Concurrence of superposition

The bounds on concurrence of the superposition state in terms of those of the states being superposed are studied in this paper. The bounds on concurrence are quite different from those on the entanglement measure based on von Neumann entropy (Phys. Rev. Lett. 97, 100502 (2006)). In particular, a nonzero lower bound can be provided if the states being superposed are properly constrained.Comment: 4 page

Impurity scattering and Friedel oscillations in mono-layer black phosphorus

We study the effect of impurity scattering effect in black phosphorurene (BP) in this work. For single impurity, we calculate impurity induced local density of states (LDOS) in momentum space numerically based on tight-binding Hamiltonian. In real space, we calculate LDOS and Friedel oscillation analytically. LDOS shows strong anisotropy in BP. Many impurities in BP are investigated using $T$-matrix approximation when the density is low. Midgap states appear in band gap with peaks in DOS. The peaks of midgap states are dependent on impurity potential. For finite positive potential, the impurity tends to bind negative charge carriers and vise versa. The infinite impurity potential problem is related to chiral symmetry in BP

Alfven seismic vibrations of crustal solid-state plasma in quaking paramagnetic neutron star

Magneto-solid-mechanical model of two-component, core-crust, paramagnetic neutron star responding to quake-induced perturbation by differentially rotational, torsional, oscillations of crustal electron-nuclear solid-state plasma about axis of magnetic field frozen in the immobile paramagnetic core is developed. Particular attention is given to the node-free torsional crust-against-core vibrations under combined action of Lorentz magnetic and Hooke's elastic forces; the damping is attributed to Newtonian force of shear viscose stresses in crustal solid-state plasma. The spectral formulae for the frequency and lifetime of this toroidal mode are derived in analytic form and discussed in the context of quasi-periodic oscillations of the X-ray outburst flux from quaking magnetars. The application of obtained theoretical spectra to modal analysis of available data on frequencies of oscillating outburst emission suggests that detected variability is the manifestation of crustal Alfven's seismic vibrations restored by Lorentz force of magnetic field stresses.Comment: 10 pages, 10 figure

Self-optimization of optical confinement in ultraviolet photonic crystal slab laser

We studied numerically and experimentally the effects of structural disorder on the performance of ultraviolet photonic crystal slab lasers. Optical gain selectively amplifies the high-quality modes of the passive system. For these modes, the in-plane and out-of-plane leakage rates may be automatically balanced in the presence of disorder. The spontaneous optimization of in-plane and out-of-plane confinement of light in a photonic crystal slab may lead to a reduction of the lasing threshold.Comment: 5 pages, 5 figure

State-independent experimental test of quantum contextuality in an indivisible system

We report the first state-independent experimental test of quantum contextuality on a single photonic qutrit (three-dimensional system), based on a recent theoretical proposal [Yu and Oh, Phys. Rev. Lett. 108, 030402 (2012)]. Our experiment spotlights quantum contextuality in its most basic form, in a way that is independent of either the state or the tensor product structure of the system

A unique distant submillimeter galaxy with an X-ray-obscured radio-luminous active galactic nucleus

We present a multiwavelength study of an atypical submillimeter galaxy in the GOODS-North field, with the aim to understand its physical properties of stellar and dust emission, as well as the central AGN activity. Although it is shown that the source is likely an extremely dusty galaxy at high redshift, its exact position of submillimeter emission is unknown. With the new NOEMA interferometric imaging, we confirm that the source is a unique dusty galaxy. It has no obvious counterpart in the optical and even NIR images observed with HST at lambda~<1.4um. Photometric-redshift analyses from both stellar and dust SED suggest it to likely be at z~>4, though a lower redshift at z~>3.1 cannot be fully ruled out (at 90% confidence interval). Explaining its unusual optical-to-NIR properties requires an old stellar population (~0.67 Gyr), coexisting with a very dusty ongoing starburst component. The latter is contributing to the FIR emission, with its rest-frame UV and optical light being largely obscured along our line of sight. If the observed fluxes at the rest-frame optical/NIR wavelengths were mainly contributed by old stars, a total stellar mass of ~3.5x10^11Msun would be obtained. An X-ray spectral analysis suggests that this galaxy harbors a heavily obscured AGN with N_H=3.3x10^23 cm^-2 and an intrinsic 2-10 keV luminosity of L_X~2.6x10^44 erg/s, which places this object among distant type 2 quasars. The radio emission of the source is extremely bright, which is an order of magnitude higher than the star-formation-powered emission, making it one of the most distant radio-luminous dusty galaxies. The combined characteristics of the galaxy suggest that the source appears to have been caught in a rare but critical transition stage in the evolution of submillimeter galaxies, where we are witnessing the birth of a young AGN and possibly the earliest stage of its jet formation and feedback.Comment: 13 pages in printer format, 10 figures, 1 table, accepted for publication in the A&

Survivability model for security and dependability analysis of a vulnerable critical system

This paper aims to analyze transient security and dependability of a vulnerable critical system, under vulnerability-related attack and two reactive defense strategies, from a severe vulnerability announcement until the vulnerability is fully removed from the system. By severe, we mean that the vulnerability-based malware could cause significant damage to the infected system in terms of security and dependability while infecting more and more new vulnerable computer systems. We propose a Markov chain-based survivability model for capturing the vulnerable critical system behaviors during the vulnerability elimination process. A high-level formalism based on Stochastic Reward Nets is applied to automatically generate and solve the survivability model. Survivability metrics are defined to quantify system attributes. The proposed model and metrics not only enable us to quantitatively assess the system survivability in terms of security risk and dependability, but also provide insights on the system investment decision. Numerical experiments are constructed to study the impact of key parameters on system security, dependability and profit

A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition.

Recent years have witnessed the success of deep learning methods in human activity recognition (HAR). The longstanding shortage of labeled activity data inherently calls for a plethora of semisupervised learning methods, and one of the most challenging and common issues with semisupervised learning is the imbalanced distribution of labeled data over classes. Although the problem has long existed in broad real-world HAR applications, it is rarely explored in the literature. In this paper, we propose a semisupervised deep model for imbalanced activity recognition from multimodal wearable sensory data. We aim to address not only the challenges of multimodal sensor data (e.g., interperson variability and interclass similarity) but also the limited labeled data and class-imbalance issues simultaneously. In particular, we propose a pattern-balanced semisupervised framework to extract and preserve diverse latent patterns of activities. Furthermore, we exploit the independence of multi-modalities of sensory data and attentively identify salient regions that are indicative of human activities from inputs by our recurrent convolutional attention networks. Our experimental results demonstrate that the proposed model achieves a competitive performance compared to a multitude of state-of-the-art methods, both semisupervised and supervised ones, with 10% labeled training data. The results also show the robustness of our method over imbalanced, small training data sets