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arXiv 2023年

作者： Zhang, Cheng Yang, Jinshan Yan, Zhongbo Yuan, Xiang Liu, Yanwen Zhao, Minhao Suslov, Alexey Zhang, Jinglei Pi, Li Wang, Zhong Xiu, Faxian Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Shanghai Qi Zhi Institute Shanghai200232 China State Key Laboratory of Surface Physics Department of Physics Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai200050 China School of Physics Sun Yat-Sen University Guangzhou510275 China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai200062 China National High Magnetic Field Laboratory TallahasseeFL32310 United States Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory of the Chinese Academy of Sciences Hefei230031 China Institute for Advanced Study Tsinghua University Beijing100084 China Collaborative Innovation Center of Quantum Matter Beijing100871 China Shanghai Research Center for Quantum Sciences Shanghai201315 China

The interplay of electron correlations and topological phases gives rise to various exotic phenomena including fractionalization, excitonic instability, and axionic excitation. Recently-discovered transition-metal pentatellurides can reach the ultra-quantum limit in low magnetic fields and serve as good candidates for achieving such a combination. Here, we report evidences of density wave and metal-insulator transition in HfTe5 induced by intense magnetic fields. Using the nonlinear transport technique, we detect a distinct nonlinear conduction behavior in the longitudinal resistivity within the a-c plane, corresponding to the formation of a density wave induced by magnetic fields. In high fields, the onset of the nonlinear conduction in the Hall resistivity indicates an impurity-pinned magnetic freeze-out as the possible origin of the insulating behavior. These frozen electrons can be gradually re-activated into mobile states above a threshold electric field. These experimental evidences call for further investigations into the underlying mechanism for the bulk quantum Hall effect and field-induced phase transtions in pentatellurides. © 2023, CC BY.

关键词： Quantum chemistry

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The Dual Role of Interlayer Crosslinks Leads to an Abnormal Behavior of Interlayer Thermal Resistance in Multilayer Graphene

SSRN

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SSRN 2022年

作者： Chen, Yan Wan, Jing Chen, Yang Qin, Huasong Liu, Yilun Pei, Qing-Xiang Zhang, Yong-Wei Laboratory for Multiscale Mechanics and Medical Science SV LAB School of Aerospace Xi'an Jiaotong University Xi'An710049 China School of Mechanics and Safety Engineering Zhengzhou University Zhengzhou450001 China Shanghai Institute of Applied Mathematics and Mechanics Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai University Shanghai200072 China Institute of High Performance Computing A*STAR Singapore138632 Singapore State Key Laboratory for Strength and Vibration of Mechanical Structures China

Understanding and controlling the interlayer thermal resistance (ITR) are crucial to the cross-plane thermal transport in multilayer graphene (MLG). Using non-equilibrium molecular dynamics simulations, we show that the ITR of MLG can be effectively tuned by in-plane defects, sp 2 and sp 3 C-C bond crosslinks. Specifically, with the increase of the in-plane defect density, the ITR initially increases sharply and then almost saturates;while with the increase of the crosslink density, the ITR initially also increases sharply, then peaks and subsequently decreases rapidly to a level that can be even lower than that of pristine MLG. The underlying mechanism for this unexpected variation of ITR with crosslink density is explored through the analyses of the phonon density of states (DOS) and spectral transmission function. It was found that the crosslinks play a dual role: the crosslink-generated in-plane defect enhances phonon scattering and leads to an increase in the ITR, while the interlayer bonding gives rise to a fast phonon transmission pathway and decreases the ITR. An effective medium approximation (EMA) model was proposed to describe the dual role of the crosslinks. This work provides new insight into the thermal transport behavior of crosslinks, which is useful for modulating the cross-plane thermal transport of MLG for the thermal management of MLG-based nanodevices. © 2022, The Authors. All rights reserved.

关键词： Molecular dynamics

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ASYMPTOTIC PRESERVING AND UNIFORMLY UNCONDITIONALLY STABLE FINITE DIFFERENCE SCHEMES FOR KINETIC TRANSPORT EQUATIONS

arXiv

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arXiv 2022年

作者： Zhang, Guoliang Zhu, Hongqiang Xiong, Tao Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China School of Natural Sciences Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Fujian Xiamen361005 China

In this paper, uniformly unconditionally stable first and second order finite difference schemes are developed for kinetic transport equations in the diffusive scaling. We first derive an approximate evolution equation for the macroscopic density, from the formal solution of the distribution function, which is then discretized by following characteristics for the transport part with a backward finite difference semi-Lagrangian approach, while the diffusive part is discretized implicitly. After the macroscopic density is available, the distribution function can be efficiently solved even with a fully implicit time discretization, since all discrete velocities are decoupled, resulting in a low-dimensional linear system from spatial discretizations at each discrete velocity. Both first and second order discretizations in space and in time are considered. The resulting schemes can be shown to be asymptotic preserving (AP) in the diffusive limit. Uniformly unconditional stabilities are verified from a Fourier analysis based on eigenvalues of corresponding amplification matrices. Numerical experiments, including high dimensional problems, have demonstrated the corresponding orders of accuracy both in space and in time, uniform stability, AP property, and good performances of our proposed approach. © 2022, CC BY.

关键词： Distribution functions

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Efficient Pyramid Channel Attention Network for Pathological Myopia Recognition

arXiv

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arXiv 2023年

作者： Zhang, Xiaoqing Zhao, Jilu Li, Yan Wu, Hao Zhou, Xiangtian Liu, Jiang Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China National Clinical Research Center for Ocular Diseases Eye Hospital Wenzhou Medical University Wenzhou325027 China State Key Laboratory of Ophthalmology Optometry and Visual Science Eye Hospital Wenzhou Medical University Wenzhou325027 China Research Unit of Myopia Basic Research and Clinical Prevention and Control Chinese Academy of Medical Sciences Wenzhou325027 China Singapore Eye Research Institute 169856 Singapore

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristic of pathology distribution in PM is global-local on the fundus image, which plays a significant role in assisting clinicians in diagnosing PM. However, most existing deep neural networks focused on designing complex architectures but rarely explored the pathology distribution prior of PM. To tackle this issue, we propose an efficient pyramid channel attention (EPCA) module, which fully leverages the potential of the clinical pathology prior of PM with pyramid pooling and multi-scale context fusion. Then, we construct EPCA-Net for automatic PM recognition based on fundus images by stacking a sequence of EPCA modules. Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters. In addition, we construct a PM recognition benchmark termed PM-fundus by collecting fundus images of PM from publicly available datasets. The comprehensive experiments demonstrate the superiority of EPCA-Net over state-of-the-art methods in the PM recognition task. For example, EPCA-Net achieves 97.56% accuracy and outperforms ViT by 2.85% accuracy on the PM-fundus dataset. The results also show that our method based on the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of previous methods based on traditional fine-tuning paradigm with fewer tunable parameters, which has the potential to leverage more natural image foundation models to address the PM recognition task in limited medical data regime. Copyright © 2023, The Authors. All rights reserved.

关键词： Pathology

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Dynamic Prefix-Tuning for Generative Template-based Event Extraction

arXiv

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arXiv 2022年

作者： Liu, Xiao Huang, Heyan Shi, Ge Wang, Bo School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Key Laboratory of Intelligent Information Processing and Information Security Ministry of Industry and Information Technology China Southeast Academy of Information Technology Beijing Institute of Technology China Faculty of Information Technology Beijing University of Technology China

We consider event extraction in a generative manner with template-based conditional generation. Although there is a rising trend of casting the task of event extraction as a sequence generation problem with prompts, these generation-based methods have two significant challenges, including using suboptimal prompts and static event type information. In this paper, we propose a generative template-based event extraction method with dynamic prefix (GTEE-DYNPREF) by integrating context information with type-specific prefixes to learn a context-specific prefix for each context. Experimental results show that our model achieves competitive results with the state-of-the-art classification-based model ONEIE on ACE 2005 and achieves the best performances on ERE. Additionally, our model is proven to be portable to new types of events effectively. Copyright © 2022, The Authors. All rights reserved.

关键词： Extraction

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Nonlocal Cahn-Hilliard Type Model for Image Inpainting

SSRN

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SSRN 2023年

作者： Jiang, Dandan Azaiez, Mejdi Miranville, Alain Xu, Chuanju School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen University Xiamen361005 China University of Bordeaux France Laboratoire de Mathématiques et Applications Université de Poitiers Site du Futuroscope - Téléport 2 11 Boulevard Marie et Pierre Curie - Bâtiment H3 - TSA 61125 Poitiers86073 France

This paper proposes a Cahn-Hilliard type inpainting model equipped with a nonlocal diffusion operator. A rigorous analysis of the well-posedness of the stationary solution is established using Schauder’s fixed point theory. We construct a numerical scheme based on the convexity splitting method with the nonlocal term treated implicitly and the fidelity term treated explicitly. We prove the consistency, stability and convergence of the scheme. To the best of our knowledge, this is the first study to present such an analysis and numerical scheme for this model, which provides valuable guidance for parameter selection. Numerical experiments validate the effectiveness of the proposed nonlocal model, which shows superior performance compared to both local and classical total variation models in preserving fine textures and recovering image edges. © 2023, The Authors. All rights reserved.

关键词： Textures

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Specificity-Preserving Federated Learning for MR Image Reconstruction

arXiv

引用

arXiv 2021年

作者： Feng, Chun-Mei Yan, Yunlu Wang, Shanshan Xu, Yong Shao, Ling Fu, Huazhu The Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen518055 China The Institute of High Performance Computing A*STAR Singapore138632 Singapore Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology CAS Shenzhen518055 China Terminus Group China

Federated learning (FL) can be used to improve data privacy and efficiency in magnetic resonance (MR) image reconstruction by enabling multiple institutions to collaborate without needing to aggregate local data. However, the domain shift caused by different MR imaging protocols can substantially degrade the performance of FL models. Recent FL techniques tend to solve this by enhancing the generalization of the global model, but they ignore the domain-specific features, which may contain important information about the device properties and be useful for local reconstruction. In this paper, we propose a specificity-preserving FL algorithm for MR image reconstruction (FedMRI). The core idea is to divide the MR reconstruction model into two parts: a globally shared encoder to obtain a generalized representation at the global level, and a client-specific decoder to preserve the domain-specific properties of each client, which is important for collaborative reconstruction when the clients have unique distribution. Such scheme is then executed in the frequency space and the image space respectively, allowing exploration of generalized representation and client-specific properties simultaneously in different spaces. Moreover, to further boost the convergence of the globally shared encoder when a domain shift is present, a weighted contrastive regularization is introduced to directly correct any deviation between the client and server during optimization. Extensive experiments demonstrate that our FedMRI’s reconstructed results are the closest to the ground-truth for multi-institutional data, and that it outperforms state-of-the-art FL methods. © 2021, CC BY.

关键词： Image reconstruction

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Absence of metallicity and bias-dependent resistivity in low-carrier-density EuCd2As2

arXiv

引用

arXiv 2023年

作者： Wang, Yuxiang Ma, Jianwen Yuan, Jian Wu, Wenbin Zhang, Yong Mou, Yicheng Gu, Jiaming Cheng, Peihong Shi, Wu Yuan, Xiang Zhang, Jinglei Guo, Yanfeng Zhang, Cheng State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China School of Physical Science and Technology ShanghaiTech University Shanghai201210 China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai200241 China Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory of the Chinese Academy of Sciences Hefei230031 China School of Physics and Electronic Science East China Normal University Shanghai200241 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China ShanghaiTech Laboratory for Topological Physics Shanghai201210 China

EuCd2As2 was theoretically predicted to be a minimal model of Weyl semimetals with a single pair of Weyl points in the ferromagnet state. However, the heavily p-doped EuCd2As2 crystals in previous experiments prevent direct identification of the semimetal hypothesis. Here we present a comprehensive magneto-transport study of high-quality EuCd2As2 crystals with ultralow bulk carrier density (1013 cm-3). In contrast to the general expectation of a Weyl semimetal phase, EuCd2As2 shows insulating behavior in both antiferromagnetic and ferromagnetic states as well as surface-dominated conduction from band bending. Moreover, the application of a dc bias current can dramatically modulate the resistance by over one order of magnitude, and induce a periodic resistance oscillation due to the geometric resonance. Such nonlinear transport results from the highly nonequilibrium state induced by electrical field near the band edge. Our results suggest an insulating phase in EuCd2As2 and put a strong constraint on the underlying mechanism of anomalous transport properties in this system. © 2023, CC BY.

关键词： Quantum chemistry

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Self-torqued harmonics and attosecond pulses driven by time-delayed relativistic vortex lasers

引用

Physical Review A 2022年第3期106卷 033515-033515页

作者： Jingwei Wang Matt Zepf Yuxin Leng Ruxin Li Sergey G. Rykovanov State Key Laboratory of High Field Laser Physics and Chinese Academy of Sciences Center for Excellence in Ultra-Intense Laser Science Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China China-Russian Belt and Road Joint Laboratory on Laser Science Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 07743 Jena Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena 07743 Jena Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow 121205 Russia

Light carrying time-varying orbital angular momentum (OAM) is a recently discovered type of structured electromagnetic field compared with a typical vortex field whose OAM is static. Such so-called self-torqued light is employed for manipulating the fast magnetic, topological, and quantum excitations and increasing its intensity and having access to shorter pulse durations would be of great benefit. Here we theoretically and numerically demonstrate the generation of intense self-torqued harmonics and attosecond pulses in the relativistic regime, driven by two time-delayed relativistic vortex lasers with different OAMs l1 and l2. The OAM of the nth harmonic spans nl1 to nl2, and the OAM of the attosecond pulses changes from l1 to l2. Such intense self-torqued harmonics and attosecond pulses may offer alternative possibilities in ultrafast spectroscopy.

关键词： high intensity laser-plasma interactions high-energy-density plasmas Radiation & particle generation in plasmas Ultrafast phenomena Relativistic plasmas Particle-in-cell methods Relativistic hydrodynamics

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Styx: A Data-Oriented Mutation Framework to Improve the Robustness of DNN

Styx: A Data-Oriented Mutation Framework to Improve the Robu...

引用

IEEE International Conference on Automated Software Engineering (ASE)

作者： Meixi Liu Weijiang Hong Weiyu Pan Chendong Feng Zhenbang Chen Ji Wang College of Computer National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (数字)9781450367684

ISBN: (纸本)9781728172811

The robustness of deep neural network (DNN) is critical and challenging to ensure. In this paper, we propose a general data-oriented mutation framework, called Styx, to improve the robustness of DNN. Styx generates new training data by slightly mutating the training data. In this way, Styx ensures the DNN's accuracy on the test dataset while improving the adaptability to small perturbations, i.e., improving the robustness. We have instantiated Styx for image classification and proposed pixel-level mutation rules that are applicable to any image classification DNNs. We have applied Styx on several commonly used benchmarks and compared Styx with the representative adversarial training methods. The preliminary experimental results indicate the effectiveness of Styx.

关键词： Training Perturbation methods Neural networks Training data Robustness Image classification Software engineering

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