Differential measurement of atmospheric refraction with a telescope with double fields of view

For the sake of complete theoretical research of atmospheric refraction, the atmospheric refraction under the condition of lower angles of elevation is still worthy to be analyzed and explored. In some engineering applications, the objects with larger zenith distance must be observed sometimes. Carrying out observational research of the atmospheric refraction at lower angles of elevation has an important significance. It has been considered difficult to measure the atmospheric refraction at lower angles of elevation. A new idea for determining atmospheric refraction by utilizing differential measurement with double fields of view is proposed. Taking the observational principle of HIPPARCOS satellite as a reference, a schematic prototype with double fields of view was developed. In August of 2013, experimental observations were carried out and the atmospheric refractions at lower angles of elevation can be obtained by the schematic prototype. The measured value of the atmospheric refraction at the zenith distance of 78.8 degree is $240.23"\pm0.27"$, and the feasibility of differential measurement of atmospheric refraction with double fields of view was justified. The limitations of the schematic prototype such as inadequate ability of gathering light, lack of accurate meteorological data recording and lower automatic level of observation and data processing were also pointed out, which need to be improved in subsequent work.Comment: 10 pages, 6 figure

Discriminative Block-Diagonal Representation Learning for Image Recognition

Existing block-diagonal representation studies mainly focuses on casting block-diagonal regularization on training data, while only little attention is dedicated to concurrently learning both block-diagonal representations of training and test data. In this paper, we propose a discriminative block-diagonal low-rank representation (BDLRR) method for recognition. In particular, the elaborate BDLRR is formulated as a joint optimization problem of shrinking the unfavorable representation from off-block-diagonal elements and strengthening the compact block-diagonal representation under the semisupervised framework of LRR. To this end, we first impose penalty constraints on the negative representation to eliminate the correlation between different classes such that the incoherence criterion of the extra-class representation is boosted. Moreover, a constructed subspace model is developed to enhance the self-expressive power of training samples and further build the representation bridge between the training and test samples, such that the coherence of the learned intraclass representation is consistently heightened. Finally, the resulting optimization problem is solved elegantly by employing an alternative optimization strategy, and a simple recognition algorithm on the learned representation is utilized for final prediction. Extensive experimental results demonstrate that the proposed method achieves superb recognition results on four face image data sets, three character data sets, and the 15 scene multicategories data set. It not only shows superior potential on image recognition but also outperforms the state-of-the-art methods

Stable nontrivial Z2 topology in ultrathin Bi (111) films: a first-principles study

Recently, there have been intense efforts in searching for new topological insulator (TI) materials. Based on first-principles calculations, we find that all the ultrathin Bi (111) films are characterized by a nontrivial Z2 number independent of the film thickness, without the odd-even oscillation of topological triviality as commonly perceived. The stable nontrivial Z2 topology is retained by the concurrent band gap inversions at multiple time-reversal-invariant k-points and associated with the intermediate inter-bilayer coupling of the multi-bilayer Bi film. Our calculations further indicate that the presence of metallic surface states in thick Bi(111) films can be effectively removed by surface adsorption.Comment: 5 pages, 3 figure

Local Operations in qubit arrays via global but periodic Manipulation

We provide a scheme for quantum computation in lattice systems via global but periodic manipulation, in which only effective periodic magnetic fields and global nearest neighbor interaction are required. All operations in our scheme are attainable in optical lattice or solid state systems. We also investigate universal quantum operations and quantum simulation in 2 dimensional lattice. We find global manipulations are superior in simulating some nontrivial many body Hamiltonians.Comment: 5 pages, 2 figures, to appear in Phys. Rev.