arXiv subjects

Hui Zhang

Publications and source records attributed to Hui Zhang.

At least 415 records · Page 23Linked to original sources

arXiv2020

Observation of two-dimensional superconductivity at the LaAlO3/KTaO3(110) heterointerface

We report on the observation of a Tc ~0.9 K superconductivity at the interface between LaAlO3 film and the 5d transition-metal oxide KTaO3(110) single crystal. The interface shows a large anisotropy of the upper critical field, and its superconducting transition is consistent with a Berezinskii-Kosterlitz-Thouless transition. Both facts suggest that the superconductivity is two-dimensional (2D) in nature. The carrier density measured at 5 K is ~7 time 10^13 cm-2. The superconducting layer thickness and coherence length are estimated to be ~8 and ~30 nm, respectively. Our result provides a new platform for the study of 2D superconductivity at oxide interfaces.

cond-mat.supr-con↗

arXiv2020

UNetGAN: A Robust Speech Enhancement Approach in Time Domain for Extremely Low Signal-to-noise Ratio Condition

Speech enhancement at extremely low signal-to-noise ratio (SNR) condition is a very challenging problem and rarely investigated in previous works. This paper proposes a robust speech enhancement approach (UNetGAN) based on U-Net and generative adversarial learning to deal with this problem. This approach consists of a generator network and a discriminator network, which operate directly in the time domain. The generator network adopts a U-Net like structure and employs dilated convolution in the bottleneck of it. We evaluate the performance of the UNetGAN at low SNR conditions (up to -20dB) on the public benchmark. The result demonstrates that it significantly improves the speech quality and substantially outperforms the representative deep learning models, including SEGAN, cGAN fo SE, Bidirectional LSTM using phase-sensitive spectrum approximation cost function (PSA-BLSTM) and Wave-U-Net regarding Short-Time Objective Intelligibility (STOI) and Perceptual evaluation of speech quality (PESQ).

eess.AS↗

arXiv2020

Numerical Approximations and Error Analysis of the Cahn-Hilliard Equation with Dynamic Boundary Conditions

We consider the numerical approximations of the Cahn-Hilliard equation with dynamic boundary conditions (C. Liu et. al., Arch. Rational Mech. Anal., 2019). We propose a first-order in time, linear and energy stable numerical scheme, which is based on the stabilized linearly implicit approach. The energy stability of the scheme is proved and the semi-discrete-in-time error estimates are carried out. Numerical experiments, including the comparison with the former work, the accuracy tests with respect to the time step size and the shape deformation of a droplet, are performed to validate the accuracy and the stability of the proposed scheme.

math.NA↗

arXiv2020

TOI-481 b & TOI-892 b: Two long period hot Jupiters from the Transiting Exoplanet Survey Satellite

We present the discovery of two new 10-day period giant planets from the Transiting Exoplanet Survey Satellite ($TESS$) mission, whose masses were precisely determined using a wide diversity of ground-based facilities. TOI-481 b and TOI-892 b have similar radii ($0.99\pm0.01$ $\rm R_{J}$ and $1.07\pm0.02$ $\rm R_{J}$, respectively), and orbital periods (10.3311 days and 10.6266 days, respectively), but significantly different masses ($1.53\pm0.03$ $\rm M_{J}$ versus $0.95\pm0.07$ $\rm M_{J}$, respectively). Both planets orbit metal-rich stars ([Fe/H]= $+0.26\pm 0.05$ dex and [Fe/H] = $+0.24 \pm 0.05$ dex, for TOI-481 and TOI-892, respectively) but at different evolutionary stages. TOI-481 is a $\rm M_{\star}$ = $1.14\pm0.02$ $\rm M_{\odot}$, $\rm R_{\star}$ = $1.66\pm0.02$ $\rm R_{\odot}$ G-type star ($T_{\rm eff}$ = $5735 \pm 72$ K), that with an age of 6.7 Gyr, is in the turn-off point of the main sequence. TOI-892, on the other hand, is a F-type dwarf star ($T_{\rm eff}$ = $6261 \pm 80$ K), which has a mass of $\rm M_{\star}$ = $1.28\pm0.03$ $\rm M_{\odot}$, and a radius of $\rm R_{\star}$ = $1.39\pm0.02$ $\rm R_{\odot}$. TOI-481 b and TOI-892 b join the scarcely populated region of transiting gas giants with orbital periods longer than 10 days, which is important to constrain theories of the formation and structure of hot Jupiters.

astro-ph.EP↗

arXiv2020

Influence of triaxial deformation on wobbling motion in even-even nuclei

The influence of triaxial deformation $γ$ on the purely collective form of wobbling motion in even-even nuclei are discussed based on the triaxial rotor model. It is found that the harmonic approximation is realized well when $γ=30^{\circ}$ for the properties of energy spectra and electric quadrupole transition probabilities, while this approximation gets bad when $γ$ deviates from $30^{\circ}$. A recent data from Coulomb excitation experiment, namely $3_1^+$ and $2_2^+$ for the $^{110}$Ru are studied and might be suggested as the bandhead of the wobbling bands. In addition, two types of angular momentum geometries for wobbling motion, stemming from different $γ$ values, are exhibited by azimuthal plots.

nucl-th↗

arXiv2020

Electric field control of disorder-tunable superconductivity and the emergence of quantum metal at an oxide interface

We report on an extraordinary field effect of the superconducting LaAlO3/KTaO3(111) interface with Tc ~2 K. By applying a gate voltage (VG) across KTaO3, the interface can be continuously tuned from superconducting into insulating states, yielding a dome-shaped Tc-VG dependence. The electric gating has only a minor effect on carrier density as evidenced in the Hall-effect measurement, while it changes spatial profile of the carriers in the interface, hence the carrier's disorder level significantly. As temperature is decreased, the resistance saturates at lowest temperature in both superconducting and insulating sides, despite an initial dramatic dropping or increasing, which suggests an emergence of quantum metallic state associated with failed superconductor and/or fragile insulator. A VG-modulation of the magnetic-field-driven superconductor to insulator quantum phase transition reveals a non-universal criticality.

cond-mat.supr-con↗

arXiv2020

PassVizor: Toward Better Understanding of the Dynamics of Soccer Passes

In soccer, passing is the most frequent interaction between players and plays a significant role in creating scoring chances. Experts are interested in analyzing players' passing behavior to learn passing tactics, i.e., how players build up an attack with passing. Various approaches have been proposed to facilitate the analysis of passing tactics. However, the dynamic changes of a team's employed tactics over a match have not been comprehensively investigated. To address the problem, we closely collaborate with domain experts and characterize requirements to analyze the dynamic changes of a team's passing tactics. To characterize the passing tactic employed for each attack, we propose a topic-based approach that provides a high-level abstraction of complex passing behaviors. Based on the model, we propose a glyph-based design to reveal the multi-variate information of passing tactics within different phases of attacks, including player identity, spatial context, and formation. We further design and develop PassVizor, a visual analytics system, to support the comprehensive analysis of passing dynamics. With the system, users can detect the changing patterns of passing tactics and examine the detailed passing process for evaluating passing tactics. We invite experts to conduct analysis with PassVizor and demonstrate the usability of the system through an expert interview.

cs.HC↗

arXiv2020

Linear convergence of random dual coordinate incremental aggregated gradient methods

In this paper, we consider the dual formulation of minimizing $\sum_{i\in I}f_i(x_i)+\sum_{j\in J} g_j(\mathcal{A}_jx)$ with the index sets $I$ and $J$ being large. To address the difficulties from the high dimension of the variable $x$ (i.e., $I$ is large) and the large number of component functions $g_j$ (i.e., $J$ is large), we propose a hybrid method called the random dual coordinate incremental aggregated gradient method by blending the random dual block coordinate descent method and the proximal incremental aggregated gradient method. To the best of our knowledge, no research is done to address the two difficulties simultaneously in this way. Based on a newly established descent-type lemma, we show that linear convergence of the classical proximal gradient method under error bound conditions could be kept even one uses delayed gradient information and randomly updates coordinate blocks. Three application examples are presented to demonstrate the prospect of the proposed method.

math.OC↗

arXiv2020

Magnetospheric Multiscale (MMS) observations of foreshock transients at their very early stage

Foreshock transients are ion kinetic structures in the ion foreshock. Due to their dynamic pressure perturbations, they can disturb the bow shock and magnetosphere-ionosphere system. They can also accelerate particles contributing to shock acceleration. However, it is still unclear how exactly they form. Recent particle-in-cell simulations point out the important role of electric field and Hall current in the formation process. To further examine this, we use data from the Magnetospheric Multiscale (MMS) mission to apply case studies on two small (1000-2000 km) foreshock transient events that just started to form. In event 1 where MMS were in a tetrahedral formation, we show that the current density configuration, which determined the magnetic field profile, was mainly driven by Hall currents generated by demagnetized foreshock ions. The resulting time variation of the magnetic field induced electric field that drove cold plasma moving outward with magnetic field lines. In event 2 where MMS were in a string-of-pearls formation, we analyze the evolution of field and plasma parameters. We show that the magnetic flux and mass flux were transported outward from the core resulting in the steepening of the boundary. The steepened boundary, which trapped more foreshock ions and caused stronger demagnetization of foreshock ions, nonlinearly further enhanced the Hall current. Based on our observations, we propose a physical formation process that the positive feedback of foreshock ions on the varying magnetic field caused by the foreshock ion Hall current enables an instability and the growth of the structure.

physics.space-ph↗

arXiv2020

Epitaxial Growth of Two-dimensional Insulator Monolayer Honeycomb BeO

The emergence of two-dimensional (2D) materials launched a fascinating frontier of flatland electronics. Most crystalline atomic layer materials are based on layered van der Waals materials with weak interlayer bonding, which naturally leads to thermodynamically stable monolayers. We report the synthesis of a 2D insulator comprised of a single atomic sheet of honeycomb structure BeO (h-BeO), although its bulk counterpart has a wurtzite structure. The h-BeO is grown by molecular beam epitaxy (MBE) on Ag(111) thin films that are conveniently grown on Si(111) wafers. Using scanning tunneling microscopy and spectroscopy (STM/S), the honeycomb BeO lattice constant is determined to be 2.65 angstrom with an insulating band gap of 6 eV. Our low energy electron diffraction (LEED) measurements indicate that the h-BeO forms a continuous layer with good crystallinity at the millimeter scale. Moiré pattern analysis shows the BeO honeycomb structure maintains long range phase coherence in atomic registry even across Ag steps. We find that the interaction between the h-BeO layer and the Ag(111) substrate is weak by using STS and complimentary density functional theory calculations. We not only demonstrate the feasibility of growing h-BeO monolayers by MBE, but also illustrate that the large-scale growth, weak substrate interactions, and long-range crystallinity make h-BeO an attractive candidate for future technological applications. More significantly, the ability to create a stable single crystalline atomic sheet without a bulk layered counterpart is an intriguing approach to tailoring novel 2D electronic materials.

cond-mat.mes-hall↗

arXiv2020

Double lattice potential for molecular dynamics simulation of silicon with demonstrated validity

To reproduce the diamond structure of silicon, double lattice (DL) potential constructed from two interatomic potentials for face centered cubic (fcc) lattice, is proposed for molecular dynamics (MD) simulations. For the validity test of MD simulation, the Tersoff potential, the Stillinger and Weber (SW) potential, the environment-dependent interatomic (EDI) potential, the charge optimized many-body (COMB) potential, and the modified embedded-atom (MEAM) potential have been also employed for comparison. The crystal lattice of simulated silicon system is identified by calculating the distribution functions of the distances between the atoms and the angles between the lines linking an atom with its nearest neighbors. The results are also compared with the perfect silicon crystal. The crystal lattice, the crystallization temperature, and elastic constants have been calculated from MD simulations using above potentials. The results show that the systems with modified Tersoff, SW, EDI, COMB, and MEAM potentials could not exhibit the diamond structure and only the DL potential gives diamond lattice. The ground state for DL potential is the wurtzite structure, and the metastable state formed during rapid cooling is the cubic diamond structure. The physical parameters obtained from the simulation with DL potential are in agreement with the experiment results. This work indicated that only DL potential is valid for MD simulation of silicon crystal among above various potentials.

cond-mat.mtrl-sci↗

arXiv2020

User independent Emotion Recognition with Residual Signal-Image Network

User independent emotion recognition with large scale physiological signals is a tough problem. There exist many advanced methods but they are conducted under relatively small datasets with dozens of subjects. Here, we propose Res-SIN, a novel end-to-end framework using Electrodermal Activity(EDA) signal images to classify human emotion. We first apply convex optimization-based EDA (cvxEDA) to decompose signals and mine the static and dynamic emotion changes. Then, we transform decomposed signals to images so that they can be effectively processed by CNN frameworks. The Res-SIN combines individual emotion features and external emotion benchmarks to accelerate convergence. We evaluate our approach on the PMEmo dataset, the currently largest emotional dataset containing music and EDA signals. To the best of author's knowledge, our method is the first attempt to classify large scale subject-independent emotion with 7962 pieces of EDA signals from 457 subjects. Experimental results demonstrate the reliability of our model and the binary classification accuracy of 73.65% and 73.43% on arousal and valence dimension can be used as a baseline.

cs.CV↗

arXiv2020

Emotion Correlation Mining Through Deep Learning Models on Natural Language Text

Emotion analysis has been attracting researchers' attention. Most previous works in the artificial intelligence field focus on recognizing emotion rather than mining the reason why emotions are not or wrongly recognized. Correlation among emotions contributes to the failure of emotion recognition. In this paper, we try to fill the gap between emotion recognition and emotion correlation mining through natural language text from web news. Correlation among emotions, expressed as the confusion and evolution of emotion, is primarily caused by human emotion cognitive bias. To mine emotion correlation from emotion recognition through text, three kinds of features and two deep neural network models are presented. The emotion confusion law is extracted through orthogonal basis. The emotion evolution law is evaluated from three perspectives, one-step shift, limited-step shifts, and shortest path transfer. The method is validated using three datasets-the titles, the bodies, and the comments of news articles, covering both objective and subjective texts in varying lengths (long and short). The experimental results show that, in subjective comments, emotions are easily mistaken as anger. Comments tend to arouse emotion circulations of love-anger and sadness-anger. In objective news, it is easy to recognize text emotion as love and cause fear-joy circulation. That means, journalists may try to attract attention using fear and joy words but arouse the emotion love instead; After news release, netizens generate emotional comments to express their intense emotions, i.e., anger, sadness, and love. These findings could provide insights for applications regarding affective interaction such as network public sentiment, social media communication, and human-computer interaction.

cs.CL↗

arXiv2020

AutoSTR: Efficient Backbone Search for Scene Text Recognition

Scene text recognition (STR) is very challenging due to the diversity of text instances and the complexity of scenes. The community has paid increasing attention to boost the performance by improving the pre-processing image module, like rectification and deblurring, or the sequence translator. However, another critical module, i.e., the feature sequence extractor, has not been extensively explored. In this work, inspired by the success of neural architecture search (NAS), which can identify better architectures than human-designed ones, we propose automated STR (AutoSTR) to search data-dependent backbones to boost text recognition performance. First, we design a domain-specific search space for STR, which contains both choices on operations and constraints on the downsampling path. Then, we propose a two-step search algorithm, which decouples operations and downsampling path, for an efficient search in the given space. Experiments demonstrate that, by searching data-dependent backbones, AutoSTR can outperform the state-of-the-art approaches on standard benchmarks with much fewer FLOPS and model parameters.

cs.CV↗

arXiv2020

Chirality and Magnetic Field

We present a brief overview on recent developments of theory and phenomenology for novel many-body phenomena related to the chirality and magnetic field, with an emphasis on their experimental implications and possible detection in relativistic nuclear collisions.

nucl-th↗

arXiv2020

A lateral semicircular canal segmentation based geometric calibration for human temporal bone CT Image

Computed Tomography (CT) of the temporal bone has become an important method for diagnosing ear diseases. Due to the different posture of the subject and the settings of CT scanners, the CT image of the human temporal bone should be geometrically calibrated to ensure the symmetry of the bilateral anatomical structure. Manual calibration is a time-consuming task for radiologists and an important pre-processing step for further computer-aided CT analysis. We propose an automatic calibration algorithm for temporal bone CT images. The lateral semicircular canals (LSCs) are segmented as anchors at first. Then, we define a standard 3D coordinate system. The key step is the LSC segmentation. We design a novel 3D LSC segmentation encoder-decoder network, which introduces a 3D dilated convolution and a multi-pooling scheme for feature fusion in the encoding stage. The experimental results show that our LSC segmentation network achieved a higher segmentation accuracy. Our proposed method can help to perform calibration of temporal bone CT images efficiently.

eess.IV↗

arXiv2020

A planet within the debris disk around the pre-main-sequence star AU Microscopii

AU Microscopii (AU Mic) is the second closest pre main sequence star, at a distance of 9.79 parsecs and with an age of 22 million years. AU Mic possesses a relatively rare and spatially resolved3 edge-on debris disk extending from about 35 to 210 astronomical units from the star, and with clumps exhibiting non-Keplerian motion. Detection of newly formed planets around such a star is challenged by the presence of spots, plage, flares and other manifestations of magnetic activity on the star. Here we report observations of a planet transiting AU Mic. The transiting planet, AU Mic b, has an orbital period of 8.46 days, an orbital distance of 0.07 astronomical units, a radius of 0.4 Jupiter radii, and a mass of less than 0.18 Jupiter masses at 3 sigma confidence. Our observations of a planet co-existing with a debris disk offer the opportunity to test the predictions of current models of planet formation and evolution.

astro-ph.EP↗

arXiv2020

The structure of strong $k$-quasi-transitive digraphs with large diameters

Let $k$ be an integer with $k\geq 2$. A digraph $D$ is $k$-quasi-transitive, if for any path $x_0x_1\ldots x_k$ of length $k$, $x_0$ and $x_k$ are adjacent. Suppose that there exists a path of length at least $k+2$ in $D$. Let $P$ be a shortest path of length $k+2$ in $D$. Wang and Zhang [Hamiltonian paths in $k$-quasi-transitive digraphs, Discrete Mathematics, 339(8) (2016) 2094--2099] proved that if $k$ is even and $k\ge 4$, then $D[V(P)]$ and $D[V(D)\setminus V(P)]$ are both semicomplete digraphs. In this paper, we shall prove that if $k$ is odd and $k\ge 5$, then $D[V(P)]$ is either a semicomplete digraph or a semicomplete bipartite digraph and $D[V(D)\setminus V(P)]$ is either a semicomplete digraph, a semicomplete bipartite digraph or an empty digraph.

math.CO↗