arXiv subjects

Wei Li

Publications and source records attributed to Wei Li.

At least 1,243 records · Page 69Linked to original sources

arXiv2018

Surface symmetry breaking and disorder effects on superconductivity in perovskite BaBi3 epitaxial films

The structural or electronic symmetry breaking of the host lattice is a recurrent phenomenon in many quantum materials, including superconductors. Yet, how these broken symmetry states affect the electronic pair wave function of superconductivity have been rarely elucidated. Here, using low-temperature scanning tunneling microscopy and first-principles calculations, we identify the broken rotational symmetry via stripe ordering on the (001) surface of perovskite BaBi3 films grown by molecular beam epitaxy, and show that it consequently leads to anisotropic superconductivity with twofold symmetry. In contrast, the structural disorder smears out the anisotropy of electron pairing and fills superconducting subgap density of states as the film thickness is reduced. A quasi-long range model of superconducting fluctuations is revealed to describe the tunneling conductance spectra of thin BaBi3 films well, and to exemplify how disorders contribute to the low-energy quasiparticle excitations in superconductors. Our findings help understand the effects of symmetry breaking states and disorders on superconductivity, particularly the existing tunneling conductance spectra there.

cond-mat.supr-con↗

arXiv2018

Sememe Prediction: Learning Semantic Knowledge from Unstructured Textual Wiki Descriptions

Huge numbers of new words emerge every day, leading to a great need for representing them with semantic meaning that is understandable to NLP systems. Sememes are defined as the minimum semantic units of human languages, the combination of which can represent the meaning of a word. Manual construction of sememe based knowledge bases is time-consuming and labor-intensive. Fortunately, communities are devoted to composing the descriptions of words in the wiki websites. In this paper, we explore to automatically predict lexical sememes based on the descriptions of the words in the wiki websites. We view this problem as a weakly ordered multi-label task and propose a Label Distributed seq2seq model (LD-seq2seq) with a novel soft loss function to solve the problem. In the experiments, we take a real-world sememe knowledge base HowNet and the corresponding descriptions of the words in Baidu Wiki for training and evaluation. The results show that our LD-seq2seq model not only beats all the baselines significantly on the test set, but also outperforms amateur human annotators in a random subset of the test set.

cs.CL↗

arXiv2018

Band gap and band offset of Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys

Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys are promising materials for solar-blind UV photodetectors and high-power transistors. Basic key parameters in the device design, such as band gap variation with alloy composition and band offset between Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$, are yet to be established. Using density functional theory with the HSE hybrid functional, we compute formation enthalpies, band gaps, and band edge positions of (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys in the monoclinic ($β$) and corundum ($α$) phases. We find the formation enthlapies of (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys are significantly lower than of (In$_x$Ga$_{1-x}$)$_2$O$_3$, and that (Al$_x$Ga$_{1-x}$)$_2$O$_3$ with $x$=0.5 can be considered as an ordered compound AlGaO$_3$ in the monoclinic phase, with Al occupying the octahedral sites and Ga occupying the tetrahedral sites. The direct band gaps of the alloys range from 4.69 to 7.03 eV for $β$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ and from 5.26 to 8.56 eV for $α$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$. Most of the band offset of the (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloy arises from the discontinuity in the conduction band. Our results are used to explain the available experimental data, and consequences for designing modulation-doped field effect transistors (MODFETs) based on (Al$_x$Ga$_{1-x}$)$_2$O$_3$/Ga$_2$O$_3$ are discussed.

cond-mat.mtrl-sci↗

arXiv2018

Twin-plane-partitions and $\mathcal{N}=2$ affine Yangian

The universal enveloping algebra of ${\cal W}_{1+\infty}$ is isomorphic to the affine Yangian of $\mathfrak{gl}_1$. We study the ${\cal N}=2$ supersymmetric version of this correspondence, and identify the full set of defining relations of the supersymmetric affine Yangian. These relations can be deduced by demanding that the algebra has a representation on twin-plane-partitions, which we construct by gluing pairs of plane partitions. We define the action of the algebra on these twin-plane-partitions explicitly.

hep-th↗

arXiv2018

Continuous-Scale Kinetic Fluid Simulation

Kinetic approaches, i.e., methods based on the lattice Boltzmann equations, have long been recognized as an appealing alternative for solving incompressible Navier-Stokes equations in computational fluid dynamics. However, such approaches have not been widely adopted in graphics mainly due to the underlying inaccuracy, instability and inflexibility. In this paper, we try to tackle these problems in order to make kinetic approaches practical for graphical applications. To achieve more accurate and stable simulations, we propose to employ the non-orthogonal central-moment-relaxation model, where we develop a novel adaptive relaxation method to retain both stability and accuracy in turbulent flows. To achieve flexibility, we propose a novel continuous-scale formulation that enables samples at arbitrary resolutions to easily communicate with each other in a more continuous sense and with loose geometrical constraints, which allows efficient and adaptive sample construction to better match the physical scale. Such a capability directly leads to an automatic sample construction which generates static and dynamic scales at initialization and during simulation, respectively. This effectively makes our method suitable for simulating turbulent flows with arbitrary geometrical boundaries. Our simulation results with applications to smoke animations show the benefits of our method, with comparisons for justification and verification.

cs.GR↗

arXiv2018

Topological and Geometric Universal Thermodynamics in Conformal Field Theory

Universal thermal data in conformal field theory (CFT) offer a valuable means for characterizing and classifying criticality. With improved tensor network techniques, we investigate the universal thermodynamics on a nonorientable minimal surface, the crosscapped disk (or real projective plane, $\mathbb{RP}^2$). Through a cut-and-sew process, $\mathbb{RP}^2$ is topologically equivalent to a cylinder with rainbow and crosscap boundaries. We uncover that the crosscap contributes a fractional topological term $\frac{1}{2} \ln{k}$ related to nonorientable genus, with $k$ a universal constant in two-dimensional CFT, while the rainbow boundary gives rise to a geometric term $\frac{c}{4} \lnβ$, with $β$ the manifold size and $c$ the central charge. We have also obtained analytically the logarithmic rainbow term by CFT calculations, and discuss its connection to the renowned Cardy-Peschel conical singularity.

cond-mat.str-el↗

arXiv2018

Atomic Visualization of Copper Oxide Structure in Infinite-Layer Cuprate SrCuO2

We report on atomic-scale visualization of the structure of infinite-layer cuprate SrCuO2 thin films grown on Nb-doped SrTiO3 substrates by molecular beam epitaxy. In-situ scanning tunneling microscopy study reveals stoichiometric copper oxide (CuO2) plane with a 2 x 2 surface reconstruction, prompted by preferential clustering of four adjacent CuO2 plaquettes. By imaging the subsurface Sr atoms, intra-unit-cell rotational symmetry breaking is observed, which, together with the adjacent CuO2 clustering, can be well accounted for by a periodic up-down buckling of oxygen ions on the CuO2 plane. Further post-annealing leads to an incommensurate stripe structure of the surface layer. Our findings provide important structural information for deeply understanding the electronic structure of superconducting CuO2 plane as well as high temperature superconductivity in cuprates.

cond-mat.supr-con↗

arXiv2018

Nonadiabatic population transfer in a tangent-pulse driven quantum model

Fine control of the dynamics of a quantum system is the key element to perform quantum information processing and coherent manipulations for atomic and molecular systems. In this paper we propose a control protocol using a tangent-pulse driven model and demonstrate that it indicates a desirable design, i.e., of being both fast and accurate for population transfer. As opposed to other existing strategies, a remarkable character of the present scheme is that high velocity of the nonadiabatic evolution itself not only will not lead to unwanted transitions but also can suppress the error caused by the truncation of the driving pulse.

quant-ph↗

arXiv2018

SGM: Sequence Generation Model for Multi-label Classification

Multi-label classification is an important yet challenging task in natural language processing. It is more complex than single-label classification in that the labels tend to be correlated. Existing methods tend to ignore the correlations between labels. Besides, different parts of the text can contribute differently for predicting different labels, which is not considered by existing models. In this paper, we propose to view the multi-label classification task as a sequence generation problem, and apply a sequence generation model with a novel decoder structure to solve it. Extensive experimental results show that our proposed methods outperform previous work by a substantial margin. Further analysis of experimental results demonstrates that the proposed methods not only capture the correlations between labels, but also select the most informative words automatically when predicting different labels.

cs.CL↗

arXiv2018

Quantum anomalous Hall multilayers grown by molecular beam epitaxy

Quantum anomalous Hall (QAH) effect is a quantum Hall effect that occurs without the need of external magnetic field. A system composed of multiple parallel QAH layers is an effective high Chern number QAH insulator and the key to the applications of the dissipationless chiral edge channels in low energy consumption electronics. Such a QAH multilayer can also be engineered into other exotic topological phases such as a magnetic Weyl semimetal with only one pair of Weyl points. This work reports the first experimental realization of QAH multilayers in the superlattices composed of magnetically doped (Bi,Sb)$_2$Te$_3$ topological insulator and CdSe normal insulator layers grown by molecular beam epitaxy. The obtained multilayer samples show quantized Hall resistance $h/Ne$$^2$, where $h$ is the Planck's constant, $e$ is the elementary charge and $N$ is the number of the magnetic topological insulator layers, resembling a high Chern number QAH insulator.

cond-mat.mtrl-sci↗

arXiv2018

Effective definability of Kolchin polynomials

While the natural model-theoretic ranks available in differentially closed fields (of characteristic zero), namely Lascar and Morley rank, are known not to be definable in families of differential varieties; in this note we show that the differential-algebraic rank given by the Kolchin polynomial is in fact definable. As a byproduct, we are able to prove that the property of being weakly irreducible for a differential variety is also definable in families. The question of full irreducibility remains open, it is known to be equivalent to the generalized Ritt problem.

math.AC↗

arXiv2018

Mean-field theory for the Nagel-Schreckenberg model with overtaking strategy

Based on the Nagel-Schreckenberg (NS) model with periodic boundary conditions, a modified model considered overtaking strategy (NSOS) has been proposed \cite{su2016occurrence,su2016the}. In this paper, we focus on the theoretical analysis of traffic flow for NSOS model by using mean-field method. In the special case of $v_{max}=1$ where vehicles can not overtake preceding ones, the features of stationary state can be obtained exactly. However, in the case of $v_{max}>1$ where overtaking happens, some approximative methods have to be took into account. The main results are that we find the reason why traffic flow is increased in the regime where densities exceed the maximum flow density, and the influence of traffic flow on the transition density is dominated by the braking probability $p$.

nlin.CG↗

arXiv2018

Scott approach distance on metric spaces

The notion of Scott distance between points and subsets in a metric space, a metric analogy of the Scott topology on an ordered set, is introduced, making a metric space into an approach space. Basic properties of Scott distance are investigated, including its topological coreflection and its relation to injective $T_0$ approach spaces. It is proved that the topological coreflection of the Scott distance is sandwiched between the $d$-Scott topology and the generalized Scott topology; and that every injective $T_0$ approach space is a cocomplete and continuous metric space equipped with its Scott distance.

math.GN↗

arXiv2018

High-dimensional measurement-device-independent quantum key distribution based on spatial basis

Improving the secret key rate is one of the vital issues in practical applications of quantum key distribution (QKD). In this paper, we propose an experimental scheme of high-dimensional measurement-device-independent quantum key distribution (MDI-QKD) based on spatial basis aiming to increase the key rate. Two groups of discrete position basis and momentum basis are applied as conjugate spaces to generate quantum secret key. The position states are transmitted by single-mode fibers and represented by the index of the fiber, while the momentum state is a coherent superposition of the position states characterized by the phase gradient. The measurement of each momentum basis is realized by multi-slit diffraction. This experimental proposal can be implemented with standard optical elements. In addition to an enhanced key rate in a higher dimension, this high-dimensional MDI-QKD exhibits a comparable security level/performance compared to conventional polarization-based MDI-QKD.

physics.optics↗

arXiv2018

Bearing fault diagnosis based on domain adaptation using transferable features under different working conditions

Bearing failure is the most common failure mode in rotating machinery and can result in large financial losses or even casualties. However, complex structures around bearing and actual variable working conditions can lead to large distribution difference of vibration signal between a training set and a test set, which causes the accuracy-dropping problem of fault diagnosis. Thus, how to improve efficiently the performance of bearing fault diagnosis under different working conditions is always a primary challenge. In this paper, a novel bearing fault diagnosis under different working conditions method is proposed based on domain adaptation using transferable features(DATF). The dataset of normal bearing and faulty bearings are obtained through the fast Fourier transformation(FFT) of raw vibration signals under different motor speeds and load conditions. Then we reduce marginal and conditional distributions simultaneously across domains based on maximum mean discrepancy(MMD) in feature space by refining pseudo test labels, which can be obtained by the Nearest-Neighbor(NN) classifier built on training data, and then a robust transferable feature representation for training and test domains is achieved after several iterations. With the help of the NN classifier trained on transferable features, bearing fault categories are identified accurately in final. Extensive experiment results show that the proposed method under different working conditions can identify the bearing faults accurately and outperforms obviously competitive approaches.

eess.SP↗

arXiv2018

Predicting the thermodynamic stability of perovskite oxides using machine learning models

Perovskite materials have become ubiquitous in many technologically relevant applications, ranging from catalysts in solid oxide fuel cells to light absorbing layers in solar photovoltaics. The thermodynamic phase stability is a key parameter that broadly governs whether the material is expected to be synthesizable, and whether it may degrade under certain operating conditions. Phase stability can be calculated using Density Functional Theory (DFT), but the significant computational cost makes such calculation potentially prohibitive when screening large numbers of possible compounds. In this work, we developed machine learning models to predict the thermodynamic phase stability of perovskite oxides using a dataset of more than 1900 DFT-calculated perovskite oxide energies. The phase stability was determined using convex hull analysis, with the energy above the convex hull (Ehull) providing a direct measure of the stability. We generated a set of 791 features based on elemental property data to correlate with the Ehull value of each perovskite compound. For classification, the extra trees algorithm achieved the best prediction accuracy of 0.93 (+/- 0.02), with an F1 score of 0.88 (+/- 0.03). For regression, leave-out 20% cross-validation tests with kernel ridge regression achieved the minimal root mean square error (RMSE) of 28.5 (+/- 7.5) meV/atom between cross-validation predicted Ehull values and DFT calculations, with the mean absolute error (MAE) in cross-validation energies of 16.7 (+/- 2.3) meV/atom. We further validated our model by predicting the stability of compounds not present in the training set and demonstrated our machine learning models are a fast and effective means of obtaining qualitatively useful guidance for a wide-range of perovskite oxide stability, potentially impacting materials design choices in a variety of technological applications.

cond-mat.mtrl-sci↗

arXiv2018

Large Disparity Between Optical and Fundamental Band Gaps in Layered In2Se3

In$_2$Se$_3$ is a semiconductor material that can be stabilized in different crystal structures (at least one 3D and several 2D layered structures have been reported) with diverse electrical and optical properties. This feature has plagued its characterization over the years, with reported band gaps varying in an unacceptable range of 1 eV. Using first-principles calculations based on density functional theory and the HSE06 hybrid functional, we investigated the structural and electronic properties of four layered phases of In$_2$Se$_3$, addressing their relative stability and the nature of their fundamental band gaps, i.e., direct {\em versus} indirect. Our results show large disparities between fundamental and optical gaps. The absorption coefficients are found to be as high as that in direct-gap III-V semiconductors. The band alignment with respect to conventional semiconductors indicate a tendency to $n$-type conductivity, explaining recent experimental observations.

cond-mat.mtrl-sci↗

arXiv2018

The supersymmetric affine Yangian

The affine Yangian of $\mathfrak{gl}_1$ is known to be isomorphic to ${\cal W}_{1+\infty}$, the $W$-algebra that characterizes the bosonic higher spin -- CFT duality. In this paper we propose defining relations of the Yangian that are relevant for the ${\cal N}=2$ superconformal version of ${\cal W}_{1+\infty}$. Our construction is based on the observation that the ${\cal N}=2$ superconformal ${\cal W}_{1+\infty}$ algebra contains two commuting bosonic ${\cal W}_{1+\infty}$ algebras, and that the additional generators transform in bi-minimal representations with respect to these two algebras. The corresponding affine Yangian can therefore be built up from two affine Yangians of $\mathfrak{gl}_1$ by adding in generators that transform appropriately.

hep-th↗