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Quark transverse spin-momentum correlation of the pion from lattice QCD: The Boer-Mulders function

Physical Review D 2025年第9期111卷 094507-094507页

作者： Lisa Walter Jun Hua Sebastian Lahrtz Lingquan Ma Andreas Schäfer Hai-Tao Shu Yushan Su Peng Sun Wei Wang Xiaonu Xiong Yi-Bo Yang Jian-Hui Zhang Qi-An Zhang Institut für Theoretische Physik Universität Regensburg D-93040 Regensburg Germany Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou 510006 People’s Republic of China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 People’s Republic of China Center of Advanced Quantum Studies Department of Physics Beijing Normal University Beijing 100875 People’s Republic of China School of Science and Engineering The Chinese University of Hong Kong Shenzhen 518172 People’s Republic of China Key Laboratory of Quark & Lepton Physics (MOE) and Institute of Particle Physics Central China Normal University Wuhan 430079 People’s Republic of China Department of Physics University of Maryland College Park Maryland 20742 USA Institute of Modern Physics Chinese Academy of Sciences Lanzhou Gansu Province 730000 People’s Republic of China INPAC Key Laboratory for Particle Astrophysics and Cosmology (MOE) Shanghai Key Laboratory for Particle Physics and Cosmology School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 People’s Republic of China Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences Huizhou 516000 Guangdong Province People’s Republic of China School of Physics Central South University Changsha 418003 People’s Republic of China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing 100190 People’s Republic of China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou 310024 People’s Republic of China International Centre for Theoretical Physics Asia-Pacific Beijing/Hangzhou People’s Republic of China University of Chinese Academy of Sciences School of Physical Sciences Beijing 100049 People’s Republic of China School of Physi

We present the first lattice QCD calculation of the quark transverse spin-momentum correlation, i.e., the T-odd Boer-Mulders function of the pion, using large-momentum effective theory. The calculation is done at three lattice spacings a={0.098,0.085,0.064} fm and pion masses ∼350 MeV, with pion momenta up to 1.8 GeV. The matrix elements are renormalized in a state-of-the-art scheme and extrapolated to the continuum and infinite momentum limit. We have implemented the perturbative matching up to the next-to-next-to-leading order and carried out a renormalization-group resummation. Our results provide valuable input for phenomenological analyses of the Boer-Mulders single-spin asymmetry.

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Biological data processing based on bio-processor unit(BPU), a new concept for next generation computational biology

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Science China(Life Sciences) 2018年第5期61卷 597-598页

作者： Di Liu Dongbo Bu Tieliu Shi Jianxiao Quan Depeng Wang Yongyong Shi Xiao-Chen Bo Wenbao Han Computational Virology Group Wuhan Institute of Virology Chinese Academy of Sciences Wuhan 430071 China Key Laboratory of InteUigent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Center for Bioinformatics and Computational Biology and the Institute of Biomedical Sciences School of Life Sciences East China Normal University Shanghai 200214 China State Key Laboratory of Mathematical Engineering and Advanced Computation Wuxi 214122 China Jiangsu Variable Supercomputer Tech Co Ltd. Wuxi 214125 China NextOmics Blosctences Wuhan 430074 China Bio-X Institutes Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) Shanghai Jiao Tong University Shanghai 200030 China Beijing Institute of Radiation Medicine Beifing 100850 China

The revolution of biotechnology has pushed forward life sciences into the Big Data ***,high-throughput bio-techniques have greatly accelerated the integration of biology,computing and informatics,and hence substantially pushed forward the development of bioinformatics and computational *** to the latest report of data deposition within National Centre for Biotechnology Information（NCBI）,the genome sequencing projects have increased 49.94%.

关键词：计算生物学简历处理器数据基信息科学生物信息学生命科学 NCBI

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Intelligent identification of two-dimensional nanostructures by machine-learning optical microscopy

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Nano Research 2018年第12期11卷 6316-6324页

作者： Xiaoyang Lin Zhizhong Si Wenzhi Fu Jianlei Yang Side Guo Yuan Cao Jin Zhang Xinhe Wang Peng Liu Kaili Jiang Weisheng Zhao Fert Beijing Research Institute School ofMicroelectronics & Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC)Beihang UniversityBeijing 100191China Beihang-GoertekJoint Microelectronics Institute Qingdao Research InstituteBeihang UniversityQingdao 266000China Fert Beijing Research Institute School of Computer Science and Engineering & Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC)Beihang UniversityBeijing 100191China State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics & Tsinghua-Foxconn Nanotechnology Research CenterCollaborative Innovation Center of Quantum MatterTsinghua UniversityBeijing 100084China

Two-dimensional (2D) materials and their heterostructures, with wafer-scale synthesis methods and fascinating properties, have attracted significant interest and triggered revolutions in corresponding device applications. However, facile methods to realize accurate, intelligent, and large-area characterizations of these 2D nanostructures are still highly desired. Herein, we report the successful application of machine-learning strategy in the optical identification of 2D nanostructures. The machine-learning optical identification (MOI) method endows optical microscopy with intelligent insight into the characteristic color information of 2D nanostructures in the optical photograph. The experimental results indicate that the MOI method enables accurate, intelligent, and large-area characterizations of graphene, molybdenum disulfide, and their heterostructures, including identifications of the thickness, existence of impurities, and even stacking order. With the convergence of artificial intelligence and nanoscience, this intelligent identification method can certainly promote fundamental research and wafer-scale device applications of 2D nanostructures.

关键词： machine-learning optical identification two-dimensional (2D) material heterostructure artificial intelligence

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Simulation of Passenger Evacuation of High-speed Train Cars

Simulation of Passenger Evacuation of High-speed Train Cars

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Fire Science and Fire Protection engineering (ICFSFPE), Conference on

作者： Shenshi Huang Ruichao Wei Kai Shi Jinxing Hu Shouxiang Lu Liping Lian Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Science Shenzhen China Institute of Advanced Materials Science and Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Science Shenzhen China The Smart City Research Institute of China Electronics Technology Group Corporation Shenzhen China State Key Laboratory of Fire Science University of Science and Technology of China Hefei China School of Urban Planning and Design Peking University Shenzhen China

ISBN: (数字)9781728153223

ISBN: (纸本)9781728153230

This study is to evaluate the passenger evacuation of the high-speed train. Geometry was built up based on current Chinese train type CRH380B, and scenarios were designed according to the current emergency response plans. Simulation runs were performed by Pathfinder and uncertainty of evacuation time was obtained. It is observed that the passenger flow rates in train coaches are generally stable. Passenger transfer time and evacuation time are approximately proportional to passenger attendance rate. However, in some complicated scenarios, it is found that the process of passenger transfer affects the evacuation results a lot. Reasonable passenger transfer scale can maximize the effectiveness of emergency plans. This study provides an evaluation method on the topic of train car evacuation, and future work can be carried out to optimize the design of emergency response.

关键词： passenger evacuation high-speed train monteCarlo simulation high-speed train Evacuation passengers Evacuation Time evaluation method Educational attendance simulating Cars

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Mimic Defense Structured Information System Threat Identification and Centralized Control

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Journal of Physics: Conference Series 2019年第3期1187卷

作者： Bo Zhang Weichao Li Xin Sun Yufeng Zhao State Grid Key Laboratory of Information & Network Security Nanjing China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China State Grid Zhejiang Electric Power Research Institute Hangzhou China

With the speeding up of the informatization process of our national economy and social development, the degree of informatization in our country is getting higher and higher. Information system has become the key infrastructure of our country. The security of these basic information networks and important information systems has been seriously related to national security and social stability, to the collective interests of enterprises, and to the vital interests of the broad masses of the people. Increasing application in improving work efficiency and economic benefits at the same time, the increasingly com-plex information system has also brought greater challenges to operation and maintenance managers. The use of known or unknown vulnerabilities, causing damage to information systems, stealing sensitive information, endangering the normal operation of business systems and other behaviors, has become one of the main causes of various security incidents. How to effectively deal with the vulnerability threat and various vulnerability problems of enterprise information systems, concentrate on the implementation of information security vulnerability warning related risks, and provide solutions to related vulnerability threats, have become an urgent problem to be solved. Therefore, we construct the mimic structured enterprise information system by establishing the threat identification system through unified management to form a comprehensive and secure cyber threat management system.

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Mobile APP user attribute prediction by heterogeneous information network modeling

arXiv

引用

arXiv 2019年

作者： Zhang, Hekai Gong, Jibing Teng, Zhiyong Wang, Dan Wang, Hongfei Du, Linfeng Bhuiyan, Zakirul Alam School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Lab for Computer Virtual Technology and System Integration Yanshan University Qinhuangdao066004 China School of Computer Science and Engineering Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214000 China Department of Computer and Information Sciences Fordham University

User-based attribute information, such as age and gender, is usually considered as user privacy information. It is difficult for enterprises to obtain user-based privacy attribute information. However, user-based privacy attribute information has a wide range of applications in personalized services, user behavior analysis and other aspects. Although many scholars have made achievements in user attribute prediction and other related fields, there are still two main problems that impede further improvement on the accuracy of classification: (1) Traditional machine learning classification merely takes each object as a single individual, ignoring the relationship between them;(2) At present, the popular Heterogeneous Path-Mine Information Network only considers whether the user has a relationship with the attributes of other nodes, rather than the degree of correlation of the attributes. It employs a linear regression model to fit the weight of meta-path, which is highly sensitive to outliers. To solve the above two problems, this paper advances the HetPathMine model and puts forward TPathMine model. With applying the number of clicks of attributes under each node to express the user's emotional preference information, optimizations of the solution of meta-path weight are also presented. Based on meta-path in heterogeneous information networks, the new model integrates all relationships among objects into isomorphic relationships of classified objects. Matrix is used to realize the knowledge dissemination of category knowledge among isomorphic objects. The experimental results show that: (1) the prediction of user attributes based on heterogeneous information networks can achieve higher accuracy than traditional machine learning classification methods;(2) TPathMine model based on the number of clicks is more accurate in classifying users of different age groups, and the weight of each meta-path is consistent with human intuition or the real world situation. Copyright ©

关键词： Forecasting

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P2P Network Based on Neighbor-neighbor Lists

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Journal of Physics: Conference Series 2019年第3期1168卷

作者： Hao Zhao Chenyang Wang Yuefei Zhu Wei Lin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan 450001 China Information Engineering University Information Technology Section Zhengzhou Henan 450001 China

In order to solve the vulnerability of the network structure in the real world, this paper constructs a P2P network model based on neighbor-neighbor lists. We propose two algorithms, network repairing and pruning, to improve the effectiveness and robustness of the network. Simulation experiments show that the proposed model and algorithms can effectively enhance the self-healing of P2P network.

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Network Embedding based on External Word Vectors

Network Embedding based on External Word Vectors

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IEEE International Performance computing and Communications Conference

作者： XiaoKun Zhang Yan Liu Jing Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781538668092;9781538668085

Network embedding, which preserves network's sophisticated features, aims to effectively learn the low-dimensional embedding of vertices to lower the computing and storage costs. Content information network like Twitter is defined as network with rich text information. Most research about content information network are based on the information of the network itself. By introducing external word vectors into the modeling process, we can make use of the external syntactic and semantic features. In this paper, we propose NE-EWV (Network Embedding based on External Word Vectors), which preserves the feature fusion representation from both semantic feature space as well as structural feature space. Experiments are conducted in three real-world content information network datasets. In link predict task, the AUC increases 7% to 19% compared with the models which only considering the structural features, increases 1% to 12% compared with the model considering structural and text features in most cases.

关键词： Network embedding Content information network Auto-encoder External word vectors

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Sparse representation of gaussian molecular surface

arXiv

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arXiv 2019年

作者： Gui, Sheng Chen, Minxin Lu, Benzhuo STATE KEY LABORATORY of SCIENTIFIC and ENGINEERING COMPUTING NATIONAL CENTER for MATHEMATICS and INTERDISCIPLINARY SCIENCES ACADEMY of MATHEMATICS and SYSTEMS SCIENCE CHINESE ACADEMY of SCIENCES BEIJING100190 China SCHOOL of MATHEMATICAL SCIENCES UNIVERSITY of CHINESE ACADEMY of SCIENCES BEIJING100049 China DEPARTMENT of MATHEMATICS SOOCHOW UNIVERSITY SUZHOU215006 China

In this paper, we propose a model and algorithm for sparse representing Gaussian molecular surface. The original Gaussian molecular surface is approximated by a relatively small number of radial basis functions (RBFs) with rotational ellipsoid feature. The sparsity of the RBF representation is achieved by solving a nonlinear L1optimization problem. Experimental results demonstrate that the original Gaussian molecular surface is able to be represented with good accuracy by much fewer RBFs using our L1model and algorithm. The sparse representation of Gaussian molecular surface is useful in various applications, such as molecular structure alignment, calculating molecular areas and volumes, and the method in principle can be applied to sparse representation of general shapes and coarse-grained molecular modeling. Copyright © 2019, The Authors. All rights reserved.

关键词： Radial basis function networks

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Photocurrent imaging of multi-memristive charge density wave switching in two-dimensional 1T-TaS2

arXiv

引用

arXiv 2020年

作者： Patel, Tarun Okamoto, Junichi Dekker, Tina Yang, Bowen Gao, Jingjing Luo, Xuan Lu, Wenjian Sun, Yuping Tsen, Adam W. Institute for Quantum Computing Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics University of Freiburg FreiburgD-79104 Germany Key Laboratory of Materials Physics Institute of Solid State Physics Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing210093 China

Transport studies of atomically thin 1T-TaS2 have demonstrated the presence of intermediate resistance states across the nearly commensurate (NC) to commensurate (C) charge density wave (CDW) transition, which can be further switched electrically. While this presents exciting opportunities for the material in memristor applications, the switching mechanism has remained elusive and could be potentially attributed to the formation of inhomogeneous C and NC domains across the 1T-TaS2 flake. Here, we present simultaneous electrical driving and scanning photocurrent imaging of CDWs in ultrathin 1T-TaS2 using a vertical heterostructure geometry. While micron-sized CDW domains form upon changing temperature, electrically driven transitions result in largely uniform changes, indicating that states of intermediate resistance for the latter likely correspond to true metastable CDW states in between the NC and C phases, which we then explain by a free energy analysis. Additionally, we are able to perform repeatable and bidirectional switching across the multiple CDW states without changing sample temperature, demonstrating that atomically thin 1T-TaS2 can be further used as a robust and reversible multi-memristor material. Copyright © 2020, The Authors. All rights reserved.

关键词： Memristors

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