Efficient kk-separability criteria for mixed multipartite quantum states

We investigate classification and detection of entanglement of multipartite quantum states in a very general setting, and obtain efficient $k$-separability criteria for mixed multipartite states in arbitrary dimensional quantum systems. These criteria can be used to distinguish $n-1$ different classes of multipartite inseparable states and can detect many important multipartite entangled states such as GHZ states, W states, anti W states, and mixtures thereof. They detect $k$-nonseparable $n$-partite quantum states which have previously not been identified. Here $k=2,3,\cdots,n$. No optimization or eigenvalue evaluation is needed, and our criteria can be evaluated by simple computations involving components of the density matrix. Most importantly, they can be implemented in today's experiments by using at most $\mathcal{O}(n^2)$ local measurements.Comment: 6 pages, 4 figure

Long-range dynamics of magnetic impurities coupled to a two-dimensional Heisenberg antiferromagnet

We consider a two-dimensional Heisenberg antiferromagnet on a square lattice with weakly coupled impurities, i.e. additional spins interacting with the host magnet by a small dimensionless coupling constant g<<1. Using linear spin-wave theory, we find that the magnetization disturbance at distance r from a single impurity behaves as g/r for 1>1/g. Surprisingly the disturbance is inversely proportional to the coupling constant! The interaction between two impurities separated by a distance r is proportional to g^2/r for 1>1/g. Hence at large distances, the interaction is universal and independent of the coupling constant. We also find that the frequency of Rabi oscillations between two impurities is proportional to g^2 ln(gr) at 1<<r<<1/g, logarithmically enhanced compared to the spin-wave width. This leads to a new mechanism for NMR, NQR and EPR line broadening. All these astonishing results are due to the gapless spectrum of the magnetic excitations in the quantum antiferromagnet.Comment: 6 pages, 5 figure

EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG) is widely used in eye state classification to detect human&apos;s cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL) based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches

The mechanism of hole carrier generation and the nature of pseudogap- and 60K-phases in YBCO

In the framework of the model assuming the formation of NUC on the pairs of Cu ions in CuO$_{2}$ plane the mechanism of hole carrier generation is considered and the interpretation of pseudogap and 60 K-phases in $YBa_{2}Cu_{3}O_{6+\delta}$. is offered. The calculated dependences of hole concentration in $YBa_{2}Cu_{3}O_{6+\delta}$ on doping $\delta$ and temperature are found to be in a perfect quantitative agreement with experimental data. As follows from the model the pseudogap has superconducting nature and arises at temperature $T^{*}>T_{c\infty}>T_{c}$ in small clusters uniting a number of NUC's due to large fluctuations of NUC occupation. Here $T_{c\infty}$ and $T_{c}$ are the superconducting transition temperatures of infinite and finite clusters of NUC's, correspondingly. The calculated $T^{*}(\delta)$ and $T_{n}(\delta)$ dependences are in accordance with experiment. The area between $T^{*}(\delta)$ and $T_{n}(\delta)$ corresponds to the area of fluctuations where small clusters fluctuate between superconducting and normal states owing to fluctuations of NUC occupation. The results may serve as important arguments in favor of the proposed model of HTSC.Comment: 12 pages, 7 figure

Long Range Dynamics Related to Magnetic Impurity in the 2D Heisenberg Antiferromagnet

We consider a magnetic impurity in the two-dimensional Heisenberg antifferomagnet with long range antiferromagnetic order. At low temperature the impurity magnetic susceptibility has a Curie term ($\propto 1/T$) and a logarithmic correction ($\propto \ln(T)$). We calculate the correction and derive related Ward identity for the impurity-spin-wave vertex.Comment: 5 pages, 6 figure

Energy funneling in a bent chain of Morse oscillators with long-range coupling

A bent chain of coupled Morse oscillators with long-range dispersive interaction is considered. Moving localized excitations may be trapped in the bending region. Thus chain geometry acts like an impurity. An energy funneling effect is observed in the case of random initial conditions.Comment: 6 pages, 12 figures. Submitted to Physical Review E, Oct. 13, 200

Quantum trajectories for Brownian motion

We present the stochastic Schroedinger equation for the dynamics of a quantum particle coupled to a high temperature environment and apply it the dynamics of a driven, damped, nonlinear quantum oscillator. Apart from an initial slip on the environmental memory time scale, in the mean, our result recovers the solution of the known non-Lindblad quantum Brownian motion master equation. A remarkable feature of our approach is its localization property: individual quantum trajectories remain localized wave packets for all times, even for the classically chaotic system considered here, the localization being stronger the smaller $\hbar$.Comment: 4 pages, 3 eps figure

Statistical Inference in a Directed Network Model with Covariates

Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each other. In this paper, we propose a new directed network model to capture the former via node-specific parametrization and the latter by incorporating covariates. In particular, this model quantifies the extent of heterogeneity in terms of outgoingness and incomingness of each node by different parameters, thus allowing the number of heterogeneity parameters to be twice the number of nodes. We study the maximum likelihood estimation of the model and establish the uniform consistency and asymptotic normality of the resulting estimators. Numerical studies demonstrate our theoretical findings and a data analysis confirms the usefulness of our model.Comment: 29 pages. minor revisio

Design and realization of a smart battery management system

Battery management system (BMS) emerges a decisive system component in battery-powered applications, such as (hybrid) electric vehicles and portable devices. However, due to the inaccurate parameter estimation of aged battery cells and multi-cell batteries, current BMSs cannot control batteries optimally, and therefore affect the usability of products. In this paper, we proposed a smart management system for multi-cell batteries, and discussed the development of our research study in three directions: i) improving the effectiveness of battery monitoring and current sensing, ii) modeling the battery aging process, and iii) designing a self-healing circuit system to compensate performance variations due to aging and other variations.published_or_final_versio