检索结果-内蒙古大学图书馆

Chinese automation Congress (CAC)

作者： Zhuangzhuang Ma Hongjian Chen Lei Shi Jinliang Shao School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu Glasgow college University of Electronic Science and Technology of China Chengdu School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

This paper investigates the containment control problem for multi-agent systems based on the broadcast gossip algorithm, in which only one agent wakes up in the light of the asynchronous time model at each time and sends its information, and one part of the remaining agents get the message to update their states while the other part keep the states unchanged. We equivalently transform the algorithm into a mathematical model with the matrix-vector form, then conduct a detailed theoretical analysis for the mathematical model by utilizing tools including graph theory and stochastic matrix. Then, we establish a necessary and sufficient algebraic graph condition to ensure that every follower gradually enters the convex hull spanned by the leaders. Finally, we give a numerical example to argument the validity of theoretical result.

关键词： Multi-agent systems Heuristic algorithms Stochastic processes Forestry STEM Graph theory Topology

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Dark Matter Search Results from the PandaX-4T Commissioning Run

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Physical Review Letters 2021年第26期127卷 261802-261802页

作者： Yue Meng Zhou Wang Yi Tao Abdusalam Abdukerim Zihao Bo Wei Chen Xun Chen Yunhua Chen Chen Cheng Yunshan Cheng Xiangyi Cui Yingjie Fan Deqing Fang Changbo Fu Mengting Fu Lisheng Geng Karl Giboni Linhui Gu Xuyuan Guo Ke Han Changda He Jinrong He Di Huang Yanlin Huang Zhou Huang Ruquan Hou Xiangdong Ji Yonglin Ju Chenxiang Li Mingchuan Li Shu Li Shuaijie Li Qing Lin Jianglai Liu Xiaoying Lu Lingyin Luo Wenbo Ma Yugang Ma Yajun Mao Nasir Shaheed Xuyang Ning Ningchun Qi Zhicheng Qian Xiangxiang Ren Changsong Shang Guofang Shen Lin Si Wenliang Sun Andi Tan Anqing Wang Meng Wang Qiuhong Wang Shaobo Wang Siguang Wang Wei Wang Xiuli Wang Mengmeng Wu Weihao Wu Jingkai Xia Mengjiao Xiao Xiang Xiao Pengwei Xie Binbin Yan Xiyu Yan Jijun Yang Yong Yang Chunxu Yu Jumin Yuan Ying Yuan Dan Zhang Minzhen Zhang Peng Zhang Tao Zhang Li Zhao Qibin Zheng Jifang Zhou Ning Zhou Xiaopeng Zhou Yong Zhou School of Physics and Astronomy Shanghai Jiao Tong University MOE Key Laboratory for Particle Astrophysics and Cosmology Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai 200240 China Shanghai Jiao Tong University Sichuan Research Institute Chengdu 610213 China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Yalong River Hydropower Development Company Limited 288 Shuanglin Road Chengdu 610051 China School of Physics Sun Yat-Sen University Guangzhou 510275 China Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary Science Shandong University Qingdao 266237 Shandong China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao 266237 Shandong China School of Physics Nankai University Tianjin 300071 China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern Physics Fudan University Shanghai 200433 China School of Physics Peking University Beijing 100871 China School of Physics Beihang University Beijing 100191 China International Research Center for Nuclei and Particles in the Cosmos and Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing 100191 China School of Medical Instrument and Food Engineering University of Shanghai for Science and Technology Shanghai 200093 China Department of Physics University of Maryland College Park Maryland 20742 USA School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei 230026 China Department of Modern Physics University of Science and Technology of China Hefei 230026 China SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai 200240 China

We report the first dark matter search results using the commissioning data from PandaX-4T. Using a time projection chamber with 3.7 tonne of liquid xenon target and an exposure of 0.63 tonne·year, 1058 candidate events are identified within an approximate nuclear recoil energy window between 5 and 100 keV. No significant excess over background is observed. Our data set a stringent limit to the dark matter–nucleon spin-independent interactions, with a lowest excluded cross section (90% C.L.) of 3.8×10−47 cm2 at a dark matter mass of 40 GeV/c2.

关键词： Particle dark matter Dark matter detectors

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An Ultrahigh-energy γ-ray Bubble Powered by a Super PeVatron

arXiv

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arXiv 2023年

作者： Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Q.W. Tang, Z.B. Tian, W.W. Wang, C. Wang, C.B. Wang, G.W. TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays [Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University 519000 Zhuhai Guangdong Guangzhou510275 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Département de Physique Nucléaire et Corpusculaire Faculté de Sciences Université de Genève 24 Quai Ernest Ansermet Geneva1211 Switzerland Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China APC Universit’e Paris Cit’e CNRS IN2P3 CEA/IRFU Observatoire de Paris Paris119 75205 France Department of Engineering Physics Tsinghua University Beijing100084 China School of Physics and Microelectronics Zhengzhou University Henan Zhengzhou450001 China Yunnan O

We report the detection of a γ-ray bubble spanning at least 100 deg2 in ultra high energy (UHE) up to a few PeV in the direction of the star-forming region Cygnus X, implying the presence Super PeVatron(s) accelerating protons to at least 10 PeV. A log-parabola form with the photon index Γ(E) = (2.71 ± 0.02) + (0.11 ± 0.02) × log10(E/10 TeV) is found fitting the gamma-ray energy spectrum of the bubble well. UHE sources, ‘hot spots’ correlated with very massive molecular clouds, and a quasi-spherical amorphous γ-ray emitter with a sharp central brightening are observed in the bubble. In the core of ∼ 0.5◦, spatially associating with a region containing massive OB association (Cygnus OB2) and a microquasar (Cygnus X-3), as well as previously reported multi-TeV sources, an enhanced concentration of UHE γ-rays are observed with 2 photons at energies above 1 PeV. The general feature of the bubble, the morphology and the energy spectrum, are reasonably reproduced by the assumption of a particle accelerator in the core, continuously injecting protons into the ambient medium. Copyright © 2023, The Authors. All rights reserved.

关键词： Gamma rays

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Erratum:A Search for Solar Axions and Anomalous Neutrino Magnetic Moment with the Complete PandaX-Ⅱ Data[***.38(2021)011301]

引用

Chinese Physics Letters 2021年第10期38卷 71-72页

作者： Xiaopeng Zhou Xinning Zeng Xuyang Ning Abdusalam Abdukerim Wei Chen Xun Chen Yunhua Chen Chen Cheng Xiangyi Cui Yingjie Fan Deqing Fang Changbo Fu Mengting Fu Lisheng Geng Karl Giboni Linhui Gu Xuyuan Guo Ke Han Changda He Di Huang Yan Huang Yanlin Huang Zhou Huang Xiangdong Ji Yonglin Ju Shuaijie Li Huaxuan Liu Jianglai Liu † Xiaoying Lu Wenbo Ma Yugang Ma Yajun Mao Yue Meng Kaixiang Ni Jinhua Ning Xiangxiang Ren Changsong Shang Guofang Shen Lin Si Andi Tan Anqing Wang Hongwei Wang Meng Wang Qiuhong Wang Siguang Wang Wei Wang Xiuli Wang Zhou Wang Mengmeng Wu Shiyong Wu Weihao Wu Jingkai Xia Mengjiao Xiao Pengwei Xie Binbin Yan Jijun Yang Yong Yang Chunxu Yu Jumin Yuan Ying Yuan Dan Zhang Tao Zhang Li Zhao Qibin Zheng Jifang Zhou Ning Zhou INPAC School of Physics and AstronomyShanghai Jiao Tong Universityand Shanghai Key Laboratory for Particle Physics and CosmologyShanghai 200240China School of Physics Beihang UniversityBeijing 100191China Shanghai Jiao Tong University Sichuan Research Institute Chengdu 610213China Yalong River Hydropower Development Company Ltd.288 Shuanglin RoadChengdu 610051China School of Physics Sun Yat-Sen UniversityGuangzhou 510275China Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghai 200240China School of Physics Nankai UniversityTianjin 300071China Key Laboratory of Nuclear Physics and Ion-Beam Application(MOE) Institute of Modern PhysicsFudan UniversityShanghai 200433China School of Physics Peking UniversityBeijing 100871China International Research Center for Nuclei and Particles in the Cosmos&Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang UniversityBeijing 100191China School of Medical Instrument and Food Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Physics University of MarylandCollege ParkMaryland 20742USA School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Physics and Key Laboratory of Particle Physics and Particle Irradiation(MOE) Shandong UniversityJinan 250100China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Center for High Energy Physics Peking UniversityBeijing 100871China

In our published letter,[1]we have identified a minor error in Figs.2 and ***,we have 2111 events in these two plots with 646,249,382,and 834 events in Run 9(20.0 ton·day),Run 10(19.4 ton·day),Run 11–1(24.2 ton·day),and Run 11–2(37.1 ton·day).The mistake is due to an incorrect application of a small energy non-linearity(known as the BLS non-linearity)in making plots,but has no impact to the final *** 2 and 3 are now updated in this note.

关键词： letter error

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Stock Time Series Prediction Based on Deep Learning

Stock Time Series Prediction Based on Deep Learning

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2019 2nd International Conference on Mechanical,Electronic and engineering technology(MEET 2019)

作者： Zou Cunzhu Luo Jiping Bai Shengyuan Wang Yuanze Zhong Changfa Cai Yi Information Science and Technology College Dalian Maritime University Navigation College Dalian Maritime University College of Marine electrical engineering Dalian Maritime University Department of Nuclear Engineering & New Energy Technology The Engineering & Technical College of Chengdu University of Technology

With the continuous development of financial markets and the gradual improvement of the financial system, people participate in financial market investment. The interest in capital is also growing, and it is accompanied by a strong demand for accurate and effective financial information services. So how to accurately predict the trend of stocks has become a focus of attention. In this paper, based on the traditional method ARIMA, the corresponding RNN(LSTM) model is proposed for the stock time series prediction problem, and its application situation is further analyzed and optimized, so that it can better explore the change law of stock data. And by setting the corresponding experimental test model method on the stock forecasting task performance. The research and evaluation of the model method demonstrates the good performance of the deep learning model and the ARIMA model in the stock time series forecasting task. The error between the stock forecasting result and the real value of each model method is at a low level. In comparison with the prediction effects of model methods such as Prophet, the RNN model proposed in this paper is closer to the real market performance, and has achieved a significantly better prediction effect than the comparison method.

关键词： RNN Time Series ARIMA Stock

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Recovery Control for Hybrid MTDC Systems with Offshore Wind Farms Supplying Weak Grids

Recovery Control for Hybrid MTDC Systems with Offshore Wind ...

引用

International Conference on High Voltage engineering and Application, ICHVE

作者： Ming Feng Carlos E. Ugalde-Loo Kuan Li Lei Zhang Bin Liu Yuancheng Yu College of Automation and Electrical Engineering Chengdu Technological University Chengdu Sichuan China School of Engineering Cardiff University Cardiff Wales United Kingdom Power System Technology Center State Grid Shandong Electric Power Research Institute Ji'nan Shandong China Guodian Dadu River Hydropower Development Co. Ltd. China Energy Investment Corporation Chengdu Sichuan China

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Multi-terminal direct-current (MTDC) grids are projected to be deployed for the large-scale grid integration of offshore wind farms. Hybrid systems simultaneously considering line commutated converter (LCC) and voltage source converter (VSC) technologies have been proposed. However, the output power fluctuation and the lack of reactive power compensation at the onshore receiving end may compromise voltage stability during the transient recovery process of the hybrid system upon faults. This paper presents a recovery control strategy for hybrid VSC-LCC systems. The system under study consists of an LCC and two VSCs and is used to transmit bulk power from a wind farm to both an isolated island and a mainland ac system. A sensitivity analysis is conducted to assess the voltage stability of the ac bus on the LCC side. A coordination recovery control strategy is designed and a simulation model is built in PSCAD/EMTDC to verify the strategy. Simulation results show that the presented strategy is effective to maintain transient voltage stability of the hybrid system and can prevent LCC communication failures.

关键词： Wind farms Inverters Power conversion Converters Voltage control Power system stability Static VAr compensators

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Reliability enhanced data processing system capable of runtime fault recovery 3

Reliability enhanced data processing system capable of runti...

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3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Shen, Beichen Peng, Libiao Xie, Yongle College of Software Engineering Sichuan University Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781538647936

In order to enhance the reliability of Big Data transmission and real-time processing in radiation environment, a reliability enhanced FPGA system with runtime fault recovery is presented in this work. This technique is proposed based on selective module redundancy and dynamic partial reconfiguration in order to improve the performance and reliability of systems implemented on SRAM-based FPGAs with fault tolerance and runtime recovery. Coarse-grained TMR architecture and fine-grained TMR architecture combining with dynamic reconfiguration are used to protect the system against soft errors caused by SEU. Fault detection units based on majority voter and XNOR gate are inserted in each redundancy module, and the built in-slice carry-chains are used to merge the large number of error flags produced by the fault detection units. The results show that the improvements in recovery time and reliability are achieved by the proposed technique. © 2018 IEEE.

关键词： Fault tolerance

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Improved limits on solar axions and bosonic dark matter from the CDEX-1B experiment using the profile likelihood ratio method

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Physical Review D 2020年第5期101卷 052003-052003页

作者： Y. Wang Q. Yue S. K. Liu K. J. Kang Y. J. Li H. P. An J. P. Chang J. H. Chen Y. H. Chen J. P. Cheng W. H. Dai Z. Deng X. P. Geng H. Gong P. Gu X. Y. Guo H. T. He L. He S. M. He J. W. Hu H. X. Huang T. C. Huang L. P. Jia H. B. Li H. Li M. X. Li J. M. Li J. Li X. Li X. Q. Li Y. L. Li B. Liao F. K. Lin S. T. Lin Y. D. Liu Y. Y. Liu Z. Z. Liu H. Ma Q. Y. Nie J. H. Ning H. Pan N. C. Qi C. K. Qiao J. Ren X. C. Ruan V. Sharma Z. She L. Singh M. K. Singh T. X. Sun C. J. Tang W. Y. Tang Y. Tian G. F. Wang L. Wang Q. Wang Z. Wang H. T. Wong S. Y. Wu Y. C. Wu H. Y. Xing Y. Xu T. Xue Y. L. Yan L. T. Yang N. Yi C. X. Yu H. J. Yu J. F. Yue X. H. Zeng M. Zeng Z. Zeng B. T. Zhang F. S. Zhang L. Zhang Z. Y. Zhang M. G. Zhao J. F. Zhou Z. Y. Zhou J. J. Zhu Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics Tsinghua University Beijing 100084 Department of Physics Tsinghua University Beijing 100084 College of Physics Sichuan University Chengdu 610064 NUCTECH Company Beijing 100084 Institute of Physics Academia Sinica Taipei 11529 YaLong River Hydropower Development Company Chengdu 610051 Department of Nuclear Physics China Institute of Atomic Energy Beijing 102413 Sino-French Institute of Nuclear and Technology Sun Yat-sen University Zhuhai 519082 School of Physics Nankai University Tianjin 300071 College of Nuclear Science and Technology Beijing Normal University Beijing 100875 Department of Physics Banaras Hindu University Varanasi 221005 Department of Physics Beijing Normal University Beijing 100875

We present the improved constraints on couplings of solar axions and more generic bosonic dark matter particles using 737.1 kg days of data from the CDEX-1B experiment. The CDEX-1B experiment, located at the China Jinping Underground Laboratory, primarily aims at the direct detection of weakly interacting massive particles using a p-type point-contact germanium detector. We adopt the profile likelihood ratio method for analysis of data in the presence of backgrounds. An energy threshold of 160 eV was achieved, much better than the 475 eV of CDEX-1A with an exposure of 335.6 kg days. This significantly improves the sensitivity for the bosonic dark matter below 0.8 keV among germanium detectors. Limits are also placed on the coupling gAe<2.48×10−11 from Compton, bremsstrahlung, atomic-recombination, and deexcitation channels and gANeff×gAe<4.14×10−17 from a Fe57 M1 transition at 90% confidence level.

关键词： Particle astrophysics Particle dark matter

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Direct Detection Constraints on Dark Photons with the CDEX-10 Experiment at the China Jinping Underground Laboratory

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Physical Review Letters 2020年第11期124卷 111301-111301页

作者： Z. She L. P. Jia Q. Yue H. Ma K. J. Kang Y. J. Li M. Agartioglu H. P. An J. P. Chang J. H. Chen Y. H. Chen J. P. Cheng W. H. Dai Z. Deng X. P. Geng H. Gong P. Gu Q. J. Guo X. Y. Guo L. He S. M. He H. T. He J. W. Hu T. C. Huang H. X. Huang H. B. Li H. Li J. M. Li J. Li M. X. Li X. Li X. Q. Li Y. L. Li B. Liao F. K. Lin S. T. Lin S. K. Liu Y. D. Liu Y. Y. Liu Z. Z. Liu Y. C. Mao Q. Y. Nie J. H. Ning H. Pan N. C. Qi C. K. Qiao J. Ren X. C. Ruan B. Sevda C. S. Shang V. Sharma L. Singh M. K. Singh T. X. Sun C. J. Tang W. Y. Tang Y. Tian G. F. Wang L. Wang Q. Wang Y. Wang Y. X. Wang Z. Wang H. T. Wong S. Y. Wu H. Y. Xing Y. Xu T. Xue Y. L. Yan L. T. Yang N. Yi C. X. Yu H. J. Yu J. F. Yue M. Zeng Z. Zeng B. T. Zhang L. Zhang F. S. Zhang Z. Y. Zhang M. G. Zhao J. F. Zhou Z. Y. Zhou J. J. Zhu Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics Tsinghua University Beijing 100084 Institute of Physics Academia Sinica Taipei 11529 Department of Physics Dokuz Eylül University İzmir 35160 Department of Physics Tsinghua University Beijing 100084 NUCTECH Company Beijing 100084 YaLong River Hydropower Development Company Chengdu 610051 College of Nuclear Science and Technology Beijing Normal University Beijing 100875 College of Physics Sichuan University Chengdu 610064 School of Physics Peking University Beijing 100871 Sino-French Institute of Nuclear and Technology Sun Yat-sen University Zhuhai 519082 Department of Nuclear Physics China Institute of Atomic Energy Beijing 102413 School of Physics Nankai University Tianjin 300071 Department of Physics Banaras Hindu University Varanasi 221005 Department of Physics Beijing Normal University Beijing 100875

We report constraints on the dark photon effective kinetic mixing parameter (κ) with data taken from two p-type point-contact germanium detectors of the CDEX-10 experiment at the China Jinping Underground Laboratory. The 90% confidence level upper limits on κ of solar dark photon from 205.4 kg-day exposure are derived, probing new parameter space with masses (mV) from 10 to 300 eV/c2 in direct detection experiments. Considering dark photon as the cosmological dark matter, limits at 90% confidence level with mV from 0.1 to 4.0 keV/c2 are set from 449.6 kg-day data, with a minimum of κ=1.3×10−15 at mV=200 eV/c2.

关键词： Cosmic ray & astroparticle detectors Particle astrophysics Particle dark matter Hypothetical gauge bosons

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Research and Analysis of Power Supply Load Forecasting and Self-Healing Control in Urban Rail Transit System

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IOP Conference Series: Earth and Environmental Science 2021年第4期769卷

作者： Jiangchun Yu Junyi Wang Fei Tong School of Electrical and Automation Engineering East China Jiaotong University Nanchang Jiangxi 330000 College of Mechanical and Electrical Engineering Northeast Forestry University Harbin Heilongjiang 150036 School of Management Science Chengdu University of Technology Chengdu Sichuan 646000

With the continuous expansion of urban scale and the continuous increase of population, the pressure of urban traffic is increasing, so it is necessary to improve urban rail transit and better promote urban development and construction. At this stage, urban rail transit as an important tool of urban public transport, with fast, energy-saving and other advantages, so it has become an important part of urban infrastructure. Stable power system is the basis to ensure the stable operation of urban rail transit. However, traction power supply and electric power technology are needed to provide technical support in the operation of urban rail transit. This paper analyzes the content of this aspect and has a certain understanding of the relevant technology through the analysis of the article. Urge the relevant staff to conduct in-depth research, in order to obtain more advanced technology. With the gradual improvement of the reliability and advanced nature of the power grid, the self-healing ability has become the core function of the advanced power grid system in the future. This paper analyzes and compares the research status and technical characteristics of self-healing technology of distribution network system and rail transit power supply system, and points out the deficiency of self-healing of rail transit power supply system at present; by combing the fault scenarios and self-healing requirements of rail transit power supply system, this paper preliminarily analyzes the realization method of self-healing system, and puts forward an overall architecture of self-healing system. This paper first explains the causes of urban rail transit power system faults, then explains the fault types of urban rail transit power system, and finally explains the ways to deal with the faults of urban rail transit power system. With the continuous acceleration of urban modernization in China, urban rail transit has become the main force of urban transportation, providing people with mor

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