solving multi-criteria problems of expert data analysis (Foresight) aimed to identify technological breakthroughs and strategic perspectives of scientific, technological and innovative developmen

Adaptive fuzzy neural production network with MIMO-structure for the evaluation of technology efficiency

The paper presents an example of modeling the algorithm operation. The paper analyses the modified Wang and Mendel MIMO-architecture of the adaptive fuzzy neural production network with a logical conclusion. It is distinguished by the automatic generation of a set of fuzzy rules based on a fuzzy decision tree and a hybrid algorithm for parameter adaptation by the neural network (centers, widths of membership functions, and conclusions) starting from the leaf nodes to the root nodes of the tree