arXiv subjects

Wei Luo

Publications and source records attributed to Wei Luo.

At least 163 records · Page 9Linked to original sources

arXiv2021

Floquet band engineering and topological phase transitions in 1T' transition metal dichalcogenides

Using ab initio tight-binding approaches, we investigate Floquet band engineering of the 1T' phase of transition metal dichalcogenides (MX2, M = W, Mo and X = Te, Se, S) monolayers under the irradiation with circularly polarized light. Our first principles calculations demonstrate that light can induce important transitions in the topological phases of this emerging materials family. For example, upon irradiation, Te-based MX2 undergoes a phase transition from quantum spin Hall (QSH) semimetal to time-reversal symmetry broken QSH insulator with a nontrivial band gap of up to 92.5 meV. On the other hand, Se- and S-based MX2 undergoes the topological phase transition from the QSH effect to the quantum anomalous Hall (QAH) effect and into trivial phases with increasing light intensity. From a general perspective, our work brings further insight into non-equilibrium topological systems.

cond-mat.mtrl-sci↗

arXiv2021

Product-oriented Machine Translation with Cross-modal Cross-lingual Pre-training

Translating e-commercial product descriptions, a.k.a product-oriented machine translation (PMT), is essential to serve e-shoppers all over the world. However, due to the domain specialty, the PMT task is more challenging than traditional machine translation problems. Firstly, there are many specialized jargons in the product description, which are ambiguous to translate without the product image. Secondly, product descriptions are related to the image in more complicated ways than standard image descriptions, involving various visual aspects such as objects, shapes, colors or even subjective styles. Moreover, existing PMT datasets are small in scale to support the research. In this paper, we first construct a large-scale bilingual product description dataset called Fashion-MMT, which contains over 114k noisy and 40k manually cleaned description translations with multiple product images. To effectively learn semantic alignments among product images and bilingual texts in translation, we design a unified product-oriented cross-modal cross-lingual model (\upoc~) for pre-training and fine-tuning. Experiments on the Fashion-MMT and Multi30k datasets show that our model significantly outperforms the state-of-the-art models even pre-trained on the same dataset. It is also shown to benefit more from large-scale noisy data to improve the translation quality. We will release the dataset and codes at https://github.com/syuqings/Fashion-MMT.

cs.CV↗

arXiv2021

Sign reversal of magnetoresistivity in massive nodal-line semimetals due to Lifshitz transition of Fermi surface

Topological nodal-line semimetals offer an interesting research platform to explore novel phenomena associated with its torus-shaped Fermi surface. Here, we study magnetotransport in the massive nodal-line semimetal with spin-orbit coupling and finite Berry curvature distribution which exists in many candidates. The magnetic field leads to a deformation of the Fermi torus through its coupling to the orbital magnetic moment, which turns out to be the main scenario of the magnetoresistivity (MR) induced by the Berry curvature effect. We show that a small deformation of the Fermi surface yields a positive MR $\propto B^2$, different from the negative MR by pure Berry curvature effect in other topological systems. As the magnetic field increases to a critical value, a topological Lifshitz transition of the Fermi surface can be induced, and the MR inverts its sign at the same time. The temperature dependence of the MR is investigated, which shows a totally different behavior before and after the Lifshitz transition. Our work uncovers a novel scenario of the MR induced solely by the deformation of the Fermi surface and establishes a relation between the Fermi surface topology and the sign of the MR.

cond-mat.mes-hall↗

arXiv2021

Large time behavior of global strong solutions to the 2-D compressible FENE dumbbell model

In this paper, we mainly study large time behavior of the strong solutions to the 2-D compressible finite extensible nonlinear elastic (FENE) dumbbell model. The Fourier splitting method yields that the $L^2$ decay rate is $\ln^{-l}(e+t)$ for any $l\in\mathbb{N}$. By virtue of the time weighted energy estimate, we can improve the decay rate to $(1+t)^{-\frac{1}{4}}$. Under the low-frequency condition and by the Littlewood-Paley theory, we show that the solutions belong to some Besov space with negative index and obtain the optimal $L^2$ decay rate.

math.AP↗

arXiv2021

Global strong solutions and optimal $L^2$ decay to the compressible FENE dumbbell model

In this paper, we are concerned with the global well-posedness and $L^2$ decay rate for the strong solutions of the compressible finite extensible nonlinear elastic (FENE) dumbbell model. For $d\geq 2$, we prove that the compressible FENE dumbbell model admits a unique global strong solution provided the initial data are close to equilibrium state. Moreover, by the Littlewood-Paley decomposition theory and the Fourier splitting method, we show optimal $L^2$ decay rate of global strong solutions for $d\geq 3$.

math.AP↗

arXiv2021

Integrality of the LMOV invariants for framed unknot

The Labastida-Marinõ-Ooguri-Vafa (LMOV) invariants are the open string BPS invariants which are expected to be integers based on the string duality conjecture from M-theory. Several explicit formulae of LMOV invariants for framed unknot have been obtained in the literature. In this paper, we present a unified method to deal with the integrality of such explicit formulae. Furthermore, we also prove the integrality of certain LMOV invariants for framed unknot in higher genera.

math.GT↗

arXiv2021

Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors

We consider forecasting a single time series using a large number of predictors in the presence of a possible nonlinear forecast function. Assuming that the predictors affect the response through the latent factors, we propose to first conduct factor analysis and then apply sufficient dimension reduction on the estimated factors, to derive the reduced data for subsequent forecasting. Using directional regression and the inverse third-moment method in the stage of sufficient dimension reduction, the proposed methods can capture the non-monotone effect of factors on the response. We also allow a diverging number of factors and only impose general regularity conditions on the distribution of factors, avoiding the undesired time reversibility of the factors by the latter. These make the proposed methods fundamentally more applicable than the sufficient forecasting method in Fan et al. (2017). The proposed methods are demonstrated in both simulation studies and an empirical study of forecasting monthly macroeconomic data from 1959 to 2016. Also, our theory contributes to the literature of sufficient dimension reduction, as it includes an invariance result, a path to perform sufficient dimension reduction under the high-dimensional setting without assuming sparsity, and the corresponding order-determination procedure.

math.ST↗

arXiv2021

The continuous dependence for the Navier-Stokes equations in $\dot{B}^{\frac{d}{p}-1}_{p,r}$

In this paper, we mainly investigate the Cauchy problem for the incompressible Navier-Stokes equations in homogeneous Besov spaces $\dot{B}^{\frac{d}{p}-1}_{p,r}$ with $1\leq p<\infty,\ 1\leq r\leq \infty, \ d\geq 2$. Firstly, we prove the local existence of the solution and give a lower bound of the lifespan $T$ of the solution. The lifespan depends on the Littlewood-Paley decomposition of the initial data, that is $\dotΔ_j u_0$. Secondly, if the initial data $u^n_0\rightarrow u_0$ in $\dot{B}^{\frac{d}{p}-1}_{p,r}$, then the corresponding lifespan $T_n\rightarrow T$. Thirdly, we prove that the data-to-solutions map is continuous in $\dot{B}^{\frac{d}{p}-1}_{p,r}$. Therefore, the Cauchy problem of the Navier-Stokes equations is locally well-posed in the critical Besov spaces in the Hadamard sense. Moreover, we also obtain well-posedness and weak-strong uniqueness results in $L^{\infty}L^2\cap L^{2}\dot{H}^1$.

math.AP↗

arXiv2020

Anomalous Andreev Reflection on a Torus-Shaped Fermi Surface

Andreev reflection (AR) refers to the electron-hole conversion at the normal metal-superconductor interface. In a three-dimensional metal with spherical Fermi surface, retro (specular) AR can occur with the sign reversal of all three (a single) components of particle velocity. Here, we predict a novel type of AR with the inversion of two velocity components, dubbed "anomalous-trajectory Andreev reflection" (AAR), which can be realized in a class of materials with torus-shaped Fermi surface, such as doped nodal line semimetals. For its toroidal circle perpendicular to the interface, the Fermi torus doubles the AR channels and generates multiple AR processes. In particular, the AAR and retro AR are found to dominate electron transport in the light and heavy doping regimes, respectively. We show that the AAR visibly manifests as a ridge structure in the spatially resolved nonlocal conductance, in contrast to the peak structure for the retro AR. Our work opens a new avenue for the AR spectroscopy and offers a clear transport signature of torus-shaped Fermi surface.

cond-mat.supr-con↗

arXiv2020

The estimate of lifespan and local well-posedness for the non-resistive MHD equations in homogeneous Besov spaces

In this paper, we mainly investigate the Cauchy problem of the non-resistive MHD equation. We first establish the local existence in the homogeneous Besov space $\dot{B}^{\frac{d}{p}-1}_{p,1}\times \dot{B}^{\frac{d}{p}}_{p,1}$ with $p<\infty$, and give a lifespan $T$ of the solution which depends on the norm of the Littlewood-Paley decomposition of the initial data. Then, we prove that if the initial data $(u^n_0,b^n_0)\rightarrow (u_0,b_0)$ in $\dot{B}^{\frac{d}{p}-1}_{p,1}\times \dot{B}^{\frac{d}{p}}_{p,1}$, then the corresponding existence times $T_n\rightarrow T$, which implies that they have a common lower bound of the lifespan. Finally, we prove that the data-to-solutions map depends continuously on the initial data when $p\leq 2d$. Therefore the non-resistive MHD equation is local well-posedness in the homogeneous Besov space in the Hadamard sense. Our obtained result improves considerably the recent results in \cite{Li1,chemin1,Feffer2}.

math.AP↗

arXiv2020

Large time behavior to the FENE dumbbell model of polymeric flows near equilibrium

In this paper we mainly study large time behavior for the strong solutions of the finite extensible nonlinear elastic (FENE) dumbbell model. There is a lot results about the $L^2$ decay rate of the co-rotation model. In this paper, we consider the general case. We prove that the optimal $L^2$ decay rate of the velocity is $(1+t)^{-\frac{d}{4}}$ with $d\geq 2$. This result improves the previous result in \cite{Luo-Yin}.

math.AP↗

arXiv2020

Vanishing viscosity limit to the FENE dumbbell model of polymeric flows

In this paper we mainly investigate the inviscid limit for the strong solutions of the finite extensible nonlinear elastic (FENE) dumbbell model. By virtue of the Littlewood-Paley theory, we first obtain a uniform estimate for the solution to the FENE dumbbell model with viscosity in Besov spaces. Moreover, we show that the data-to-solution map is continuous. Finally, we prove that the strong solution of the FENE dumbbell model converges to a Euler system couple with a Fokker-Planck equation. Furthermore, convergence rates in Lebesgue spaces are obtained also.

math.AP↗

arXiv2020

Learning Semantically Enhanced Feature for Fine-Grained Image Classification

We aim to provide a computationally cheap yet effective approach for fine-grained image classification (FGIC) in this letter. Unlike previous methods that rely on complex part localization modules, our approach learns fine-grained features by enhancing the semantics of sub-features of a global feature. Specifically, we first achieve the sub-feature semantic by arranging feature channels of a CNN into different groups through channel permutation. Meanwhile, to enhance the discriminability of sub-features, the groups are guided to be activated on object parts with strong discriminability by a weighted combination regularization. Our approach is parameter parsimonious and can be easily integrated into the backbone model as a plug-and-play module for end-to-end training with only image-level supervision. Experiments verified the effectiveness of our approach and validated its comparable performance to the state-of-the-art methods. Code is available at https://github.com/cswluo/SEF

cs.CV↗

arXiv2020

MODEL: Motif-based Deep Feature Learning for Link Prediction

Link prediction plays an important role in network analysis and applications. Recently, approaches for link prediction have evolved from traditional similarity-based algorithms into embedding-based algorithms. However, most existing approaches fail to exploit the fact that real-world networks are different from random networks. In particular, real-world networks are known to contain motifs, natural network building blocks reflecting the underlying network-generating processes. In this paper, we propose a novel embedding algorithm that incorporates network motifs to capture higher-order structures in the network. To evaluate its effectiveness for link prediction, experiments were conducted on three types of networks: social networks, biological networks, and academic networks. The results demonstrate that our algorithm outperforms both the traditional similarity-based algorithms by 20% and the state-of-the-art embedding-based algorithms by 19%.

cs.SI↗

arXiv2020

Electrically tunable Kondo effect as a direct measurement of the chiral anomaly in disorder Weyl semimetals

We propose a mechanism to directly measure the chiral anomaly in disorder Weyl semimetals (WSMs) by the Kondo effect. We find that in a magnetic and electric field driven WSM, the locations of the Kondo peaks can be modulated by the chiral chemical potential, which is proportional to $\mathbf{E}\cdot \mathbf{B}$. The Kondo peaks come from spin fluctuations within the impurities, which apart from the temperature, relate closely to the host's Fermi level. In WSMs, the chiral-anomaly-induced chirality population imbalance will shift the local Fermi levels of the paired Weyl valleys toward opposite directions in energy, and then affects the Kondo effect. Consequently, the Kondo effect can be tunable by an external electric field via the chiral chemical potential. This is unique to the chiral anomaly. Base on this, we argue that the electrically tunable Kondo effect can serve as a direct measurement of the chiral anomaly in WSMs. The Kondo peaks are robust against the disorder effect and therefore, the signal of the chiral anomaly survives for a relatively weak magnetic field.

cond-mat.mes-hall↗

arXiv2020

Two-dimensional Topological Semimetals Protected by Symmorphic Symmetries

Two-dimensional (2D) band crossing semimetals (BCSMs) could be used to build a range of novel nanoscale devices such as superlenses and transistors. We find that symmorphic symmetry can protect a new type of robust 2D BCSMs, unlike the previously proposed 2D essential BCSMs protected by non-symmorphic symmetry [Young et al., Phys. Rev. Lett. 115, 126803 (2015)]. This type of symmorphic symmetry protected (SSP) 2D essential BCSMs cannot be pair annihilated without destroying the crystalline symmetries, as opposed to the 2D BCSMs caused by the accidental band crossing. Through group theory analysis, we find that 2D SSP BCSMs can only exist at the K (K') point of Brillouin zone (BZ) of four layer groups and identify nonmagnetic 2D FeB2 as a candidate. Interestingly, nonmagnetic 2D SSP BCSMs can host a single pair of band crossing points (BCPs), whereas nonmagnetic three-dimensional (3D) Weyl semimetals (WSMs) have at least two pairs of band crossing Weyl points. It is found that the single pair of BCPs are robust against any kinds of strain. Furthermore, our calculation suggests that essential 2D SSP BCSMs can be used to realize electric field control of spin-texture, thus are promising candidates for spintronic devices.

cond-mat.mes-hall↗

arXiv2020

Voltage-Induced Inertial Domain Wall Motion in an Antiferromagnetic Nanowire

Racetrack memory based on magnetic domain walls (DWs) motion exhibits advantages of small volume and high reading speed. When compared to current-induced DW motion, voltage-induced DW motion exhibits lower dissipation. On the other hand, the DW in an antiferromagnet (AFM) moves at a high velocity with weak stray field. In this work, the AFM DW motion induced by a gradient of magnetic anisotropy energy under a voltage pulse has been investigated in theory. The dynamics equation for the DW motion was derived. The solution indicates that the DW velocity is higher than 100 m/s, and because of inertia, the DW is able to keep moving at a speed of around 100 m/s for several nano seconds after turning off the voltage in a period of pulse. The mechanism for this DW inertia is explained based on the Lagrangian route. On the other hand, a spin wave is emitted while the DW is moving, yet the DW is still able to move at an ever increasing velocity with enlarging DW width. This indicates energy loss from emission of spin wave is less than the energy gain from the effective field of the gradient of anisotropy energy.

physics.app-ph↗

arXiv2020

Evolution of superconductivity and antiferromagnetic order in Ba(Fe$_{0.92-x}$Co$_{0.08}$V$_x$)$_2$As$_2$

The vanadium doping effects on superconductivity and magnetism of iron pnictides are investigated in Ba(Fe$_{0.92-x}$Co$_{0.08}$V$_x$)$_2$As$_2$ by transport, susceptibility and neutron scattering measurements. The doping of magnetic impurity V causes a fast suppression of superconductivity with T$_c$ reduced at a rate of 7.4~K/1\%V. On the other hand, the long-range commensurate $C$-type antiferromagnetic order is recovered upon the V doping. The value of ordered magnetic moments of Ba(Fe$_{0.92-x}$Co$_{0.08}$V$_x$)$_2$As$_2$ follows a dome-like evolution versus doping concentration x. A possible Griffiths-type antiferromagnetic region of multiple coexisting phases in the phase diagram of Ba(Fe$_{0.92-x}$Co$_{0.08}$V$_x$)$_2$As$_2$ is identified, in accordance with previous theoretical predictions based on a cooperative behavior of the magnetic impurities and the conduction electrons mediating the Ruderman-Kittel-Kasuya-Yosida interactions between them.

cond-mat.supr-con↗