arXiv subjects

Qian Wu

Publications and source records attributed to Qian Wu.

54 records · Page 3Linked to original sources

arXiv2022

Motion Sensitive Contrastive Learning for Self-supervised Video Representation

Contrastive learning has shown great potential in video representation learning. However, existing approaches fail to sufficiently exploit short-term motion dynamics, which are crucial to various down-stream video understanding tasks. In this paper, we propose Motion Sensitive Contrastive Learning (MSCL) that injects the motion information captured by optical flows into RGB frames to strengthen feature learning. To achieve this, in addition to clip-level global contrastive learning, we develop Local Motion Contrastive Learning (LMCL) with frame-level contrastive objectives across the two modalities. Moreover, we introduce Flow Rotation Augmentation (FRA) to generate extra motion-shuffled negative samples and Motion Differential Sampling (MDS) to accurately screen training samples. Extensive experiments on standard benchmarks validate the effectiveness of the proposed method. With the commonly-used 3D ResNet-18 as the backbone, we achieve the top-1 accuracies of 91.5\% on UCF101 and 50.3\% on Something-Something v2 for video classification, and a 65.6\% Top-1 Recall on UCF101 for video retrieval, notably improving the state-of-the-art.

cs.CV↗

arXiv2022

Investigating the muon catalyzed fusion in muonic lithium hydride

In this work, we consider the muonic LiH as a new stage of the $μ$ catalyzed fusion. We calculate the bound states of the muonic LiH and LiH$^+$ and their wave functions based on the three and four body approximation. In order to solve the Schr$\ddot{\rm o}$dinger equation, we apply the Gaussian expansion method which gives us both the eigen energies and the wave functions. The existences of the bound states in muonic LiH and LiH$^+$ are confirmed. We find the dynamical behaviors between the $^7$Li and proton in muonic LiH and LiH$^+$ are similar as the ones in dt$μ_2$ and dt$μ$, respectively. The $α$ sticking probability in the muonic LiH$^+$ after the nuclear fusion is studied. The calculated $α$ sticking probability of being captured to the ground state of He$μ$ is 5 times smaller than the one in dt$μ$.

nucl-th↗

arXiv2022

Intrinsic Layer-Polarized Anomalous Hall Effect in Bilayer MnBi2Te4

Layer-polarized anomalous Hall effect (LP-AHE) is an attractive phenomenon in condensed-matter physics from the standpoints of both fundamental interest and device applications. The current LP-AHE research is based on the extrinsic paradigm of using external electric fields, in which the generation and control of LP-AHE are not straightforward. Here, we propose a novel mechanism that realizes intrinsic LP-AHE in bilayer lattices, through the mediation of sliding physics and Berry curvature. Moreover, this mechanism could render the LP-AHE in a controllable and reversable fashion. We analyze the symmetry requirements for a system to host such intrinsic LP-AHE. Its validity is further demonstrated in a real material of bilayer MnBi2Te4. By stacking with broken inversion symmetry, the layer-locked Berry curvature enables the intrinsic LP-AHE in bilayer MnBi2Te4, and the switchable control of its LP-AHE is achieved by sliding ferroelectricity. Our work opens a significant new direction for LP-AHE and two-dimensional (2D) materials research.

cond-mat.mtrl-sci↗

arXiv2022

A Novel Markov Model for Near-Term Railway Delay Prediction

Predicting the near-future delay with accuracy for trains is momentous for railway operations and passengers' traveling experience. This work aims to design prediction models for train delays based on Netherlands Railway data. We first develop a chi-square test to show that the delay evolution over stations follows a first-order Markov chain. We then propose a delay prediction model based on non-homogeneous Markov chains. To deal with the sparsity of the transition matrices of the Markov chains, we propose a novel matrix recovery approach that relies on Gaussian kernel density estimation. Our numerical tests show that this recovery approach outperforms other heuristic approaches in prediction accuracy. The Markov chain model we propose also shows to be better than other widely-used time series models with respect to both interpretability and prediction accuracy. Moreover, our proposed model does not require a complicated training process, which is capable of handling large-scale forecasting problems.

cs.LG↗

arXiv2022

Pion parton distribution functions with the nonrelativistic constituent quark model

We calculate the valence quark distribution functions of the $π$ meson using the non-relativistic chiral constituent quark model. The $π$ wave function is obtained by solving the two-body Schrödinger equation within the framework of constituent quark model. We transform the $π$ wave function from the rest frame to the light cone or infinite momentum frame based on the Lorentz boost. The valence quark distributions at the initial evolution scale are obtained. The QCD evolution are given with the DGLAP equations with parton-parton recombination corrections. With tuning the valence up (down) quark mass to 70 MeV, the calculated valence up quark distributions at $Q^2=20$ GeV$^2$ are in good agreement with the E615 experimental data. The structure functions $\rm{F}_2^π(x,Q^2)$ of pion are also calculated which consist with the H1 experimental data. The proposed mechanisms here could be also used to study other hadrons.

hep-ph↗

arXiv2021

Main-Group Metal Elements as Promising Active Centers for Single-Atom Catalysts

Current research efforts on single-atom catalysts (SACs) exclusively focus on nonmetal or transition-metal atoms as active centers, while employing main-group metal elements is seemingly excluded because their delocalized s/p-bands are prone to yield a broadened resonance for the interaction with adsorbates. Here, we use high-throughput first-principles calculations to investigate the possible incorporation of Mg, Al and Ga to form graphene-based SACs for NO reduction reaction (NORR) toward NH3. 51 SAC candidates with different metal coordination environment have been computationally screened employing a rationally designed four-step process, yielding six SACs with high catalytic activity and NORR selectivity. The performance is rationalized by the modulation of s/p-band filling of the main-group metals. The adsorption free energy of NO is identified as efficient descriptor for such SACs. The underlying physical mechanism is revealed and generally applicable to other main group metal SACs. These fundamental insights extend SACs to main-group metal elements.

cond-mat.mtrl-sci↗

arXiv2021

Fractal Rosette: A Stable Space-Ground Network Structure in Mega-Constellation

We present F-Rosette, a stable space-ground network structure for low-earth orbit (LEO) satellite mega-constellations at scale. Due to the dynamic many-to-many space-ground mapping in high mobility, existing LEO mega-constellations with IP protocol stack suffer from frequent user IP address changes (every 133~510s per user) and network routing re-convergence (<20% network usability). To provably stabilize the space-ground network under high mobility and many-to-many dynamics, F-Rosette adopts a recursive structure over the Rosette constellation, derives a hierarchical and time-invariant network address space from a new geographical coordinate system, and ensures efficient and stable routing via geographical-to-topological routing embedding without re-convergence. Our hardware-in-the-loop, trace-driven emulations validate F-Rosette's stability, near-optimal routing (<1.4% additional delays), and marginal overhead (<1% CPU, <2MB memory) for resource-constrained satellites.

cs.NI↗

arXiv2021

Spontaneous valley polarization in 2D organometallic lattice

2D ferrovalley materials that exhibit spontaneous valley polarization are both fundamentally intriguing and practically appealing to be used in valleytronic devices. Usually, the research on 2D ferrovalley materials is mainly focused on inorganic systems, severely suffering from in-plane magnetization. Here, we alternatively show by kp model analysis and high-throughput first-principles calculations that ideal spontaneous valley polarization is present in 2D organometallic lattice. We explore the design principle for organic 2D ferrovalley materials composed of (quasi-)planer molecules and transition-metal atoms in hexagonal lattice, and identify twelve promising candidates. These systems have a ferromagnetic or antiferromagnetic semiconducting state, and importantly they exhibit robust out-of-plane magnetization. The interplay between spin and valley, together with strong spin-orbit coupling of transition-metal atoms, guarantee the spontaneous valley polarization in these systems, facilitating the anomalous valley Hall effect. Our findings significantly broaden the scientific and technological impact of ferrovalley physics.

cond-mat.mtrl-sci↗

arXiv2021

End-to-End Human Object Interaction Detection with HOI Transformer

We propose HOI Transformer to tackle human object interaction (HOI) detection in an end-to-end manner. Current approaches either decouple HOI task into separated stages of object detection and interaction classification or introduce surrogate interaction problem. In contrast, our method, named HOI Transformer, streamlines the HOI pipeline by eliminating the need for many hand-designed components. HOI Transformer reasons about the relations of objects and humans from global image context and directly predicts HOI instances in parallel. A quintuple matching loss is introduced to force HOI predictions in a unified way. Our method is conceptually much simpler and demonstrates improved accuracy. Without bells and whistles, HOI Transformer achieves $26.61\% $ $ AP $ on HICO-DET and $52.9\%$ $AP_{role}$ on V-COCO, surpassing previous methods with the advantage of being much simpler. We hope our approach will serve as a simple and effective alternative for HOI tasks. Code is available at https://github.com/bbepoch/HoiTransformer .

cs.CV↗

arXiv2020

Physical rendering of synthetic spaces for topological sound transport

Synthetic dimensions can be rendered in the physical space and this has been achieved with photonics and cold atomic gases, however, little to no work has been succeeded in acoustics because acoustic wave-guides cannot be weakly coupled in a continuous fashion. Here, we establish the theoretical principles and for the first time manufacture acoustic crystals composed of arrays of acoustic cavities strongly coupled through modulated channels to evidence one-dimensional (1D) and two-dimensional (2D) dynamic topological pumpings. In particular, the topological edge-bulkedge and corner-bulk-corner transport are physically illustrated in finite-sized acoustic structures. We delineate the generated 2D and four-dimensional (4D) quantum Hall effects by calculating first and second Chern numbers and demonstrating robustness against the geometrical imperfections. Synthetic dimensions could provide a powerful way for acoustic topological wave steering and open up a new platform to explore higher-order topological matter in dimensions four and higher.

cond-mat.mes-hall↗

arXiv2020

Channel-Coupling Fano Resonance and Acoustic Metadamping

Fano resonance featuring asymmetric spectral profiles originates from the interference of local resonances and background continuum. Its narrow-band nature looks seemingly adverse to broadband noise cancellation purposes. In this study, we report theoretically on an intriguing acoustic metamaterial capable of generating multiple Fano-like resonances to realize a broadband sound barrier with satisfactory transmission loss performance. Our proposed design involves an effective channel characterized by effective parameters and short channels filled with air. The effective channel support both monopolar and dipolar modes which interact with the continuum state admitted by the short channels to generate a pair of Fano-like resonances. Due to the destructive interference of sound waves, the two resonances result in transmission loss overall exceeding 10 dB over a broad range 0.6-1.1 kHz. In order to further optimize the overall performance, we introduce metadamping by integrating additional viscous foams in the proposed unit cell. Furthermore, for future experimental tests, the dampened design is decoded into a real space-coiling cell which exhibits identical functionality and is assembled into a partition wall to ensure transmission loss over 10 dB across the range 0.32-4 Hz. Lastly, acoustic negative refraction is accessible by deploying two coupled space-coiling channels in a similar fashion. We believe this work paves the way for realizing effective broadband sound insulation devices with efficient ventilation.

physics.app-ph↗

arXiv2020

Multilayer Routing and Resource Assignment in Spatial Channel Networks (SCNs): Oriented Toward the Massive SDM Era

In the past few decades, optical transport networks (OTNs) have undergone significant evolution, from the earliest wavelength-division multiplexing (WDM) OTNs to elastic optical networks (EONs) and later to space-division multiplexing (SDM) OTNs, to address the continuous growth of Internet traffic. By 2024, Pbps-level OTNs are expected, far exceeding the capacity limit of single-mode fibers. The massive SDM era is on the horizon. In this context, newly designed OTNs called spatial channel networks (SCNs), which achieve high cost efficiency by means of practical hierarchical optical cross-connects, have recently been proposed. However, the evolution of OTNs will simultaneously present challenges related to resource allocation in networking. For instance, with the evolution from WDM-OTNs to EONs, the resource allocation problem was transformed from the routing and wavelength assignment (RWA) problem to the routing and spectrum assignment (RSA) problem due to the additionally introduced constraint of spectrum contiguity. Similarly, specially designed algorithms are also expected to be essential for addressing the resource allocation problem in SCNs. In this paper, we define this new problem as the routing, spatial channel, and spectrum assignment (RSCSA) problem. We propose an integer linear programming (ILP) model and a heuristic algorithm to solve the RSCSA problem. We examine the performance of the proposed approaches via simulation experiments. The results show that both proposed approaches are effective in finding the optimal solutions or solutions close to the lower bounds. To the best of our knowledge, this is the first work to focus on the problem of resource allocation in SCNs.

cs.NI↗

arXiv2019

Three-body resonant states of $^9_Λ$Be with $α+α+Λ$ cluster model

We study the structure of $^9_Λ$Be in the framework of three body $α+α+Λ$ cluster model using YNG-NF interaction with the Gaussian expansion method. Employing the complex scaling method, we obtain the energies of bound states as well as energies and decay widths of the resonant states. By analyzing our wave functions of bound states and resonant states, we confirm three analogue states of $^9_Λ$Be pointed out by Band${\rm \bar{o}}$ and Motoba {\it et al.} \cite{motoba1983,motoba1985,bando1983}, $^8$Be analogue states, $^9_Λ$Be genuine states and $^9$Be analogue states. The new states of $^9_Λ$Be are also obtained at a high energy region with broader decay widths.

nucl-th↗

arXiv2018

Mass spectra of heavy mesons with instanton effects

We investigate the mass spectra of ordinary heavy mesons, based on a nonrelativistic potential approach. The heavy-light quark potential contains the Coulomb-type potential arising from one-gluon exchange, the confining potential, and the instanton-induced nonperturbative local heavy-light quark potential. All parameters are theoretically constrained and fixed. We carefully examine the effects from the instanton vacuum. Within the present form of the local potential from the instanton vacuum, we conclude that the instanton effects are rather marginal on the charmed mesons.

hep-ph↗

arXiv2018

Modeling and Routing for Predictable Dynamic Networks: This paper is only for copyright protection, and unpublished to the top-level version

The topologies of predictable dynamic networks are continuously dynamic in terms of node position, network connectivity and link metric. However, their dynamics are almost predictable compared with the ad-hoc network. The existing routing protocols specific to static or ad-hoc network do not consider this predictability and thus are not very efficient for some cases. We present a topology model based on Divide-and-Merge methodology to formulate the dynamic topology into the series of static topologies, which can reflect the topology dynamics correctly with the least number of static topologies. Then we design a dynamic programing algorithm to solve that model and determine the timing of routing update and the topology to be used. Besides, for the classic predictable dynamic network---space Internet, the links at some region have shorter delay, which leads to most traffic converge at these links. Meanwhile, the connectivity and metric of these links continuously vary, which results in a great end-to-end path variations and routing updates. In this paper, we propose a stable routing scheme which adds link life-time into its metric to eliminate these dynamics. And then we take use of the Dijkstra's greedy feature to release some paths from the dynamic link, achieving the goal of routing stability. Experimental results show that our method can significantly decrease the number of changed paths and affected network nodes, and then greatly improve the network stability. Interestingly, our method can also achieve better network performance, including the less number of loss packets, smoother variation of end-to-end delay and higher throughput.

cs.NI↗

arXiv2018

Calculation of Dissociation Temperature of Nucleon Using Gaussian Expansion Method

The first study of the dissociation temperature of nucleon in hot QCD medium in the framework of constituent quark model is presented. The temperature-dependent potential energy of the three quark system, taking as the internal energy of the system are obtained from the free energy of the system, and the temperature-dependent free energy is derived based on Debye-Hückel theory. The lattice QCD results of the free energy for heavy three-quark system are employed and extended to the light three-quark system. The Schrödinger equation for nucleon is solved with the help of Gaussian expansion method and the dissociation temperature of the nucleon is determined according to the temperature dependence of binding energy and radii. Comparing with the dissociation temperature of $J/ψ$, the dissociation temperature of nucleon is higher. So, nucleon is more difficult to melt than Charmonium.

hep-ph↗

arXiv2017

Discriminative Transformation Learning for Fuzzy Sparse Subspace Clustering

This paper develops a novel iterative framework for subspace clustering in a learned discriminative feature domain. This framework consists of two modules of fuzzy sparse subspace clustering and discriminative transformation learning. In the first module, fuzzy latent labels containing discriminative information and latent representations capturing the subspace structure will be simultaneously evaluated in a feature domain. Then the linear transforming operator with respect to the feature domain will be successively updated in the second module with the advantages of more discrimination, subspace structure preservation and robustness to outliers. These two modules will be alternatively carried out and both theoretical analysis and empirical evaluations will demonstrate its effectiveness and superiorities. In particular, experimental results on three benchmark databases for subspace clustering clearly illustrate that the proposed framework can achieve significant improvements than other state-of-the-art approaches in terms of clustering accuracy.

cs.CV↗

arXiv2017

Target Oriented High Resolution SAR Image Formation via Semantic Information Guided Regularizations

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

cs.CV↗