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arXiv 2021年

作者： Yu, Lisu Liu, Zilong Wen, Miaowen Cai, Donghong Dang, Shuping Wang, Yuhao Xiao, Pei School of Information Engineering Nanchang University Nanchang330031 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China School of Computer Science and Electronics Engineering University of Essex ColchesterCO4 3SQ United Kingdom School of Electronic and Information Engineering South China University of Technology Guangzhou510640 China College of Cyber Security Jinan University Guangzhou510632 China Thuwal23955-6900 Saudi Arabia Institute for Communication Systems 5G Innovation Centre University of Surrey GuildfordGU2 7XH United Kingdom

As 5G networks rolling out in many different countries nowadays, the time has come to investigate how to upgrade and expand them towards 6G, where the latter is expected to realize the interconnection of everything as well as the development of a ubiquitous intelligent mobile world for intelligent life. To enable this epic leap in communications, this article provides an overview and outlook on the application of sparse code multiple access (SCMA) for 6G wireless communication systems, which is an emerging disruptive non-orthogonal multiple access (NOMA) scheme for the enabling of massive connectivity. We propose to apply SCMA to a massively distributed access system (MDAS), whose architecture is based on fiber-based visible light communication (FVLC), ultra-dense network (UDN), and NOMA. Under this framework, we consider the interactions between optical front-hauls and wireless access links. In order to stimulate more upcoming research in this area, we outline a number of promising directions associated with SCMA for faster, more reliable, and more efficient multiple access in future 6G communication networks. © 2021, CC BY-NC-ND.

关键词： Visible light communication

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Self-calibration of LHAASO-KM2A electromagnetic particle detectors using single particles within extensive air showers

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Physical Review D 2022年第12期106卷 122004-122004页

作者： F. Aharonian Q. An Axikegu L. X. Bai Y. X. Bai Y. W. Bao D. Bastieri X. J. Bi Y. J. Bi J. T. Cai Z. Cao J. Chang J. F. Chang E. S. Chen L. Chen M. J. Chen M. L. Chen Q. H. Chen S. H. Chen S. Z. Chen T. L. Chen Y. Chen H. L. Cheng N. Cheng Y. D. Cheng S. W. Cui X. H. Cui Y. D. Cui B. D’Ettorre Piazzoli B. Z. Dai H. L. Dai Z. G. Dai Danzengluobu D. della Volpe K. K. Duan J. H. Fan Y. Z. Fan Z. X. Fan J. Fang K. Fang C. F. Feng L. Feng S. H. Feng X. T. Feng Y. L. Feng B. Gao C. D. Gao L. Q. Gao Q. Gao W. Gao W. K. Gao M. M. Ge L. S. Geng G. H. Gong Q. B. Gou M. H. Gu F. L. Guo J. G. Guo X. L. Guo Y. Q. Guo Y. Y. Guo Y. A. Han H. H. He H. N. He S. L. He X. B. He Y. He M. Heller Y. K. Hor C. Hou X. Hou H. B. Hu Q. Hu S. Hu S. C. Hu X. J. Hu D. H. Huang W. H. Huang X. T. Huang X. Y. Huang Y. Huang Z. C. Huang X. L. Ji H. Y. Jia K. Jia K. Jiang Z. J. Jiang M. Jin M. M. Kang T. Ke D. Kuleshov K. Levochkin B. B. Li C. Li F. Li H. B. Li H. C. Li H. Y. Li J. Li K. Li W. L. Li X. R. Li X. Li Y. Z. Li Z. Li E. W. Liang Y. F. Liang S. J. Lin B. Liu C. Liu D. Liu H. Liu H. D. Liu J. Liu J. L. Liu J. S. Liu J. Y. Liu M. Y. Liu R. Y. Liu S. M. Liu W. Liu Y. Liu Y. N. Liu W. J. Long R. Lu Q. Luo H. K. Lv B. Q. Ma L. L. Ma X. H. Ma J. R. Mao A. Masood Z. Min W. Mitthumsiri Y. C. Nan Z. W. Ou B. Y. Pang P. Pattarakijwanich Z. Y. Pei M. Y. Qi Y. Q. Qi B. Q. Qiao J. J. Qin D. Ruffolo A. Sáiz C. Y. Shao L. Shao O. Shchegolev X. D. Sheng J. Y. Shi H. C. Song Yu. V. Stenkin V. Stepanov Y. Su Q. N. Sun X. N. Sun Z. B. Sun P. H. T. Tam Z. B. Tang W. W. Tian B. D. Wang C. Wang H. Wang H. G. Wang J. C. Wang J. S. Wang L. P. Wang L. Y. Wang R. Wang R. N. Wang W. Wang X. G. Wang X. Y. Wang Y. Wang Y. D. Wang Y. J. Wang Y. P. Wang Z. H. Wang Z. X. Wang Z. Wang D. M. Wei J. J. Wei Y. J. Wei T. Wen C. Y. Wu H. R. Wu S. Wu X. F. Wu Y. S. Wu S. Q. Xi J. Xia J. J. Xia G. M. Xiang D. X. Xiao G. Xiao G. G. Xin Y. L. Xin Y. Xing Z. Xiong D. L. Xu R. X. Xu L. Xue D. H. Yan J. Z. Yan C. W. Yang F. F. Yang H. W. Yang J. Y. Yang L. L. Yang M. J. Yang R. Z. Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China 230026 Hefei Anhui China School of Physical Science and Technology & School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China College of Physics Sichuan University 610065 Chengdu Sichuan China Key Laboratory of Particle Astrophyics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China TIANFU Cosmic Ray Research Center 610299 Chengdu Sichuan China School of Astronomy and Space Science Nanjing University 210023 Nanjing Jiangsu China Center for Astrophysics Guangzhou University 510006 Guangzhou Guangdong China University of Chinese Academy of Sciences 100049 Beijing China Key Laboratory of Dark Matter and Space Astronomy & Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences 210023 Nanjing Jiangsu China Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education 850000 Lhasa Tibet China National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China Hebei Normal University 050024 Shijiazhuang Hebei China School of Physics and Astronomy (Zhuhai) & School of Physics (Guangzhou) & Sino-French Institute of Nuclear Engineering and Technology (Zhuhai) Sun Yat-sen University 519000 Zhuhai & 510275 Guangzhou Guangdong China Dipartimento di Fisica dell’Università di Napoli “Federico II” Complesso Universitario di Monte Sant’Angelo via Cinthia 80126 Napoli Italy School of Physics and Astronomy Yunnan University 650091 Kunming Yunnan China Département de Physique Nucléaire et Corpusculaire Faculté de Sciences Université de Genève 24 Quai Ernest Ansermet 1211 Geneva Switzerland Institute of Frontier and Inte

In the Large high Altitude Air Shower Observatory (LHAASO), the square kilometer array, with 5249 electromagnetic particle detectors (EDs) and 1188 muon detectors, is deployed to explore the gamma-ray sources above 30 TeV with unprecedented sensitivity and to measure primary cosmic rays in the energy range from 10 TeV to 100 PeV. The energetic particles produced by extensive air showers can serve as a continuously available source for calibration of the numerous EDs over a large area. In this study, the detector untriggered probability is first proposed to estimate the particle density at different distances from the shower core and distinguish the characteristic single-particle signal detected by each ED. This method uses science data directly, and does not require prior knowledge of the cosmic-ray elemental composition or hadronic interaction model. Experimental results show that this self-calibration can be used to determine the number of particles detected by each ED with an accuracy better than 2% within a time scale of hours, which is adequate to meet the physics requirements of the LHAASO experiment. With this high efficiency and accuracy, this calibration also provides an ideal method to monitor the detector performance throughout an expected lifetime of >10 years.

关键词： Cosmic rays & astroparticles Astrophysical & cosmological simulations Cosmic ray & astroparticle detectors Monte Carlo methods Probability theory Scintillators

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Quick and Accurate False Data Detection in Mobile Crowd Sensing

Quick and Accurate False Data Detection in Mobile Crowd Sens...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Kun Xie Xiaocan Li Xin Wang Gaogang Xie Dongliang Xie Zhenyu Li Jigang Wen Zulong Diao College of Computer Science and Electronics Engineering Hunan University Changsha China Department of Electrical and Computer Engineering State University of New York at Stony Brook State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences State key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

With the proliferation of smartphones, a novel sensing paradigm called Mobile Crowd Sensing (MCS) has emerged very recently. However, the attacks and faults in MCS cause a serious false data problem. Observing the intrinsic low dimensionality of general monitoring data and the sparsity of false data, false data detection can be performed based on the separation of normal data and anomalies. Although the existing separation algorithm based on Direct Robust Matrix Factorization (DRMF) is proven to be effective, requiring iteratively performing Singular Value Decomposition (SVD) for low-rank matrix approximation would result in a prohibitively high accumulated computation cost when the data matrix is large. In this work, we observe the quick false data location feature from our empirical study of DRMF, based on which we propose an intelligent Light weight Low Rank and False Matrix Separation algorithm (LightLRFMS) that can reuse the previous result of the matrix decomposition to deduce the one for the current iteration step. Our algorithm can largely speed up the whole iteration process. From a theoretical perspective, we validate that LightLRFMS only requires one round of SVD computation and thus has very low computation cost. We have done extensive experiments using a PM 2.5 air condition trace and a road traffic trace. Our results demonstrate that LightLRFMS can achieve very good false data detection performance with the same highest detection accuracy as DRMF but with up to 10 times faster speed thanks to its lower computation cost.

关键词： Sparse matrices Sensors Matrix decomposition Monitoring Matrix converters Roads Wireless sensor networks

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Search for the rare decays W^(+)→D_(s)^(+)γ and Z→D^(0)γ at LHCb

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Chinese Physics C 2023年第9期47卷 14-26页

作者： R.Aaij A.S.W.Abdelmotteleb C.Abellan Beteta F.Abudinén T.Ackernley B.Adeva M.Adinolfi P.Adlarson H.Afsharnia C.Agapopoulou C.A.Aidala Z.Ajaltouni S.Akar K.Akiba J.Albrecht F.Alessio M.Alexander A.Alfonso Albero Z.Aliouche P.Alvarez Cartelle R.Amalric S.Amato J.L.Amey Y.Amhis L.An L.Anderlini M.Andersson A.Andreianov M.Andreotti D.Andreou D.Ao F.Archilli A.Artamonov M.Artuso E.Aslanides M.Atzeni B.Audurier S.Bachmann M.Bachmayer J.J.Back A.Bailly-reyre P.Baladron Rodriguez V.Balagura W.Baldini J.Baptista de Souza Leite M.Barbetti R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi B.Batsukh A.Battig A.Bay A.Beck M.Becker F.Bedeschi I.B.Bediaga A.Beiter V.Belavin S.Belin V.Bellee K.Belous I.Belov I.Belyaev G.Benane G.Bencivenni E.Ben-Haim A.Berezhnoy *** *** Andres D.Berninghoff H.C.Bernstein C.Bertella A.Bertolin C.Betancourt F.Betti Ia.Bezshyiko S.Bhasin J.Bhom L.Bian M.S.Bieker N.V.Biesuz S.Bifani P.Billoir A.Biolchini M.Birch F.C.R.Bishop A.Bitadze A.Bizzeti M.P.Blago T.Blake F.Blanc J.E.Blank S.Blusk D.Bobulska J.A.Boelhauve O.Boente Garcia T.Boettcher A.Boldyrev C.S.Bolognani R.Bolzonella N.Bondar F.Borgato S.Borghi M.Borsato J.T.Borsuk S.A.Bouchiba T.J.V.Bowcock A.Boyer C.Bozzi M.J.Bradley S.Braun A.Brea Rodriguez J.Brodzicka A.Brossa Gonzalo J.Brown D.Brundu A.Buonaura L.Buonincontri A.T.Burke C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calefice S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Campana D.H.Campora Perez A.F.Campoverde Quezada S.Capelli L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini P.Carniti L.Carus A.Casais Vidal R.Caspary G.Casse M.Cattaneo G.Cavallero V.Cavallini S.Celani J.Cerasoli D.Cervenkov A.J.Chadwick M.G.Chapman M.Charles Ph.Charpentier C.A.Chavez Barajas M.Chefdeville C.Chen S.Chen A.Chernov S.Chernyshenko V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin V.Chulikov P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek G.Ciullo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cognera Centro Brasileiro de Pesquisas Físicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina Institute Of High Energy Physics(IHEP) BeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University of Chinese Academy of Sciences BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Université Savoie Mont Blanc CNRSIN2P3-LAPPAnnecyFrance UniversitéClermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance UniversitéParis-Saclay CNRS/IN2P3IJCLabOrsayFrance Laboratoire Leprince-Ringuet CNRS/IN2P3Ecole PolytechniqueInstitut Polytechnique de ParisPalaiseauFrance LPNHE Sorbonne UniversitéParis Diderot Sorbonne Paris CitéCNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultat Physik Technische Universitat DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universitat HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Cagliari MonserratoItaly Universitàdegli Studi di Padova Universitàe INFNPadovaPadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma La Sapienza RomaItaly INFN Sezione di Roma Tor Vergata RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands AGH-University of Science and Technology Faculty of Physics and Applied Computer Scienc

A search for the rare decays W^(+)→D_(s)^(+)γ and Z→D0γis performed using proton-proton collision data collected by the LHCb experiment at a centre-of-mass energy of 13TeV,corresponding to an integrated luminosity of 2.0fb−*** significant signal is observed for either decay mode and upper limits on their branching fractions are set using W^(+)→D_(s)^(+)γ and Z→μ+μ−decays as normalization *** upper limits are 6.5×10^(−4) and 2.1×10^(−3) at 95% confidence level for the W^(+)→D_(s)^(+)γ and Z→D^(0)γ decay modes,*** is the first reported search for the Z→D^(0)γ decay,while the upper limit on the W+→D+sγbranching fraction improves upon the previous best limit.

关键词： W/Z boson rare decay upper limit of branching fraction

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Bayesian Inference analysis of jet quenching using inclusive jet and hadron suppression measurements

arXiv

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arXiv 2024年

作者： Ehlers, R. Chen, Y. Mulligan, J. Ji, Y. Kumar, A. Mak, S. Jacobs, P.M. Majumder, A. Angerami, A. Arora, R. Bass, S.A. Datta, R. Du, L. Elfner, H. Fries, R.J. Gale, C. He, Y. Jacak, B.V. Jeon, S. Jonas, F. Kasper, L. Kordell II, M. Kunnawalkam-Elayavalli, R. Latessa, J. Lee, Y.-J. Lemmon, R. Luzum, M. Mankolli, A. Martin, C. Mehryar, H. Mengel, T. Nattrass, C. Norman, J. Parker, C. Paquet, J.-F. Putschke, J.H. Roch, H. Roland, G. Schenke, B. Schwiebert, L. Sengupta, A. Shen, C. Singh, M. Sirimanna, C. Soeder, D. Soltz, R.A. Soudi, I. Tachibana, Y. Velkovska, J. Vujanovic, G. Wang, X.-N. Wu, X. Zhao, W. Department of Physics University of California BerkeleyCA94270 United States Nuclear Science Division Lawrence Berkeley National Laboratory BerkeleyCA94270 United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics and Astronomy Vanderbilt University NashvilleTN37235 United States Department of Statistical Science Duke University DurhamNC27708 United States Department of Physics University of Regina ReginaSKS4S 0A2 Canada Department of Physics McGill University MontréalQCH3A 2T8 Canada Department of Physics and Astronomy Wayne State University DetroitMI48201 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Computer Science Wayne State University DetroitMI48202 United States Department of Physics Duke University DurhamNC27708 United States GSI Helmholtzzentrum für Schwerionenforschung Darmstadt64291 Germany Institute for Theoretical Physics Goethe University Frankfurt am Main60438 Germany Frankfurt Institute for Advanced Studies Frankfurt am Main60438 Germany Cyclotron Institute Texas A&M University College StationTX77843 United States Department of Physics and Astronomy Texas A&M University College StationTX77843 United States Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China Daresbury Laboratory Warrington Cheshire DaresburyWA44AD United Kingdom Instituto de Fisica Universidade de São Paulo C.P. 66318 SP São Paulo05315-970 Brazil Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Oliver Lodge Laboratory University of Liverpool

The Jetscape Collaboration reports a new determination of the jet transport parameter q in the Quark-Gluon Plasma (QGP) using Bayesian Inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at RHIC and the LHC. This multiobservable analysis extends the previously published Jetscape Bayesian Inference determination of q, which was based solely on a selection of inclusive hadron suppression data. Jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly-coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of q utilizes Active Learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data;on jet or hadron data separately;and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation. © 2024, CC BY.

关键词： Heavy ions

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RE4CPS: Requirements Engineering for Cyber-Physical Systems

RE4CPS: Requirements Engineering for Cyber-Physical Systems

引用

IEEE International Conference on Requirements Engineering

作者： Zhi Jin Xiaohong Chen Zhi Li Yijun Yu Key Laboratory of High Confidence Software Technologies (MoE) Peking University China Shanghai Key Laboratory of Trustworthy Computing East China Normal University China College of Computer Science and Information Technology Guangxi Normal University China School of Computing and Communications The Open University UK

Cyber-Physical Systems (CPSs) connect the cyber world with the physical world through a network of interrelated elements, such as sensors and actuators, robots, and other computing devices. There are increasing number of beneficial applications in dependable sectors such as aviation, transportation, aerospace, healthcare, etc.. The inherent characteristics of CPSs pose a number of challenges to requirements engineering. Unlike normal information systems, CPSs need to continuously detect and adapt to the environment changes. The interactive environment becomes the first-class citizen because the features and the changing patterns in environment are must-to-be considered. Moreover, in such systems, many non-functional requirements are environment related, like timing, safety, security, and privacy requirements. This tutorial will introduce an environment modelling based approach to engineering the requirements of CPSs. Extending the Problem Frames representations, this approach structures the model of the environmental elements and provides analysis methods for deriving and specifying requirements. We deliver this tutorial with a few supporting tools that assist the modelling and verification of the system specification, demonstrated with working examples in sufficient details. After the tutorial, participants will be able to work on the environment modelling requirements engineering for their own projects, with some hands-on experience and a good knowledge of some tool support.

关键词： Requirements engineering Tutorials Tools Software Security Timing Privacy

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Variable 2-Microlocal Besov–Triebel–Lizorkin-Type Spaces

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Acta Mathematica Sinica,English Series 2018年第4期34卷 699-748页

作者： Su Qing WU Da Chun YANG Wen YUAN Ci Qiang ZHUO Laboratory of Mathematics and Complex Systerns (Ministry of Education) School of Mathematical Sciences Beijing Normal University Beijing 100875 P. R. China Key Laboratory of High Performance Computing and Stochastic Information Processing ( HPCSIP) (Ministry of Education of China) College of Mathematics and Computer Science Hu'nan Normal University Changsha 410081 P. R. China

This article is devoted to the study of variable 2-microlocal Besov-type and Triebel- Lizorkin-type spaces. These variable function spaces are defined via a Fourier-analytical approach. The authors then characterize these spaces by means of Q-transforms, Peetre maximal functions, smooth atoms, ball means of differences and approximations by analytic functions. As applications, some re- lated Sobolev-type embeddings and trace theorems of these spaces are Mso established. Moreover, some obtained results, such as characterizations via approximations by analytic functions, are new even for the classical variable Besov and Triebel-Lizorkin spaces.

关键词： 2-Microlocal Besov space 2-Microlocal Triebel-Lizorkin space variable exponent φ-transform Peetre maximal function difference atom embedding

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Search for the doubly heavy baryon Ξ_(bc)^(+)→ decaying to J/ψΞ_(c)^(+)

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Chinese Physics C 2023年第9期47卷 1-13页

作者： R.Aaij A.S.W.Abdelmotteleb C.Abellan Beteta F.Abudinén T.Ackernley B.Adeva M.Adinolfi H.Afsharnia C.Agapopoulou C.A.Aidala S.Aiola Z.Ajaltouni S.Akar K.Akiba J.Albrecht F.Alessio M.Alexander A.Alfonso Albero Z.Aliouche P.Alvarez Cartelle S.Amato J.L.Amey Y.Amhis L.An L.Anderlini M.Andersson A.Andreianov M.Andreotti D.Andreou D.Ao F.Archilli A.Artamonov M.Artuso E.Aslanides M.Atzeni B.Audurier S.Bachmann M.Bachmayer J.J.Back A.Bailly-reyre P.Baladron Rodriguez V.Balagura W.Baldini J.Baptista de Souza Leite M.Barbetti R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi B.Batsukh A.Battig A.Bay A.Beck M.Becker F.Bedeschi I.B.Bediaga A.Beiter V.Belavin S.Belin V.Bellee K.Belous I.Belov I.Belyaev G.Bencivenni E.Ben-Haim A.Berezhnoy *** D.Berninghoff H.C.Bernstein C.Bertella A.Bertolin C.Betancourt F.Betti Ia.Bezshyiko S.Bhasin J.Bhom L.Bian M.S.Bieker N.V.Biesuz S.Bifani P.Billoir A.Biolchini M.Birch F.C.R.Bishop A.Bitadze A.Bizzeti M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska J.A.Boelhauve O.Boente Garcia T.Boettcher A.Boldyrev N.Bondar S.Borghi M.Borsato J.T.Borsuk S.A.Bouchiba T.J.V.Bowcock A.Boyer C.Bozzi M.J.Bradley S.Braun A.Brea Rodriguez J.Brodzicka A.Brossa Gonzalo D.Brundu A.Buonaura L.Buonincontri A.T.Burke C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calefice S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes P.Campana D.H.Campora Perez A.F.Campoverde Quezada S.Capelli L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Carniti L.Carus A.Casais Vidal R.Caspary G.Casse M.Cattaneo G.Cavallero V.Cavallini S.Celani J.Cerasoli D.Cervenkov A.J.Chadwick M.G.Chapman M.Charles Ph.Charpentier C.A.Chavez Barajas M.Chefdeville C.Chen S.Chen A.Chernov S.Chernyshenko V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin V.Chulikov P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek G.Ciullo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo L.Congedo A.Contu N.Cooke Centro Brasileiro de Pesquisas Físicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina Institute Of High Energy Physics(IHEP) BeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University of Chinese Academy of Sciences BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Université Savoie Mont Blanc CNRSIN2P3-LAPPAnnecyFrance UniversitéClermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance UniversitéParis-Saclay CNRS/IN2P3IJCLabOrsayFrance Laboratoire Leprince-Ringuet CNRS/IN2P3Ecole PolytechniqueInstitut Polytechnique de ParisPalaiseauFrance LPNHE Sorbonne UniversitéParis Diderot Sorbonne Paris CitéCNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultät Physik Technische Universität DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universität HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Cagliari MonserratoItaly Universitàdegli Studi di Padova Universitàe INFNPadovaPadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma La Sapienza RomaItaly INFN Sezione di Roma Tor Vergata RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands AGH-University of Science and Technology Faculty of Physics and Applied Computer Scienc

A first search for the Ξ_(bc)^(+)J/ψΞ_(c)^(+) decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9 fb−1 recorded at centre-of-mass energies of 7, 8, and 13 TeV. Two peaking structures are seen with a local (global) significance of 4.3(2.8) and 4.1(2.4) standard deviations at masses of 6571 and 6694 MeV/c2, respectively. Upper limits are set on the Ξ+bc baryon production cross-section times the branching fraction relative to that of the B+c→J/ψD+s decay at centre-of-mass energies of 8 and 13 TeV, in the Ξ+bc and in the B+c rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to 20GeV/c, respectively. Upper limits are presented as a function of the Ξ+bc mass and lifetime.

关键词： QCD B physics charm physics spectroscopy

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Efficient parallel linear scaling method to get the response density matrix in all-electron real-space density-functional perturbation theory

arXiv

引用

arXiv 2020年

作者： Shang, Honghui Liang, Wanzhen Zhang, Yunquan Yang, Jinlong State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Physical Chemistry of Solid Surfaces Collaborative Innovation Center of Chemistry for Energy Materials Fujian Provincial KeyLaboratory of Theoretical and Computational Chemistry Department of Chemistry College of Chemistry and Chemical Engineering Xiamen University XiamenFujian361005 China Hefei National Laboratory for Physical Sciences at Microscale Department of Chemical Physics Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui230026 China

The real-space density-functional perturbation theory (DFPT) for the computations of the response properties with respect to the atomic displacement and homogeneous electric field perturbation has been recently developed and implemented into the all-electron, numeric atom-centered orbitals electronic structure package FHI-aims. It is found that the bottleneck for large scale applications is the computation of the response density matrix, which scales as O(N3). Here for the response properties with respect to the homogeneous electric field, we present an efficient parallel linear scaling algorithm for the response density matrix calculation. Our scheme is based on the second-order trace-correcting purification and the parallel sparse matrix-matrix multiplication algorithms. The new scheme reduces the formal scaling from O(N3) to O(N), and shows good parallel scalability over tens of thousands of cores. As demonstrated by extensive validation, we achieve a rapid computation of accurate polarizabilities using DFPT. Finally, the computational efficiency of this scheme has been illustrated by making the scaling tests and scalability tests on massively parallel computer systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Matrix algebra

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