Photon-assisted electron transmission resonance through a quantum well with spin-orbit coupling

Using the effective-mass approximation and Floquet theory, we study the electron transmission over a quantum well in semiconductor heterostructures with Dresselhaus spin-orbit coupling and an applied oscillation field. It is demonstrated by the numerical evaluations that Dresselhaus spin-orbit coupling eliminates the spin degeneracy and leads to the splitting of asymmetric Fano-type resonance peaks in the conductivity. In turn, the splitting of Fano-type resonance induces the spin- polarization-dependent electron-current. The location and line shape of Fano-type resonance can be controlled by adjusting the oscillation frequency and the amplitude of external field as well. These interesting features may be a very useful basis for devising tunable spin filters.Comment: 10pages,4figure

Sequential Optimization for Efficient High-Quality Object Proposal Generation

We are motivated by the need for a generic object proposal generation algorithm which achieves good balance between object detection recall, proposal localization quality and computational efficiency. We propose a novel object proposal algorithm, BING++, which inherits the virtue of good computational efficiency of BING but significantly improves its proposal localization quality. At high level we formulate the problem of object proposal generation from a novel probabilistic perspective, based on which our BING++ manages to improve the localization quality by employing edges and segments to estimate object boundaries and update the proposals sequentially. We propose learning the parameters efficiently by searching for approximate solutions in a quantized parameter space for complexity reduction. We demonstrate the generalization of BING++ with the same fixed parameters across different object classes and datasets. Empirically our BING++ can run at half speed of BING on CPU, but significantly improve the localization quality by 18.5% and 16.7% on both VOC2007 and Microhsoft COCO datasets, respectively. Compared with other state-of-the-art approaches, BING++ can achieve comparable performance, but run significantly faster.Comment: Accepted by TPAM

Model Hamiltonian for Topological Insulators

In this paper we give the full microscopic derivation of the model Hamiltonian for the three dimensional topological insulators in the $Bi_2Se_3$ family of materials ($Bi_2Se_3$, $Bi_2Te_3$ and $Sb_2Te_3$). We first give a physical picture to understand the electronic structure by analyzing atomic orbitals and applying symmetry principles. Subsequently, we give the full microscopic derivation of the model Hamiltonian introduced by Zhang {\it et al} [\onlinecite{zhang2009}] based both on symmetry principles and the ${\bf k}\cdot{\bf p}$ perturbation theory. Two different types of $k^3$ terms, which break the in-plane full rotation symmetry down to three fold rotation symmetry, are taken into account. Effective Hamiltonian is derived for the topological surface states. Both the bulk and the surface models are investigated in the presence of an external magnetic field, and the associated Landau level structure is presented. For more quantitative fitting to the first principle calculations, we also present a new model Hamiltonian including eight energy bands.Comment: 18 pages, 9 figures, 5 table

Hierarchical Classification of Research Fields in the "Web of Science" Using Deep Learning

This paper presents a hierarchical classification system that automatically categorizes a scholarly publication using its abstract into a three-tier hierarchical label set (discipline, field, subfield) in a multi-class setting. This system enables a holistic categorization of research activities in the mentioned hierarchy in terms of knowledge production through articles and impact through citations, permitting those activities to fall into multiple categories. The classification system distinguishes 44 disciplines, 718 fields and 1,485 subfields among 160 million abstract snippets in Microsoft Academic Graph (version 2018-05-17). We used batch training in a modularized and distributed fashion to address and allow for interdisciplinary and interfield classifications in single-label and multi-label settings. In total, we have conducted 3,140 experiments in all considered models (Convolutional Neural Networks, Recurrent Neural Networks, Transformers). The classification accuracy is > 90% in 77.13% and 78.19% of the single-label and multi-label classifications, respectively. We examine the advantages of our classification by its ability to better align research texts and output with disciplines, to adequately classify them in an automated way, and to capture the degree of interdisciplinarity. The proposed system (a set of pre-trained models) can serve as a backbone to an interactive system for indexing scientific publications in the future.Comment: Under review in QS

Quantum Anomalous Hall Effect in Hg1−y_{1-y}Mny_{y}Te Quantum Wells

The quantum Hall effect is usually observed when the two-dimensional electron gas is subjected to an external magnetic field, so that their quantum states form Landau levels. In this work we predict that a new phenomenon, the quantum anomalous Hall effect, can be realized in Hg$_{1-y}$Mn$_{y}$Te quantum wells, without the external magnetic field and the associated Landau levels. This effect arises purely from the spin polarization of the $Mn$ atoms, and the quantized Hall conductance is predicted for a range of quantum well thickness and the concentration of the $Mn$ atoms. This effect enables dissipationless charge current in spintronics devices.Comment: 5 pages, 3 figures. For high resolution figures see final published version when availabl

ELUCID - Exploring the Local Universe with reConstructed Initial Density field III: Constrained Simulation in the SDSS Volume

A method we developed recently for the reconstruction of the initial density field in the nearby Universe is applied to the Sloan Digital Sky Survey Data Release 7. A high-resolution N-body constrained simulation (CS) of the reconstructed initial condition, with $3072^3$ particles evolved in a 500 Mpc/h box, is carried out and analyzed in terms of the statistical properties of the final density field and its relation with the distribution of SDSS galaxies. We find that the statistical properties of the cosmic web and the halo populations are accurately reproduced in the CS. The galaxy density field is strongly correlated with the CS density field, with a bias that depend on both galaxy luminosity and color. Our further investigations show that the CS provides robust quantities describing the environments within which the observed galaxies and galaxy systems reside. Cosmic variance is greatly reduced in the CS so that the statistical uncertainties can be controlled effectively even for samples of small volumes.Comment: submitted to ApJ, 19 pages, 22 figures. Please download the high-resolution version at http://staff.ustc.edu.cn/~whywang/paper

Electron interaction-driven insulating ground state in Bi2Se3 topological insulators in the two dimensional limit

We report a transport study of ultrathin Bi2Se3 topological insulators with thickness from one quintuple layer to six quintuple layers grown by molecular beam epitaxy. At low temperatures, the film resistance increases logarithmically with decreasing temperature, revealing an insulating ground state. The sharp increase of resistance with magnetic field, however, indicates the existence of weak antilocalization, which should reduce the resistance as temperature decreases. We show that these apparently contradictory behaviors can be understood by considering the electron interaction effect, which plays a crucial role in determining the electronic ground state of topological insulators in the two dimensional limit.Comment: 4 figure