检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Ma, Zhenyu Zhang, Xin Liu, Pu Deng, Yong Hu, Wenyu Chen, Longqing Zhu, Jun Chen, Sen Wang, Zhengshang Shi, Yuechun Ma, Jian Wang, Xiaoyi Qiu, Yang Zhang, Kun Cui, Xudong Walther, Thomas Southwest Minzu University State Ethnic Affairs Commission Chengdu610041 China NCS Testing Technology Co. Ltd Chengdu610041 China Pico center SUSTech Core Research Facilities Southern University of Science and Technology Shenzhen518055 China Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China College of Physical Science and Technology Sichuan University Chengdu610064 China Laboratory for Shock Wave and Detonation Physics Institute of Fluid Physics China Academy of Engineering Physics Sichuan Mianyang621900 China Sichuan Research Center of New Materials 596 Yinhe Road Shuangliu Chengdu610200 China Yongjiang Laboratory Ningbo315000 China Institute of Chemical Materials China Academy of Engineering Physics Mianyang621900 China Dept. Electronic & Electrical Eng. University of Sheffield Mappin St. SheffieldS1 3JD United Kingdom

The investigation of chemical reactions during the ion irradiation is a frontier for the study of the ion-material interaction. In order to derive the contribution of bond formation to chemistry of ion produced nanoclusters, the valence electron energy loss spectroscopy (VEELS) was exploited to investigate the Ga+ ion damage in Al2O3, InP and InGaAs, where each target material has been shown to yield different process for altering the clustering of recoil atoms: metallic Ga, metallic In and InGaP clusters in Al2O3, InP and InGaAs *** simulations based on Monte Carlo and crystal orbital Hamiltonianindicate that the chemical constitution of cascade induced nano-precipitates is a result of a competition between interstitial/vacancy consumption rate and preferential bond formation. Copyright © 2023, The Authors. All rights reserved.

关键词： Indium phosphide

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An L₁-Norm Based Optimization Method for Sparse Redundancy Resolution of Robotic Manipulators

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IEEE Transactions on Circuits and Systems II: Express Briefs 2021年第2期69卷 469-473页

作者： Zhan Li Shuai Li School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Computer Science Department Swansea University Swansea U.K. College of Engineering Swansea University Swansea U.K.

For targeted motion control tasks of manipulators, it is frequently necessary to make use of full levels of joint actuation to guarantee successful motion planning and path tracking. Such way of motion planning and control may keep the joint actuation in a non-sparse manner during motion control process. In order to improve sparsity of joint actuation for manipulator systems, a novel motion planning scheme which can optimally and sparsely adopt joint actuation is proposed in this brief. The proposed motion planning strategy is formulated as a constrained $L_{1}$ norm optimization problem, and an equivalent enhanced optimization solution dealing with bounded joint velocity is proposed as well. A new primal dual neural network with a new solution set division is further proposed and applied to solve such bounded optimization which can sparsely adopt joint actuation for motion control. Simulation and experiment results demonstrate the efficiency, accuracy and superiority of the proposed method for optimally and sparsely adopting joint actuation. The average sparsity (i.e., - $\|\dot \theta \|_{p}$ where $\theta $ denotes the joint angle) of the joint motion of the manipulator can be increased by 39.22% and 51.30% for path tracking tasks in $X - Y$ and $X - Z$ planes respectively, indicating that the sparsity of joint actuation can be enhanced.

关键词： Optimization Manipulators Redundancy Neural networks Kinematics Planning Manipulator dynamics

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The Calculation Model for ZnO Varistor Considering Micro-characteristics

The Calculation Model for ZnO Varistor Considering Micro-cha...

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Asia-Pacific International Conference on Lightning (APL)

作者： Jingke Guo Pengfei Meng Zheng Liu Wenhao Lu Long Zhao Xiao Lei Shan Li College of Electrical Engineering Sichuan University Chengdu China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi’an China High Voltage Technology Department Extra High Voltage Power Transmission Company of CSG Guangzhou China State Grid Linyi power supply company STATE GRID Corporation of China Linyi China STATE GRID Corporation of China State Grid Sichuan Electric Power Research Institute Chengdu China

The insulation level of power system is based on the overvoltage protection level of arresters. Zinc oxide(ZnO) varistor is widely used as the core element in power arrester and surge suppressor because of its excellent nonlinear voltage-current(V-I) characteristics and high surge energy absorption capability. Electrical characteristics of ZnO varistor are determined by its complex micro-structure and grain boundary characteristics. In this study, the microstructure model of ZnO varistor is established based on Voronoi model. A large-scale nonlinear resistance network equation for solving the macroscopic electrical properties of ZnO varistors is established by using a grain boundary zoning model considering intergranular bypass effect. Aiming at that it is difficult to solve the large-scale nonlinear resistance network equation by using the conventional Newton iterative method, a fast optimization algorithm based on piecewise linearization and differential reconstruction is proposed. The error index of the calculation result is less than 10$^{-3}$ orders of magnitude. Besides, the effects of microstructure parameters, such as spinel content, nonuniformity of grain size and porosity on the electrical properties of ZnO varistors were obtained by calculation.

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Advances in artificial intelligence techniques drive the application of radiomics in the clinical research of hepatocellular carcinoma

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iLIVER 2022年第1期1卷 49-54页

作者： Jingwei Wei Meng Niu Ouyang Yabo Yu Zhou Xiaoke Ma Xue Yang Hanyu Jiang Hui Hui Hongyi Cao Binwei Duan Hongjun Li Dawei Ding Jie Tian Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Molecular Imaging Beijing 100190China Department of Interventional Radiology The First Affiliated Hospital of China Medical UniversityShenyangLiaoning110000China Beijing YouAn Hospital Capital Medical UniversityBeijing Institute of HepatologyBeijing100069China School of Life Science and Technology Xidian UniversityXi'anChina School of Computer Science and Technology Xidian UniversityXi'anShaanxiChina Department of Radiology Beijing Youan HospitalCapital Medical UniverstiyBeijing100069China Department of Radiology West China HospitalSichuan UniversityChengduSichuan 610041China Department of Pathology College of Basic Medical ScienceChina Medical UniversityShenyangLiaoning110000China The Department of General Surgery Center Beijing YouAn HospitalCapital Medical UniversityChina School of Bioengineering Beihang UniversityBeijing100191China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine Beihang UniversityBeijing100191China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi'anShaanxi710126China

Hepatocellular carcinoma(HCC)remains the most common malignancy to threaten public health *** advances in artificial intelligence techniques,radiomics for HCC management provides a novel perspective to solve unmet needs in clinical settings,and reveals pixel-level radiological information for medical imaging big data,correlating the radiological phenotype with targeted clinical *** radiomics pipelines depend on handcrafted engineering features,and further deep learning-based radiomics pipelines are supplemented with deep features calculated via self-learning *** the past decade,radiomics has been widely applied in accurate diagnoses and pathological or biological behavior evaluation,as well as in prognosis *** this review,we systematically introduce the main pipelines of artificial intelligence-based radiomics and their efficacy in the clinical studies of HCC.

关键词： Artificial intelligence Diagnosis Hepatocellular carcinoma Prognosis Radiomics

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MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework

arXiv

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arXiv 2024年

作者： Xu, Xusheng Cui, Jiangyu Cui, Zidong He, Runhong Li, Qingyu Li, Xiaowei Lin, Yanling Liu, Jiale Liu, Wuxin Lu, Jiale Luo, Maolin Lyu, Chufan Pan, Shijie Pavel, Mosharev Shu, Runqiu Tang, Jialiang Xu, Ruoqian Xu, Shu Yang, Kang Yu, Fan Zeng, Qingguo Zhao, Haiying Zheng, Qiang Zhou, Junyuan Zhou, Xu Zhu, Yikang Zou, Zuoheng Bayat, Abolfazl Cao, Xi Cui, Wei Li, Zhendong Long, Guilu Su, Zhaofeng Wang, Xiaoting Wang, Zizhu Wei, Shijie Wu, Re-Bing Zhang, Pan Yung, Man-Hong MindSpore Quantum Special Interest Group Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610051 China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing100190 China Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China School of Computer Science and Technology University of Science and Technology of China Hefei230027 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China Department of Physical Chemistry University of the Basque Country UPV/EHU Apartado 644 Bilbao48080 Spain School of Physics and Astronomy Sun Yat-sen University Zhuhai519082 China Key Laboratory of Quantum Physics and Photonic Quantum Information Ministry of Education University of Electronic Science and Technology of China Chengdu611731 China Department of Automation Tsinghua University Beijing100084 China Key Laboratory of Theoretical and Computational Photochemistry Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Beijing Academy of Quantum Information Sciences Beijing100193 China State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China CAS Key Laboratory for Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China Shenzhen International Quantum Academy Shenzhen518048 China Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China

We introduce MindSpore Quantum, a pioneering hybrid quantum-classical framework with a primary focus on the design and implementation of noisy intermediate-scale quantum (NISQ) algorithms. Leveraging the robust support of MindSpore, an advanced open-source deep learning training/inference framework, MindSpore Quantum exhibits exceptional efficiency in the design and training of variational quantum algorithms on both CPU and GPU platforms, delivering remarkable performance. Furthermore, this framework places a strong emphasis on enhancing the operational efficiency of quantum algorithms when executed on real quantum hardware. This encompasses the development of algorithms for quantum circuit compilation and qubit mapping, crucial components for achieving optimal performance on quantum processors. In addition to the core framework, we introduce QuPack-a meticulously crafted quantum computing acceleration engine. QuPack significantly accelerates the simulation speed of MindSpore Quantum, particularly in variational quantum eigensolver (VQE), quantum approximate optimization algorithm (QAOA), and tensor network simulations, providing astonishing speed. This combination of cutting-edge technologies empowers researchers and practitioners to explore the frontiers of quantum computing with unprecedented efficiency and performance. © 2024, CC BY.

关键词： Quantum computers

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A method of fiducial-value normalizing to leveling the global average atomic number of lunar surface calculated by orbital Gamma spectroscopy data

A method of fiducial-value normalizing to leveling the globa...

引用

2019 International Conference on applied Machine Learning and Data Science, ICAMLDS 2019

作者： Zhao, Jiankun Xiong, Chao Yan, Wenxun Ge, Liangquan School of Nuclear Science and Engineering East China University of Technology Nanchang330013 China College of Applied Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China Fundamental Science on Radioactive Geology and Exploration Technology Laboratory East China Institute of Technology Nanchang Jiangxi330013 China

As "banded structure" is a vexed question in orbital Gamma spectroscopy data inversion. In this paper, a new method to level the lunar global data of average atomic number by the fiducial-value in the stable composition circle is proposed. In order to verify the accuracy, the existing moon-sampling rock data as the "standard sample" and fast neutron data are also presented. The slope of the positive fit curve is 1.875 and the correlation coefficient is 0.72. And some geological characteristics, such as the structural boundaries and internal features of the Antarctic Aiken Basin, can identify obviously. © Published under licence by IOP Publishing Ltd.

关键词： Moon

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Exploring New Physics with PandaX-4T Low Energy Electronic Recoil Data

arXiv

引用

arXiv 2024年

作者： Zeng, Xinning Bo, Zihao Chen, Wei Chen, Xun Chen, Yunhua Cheng, Zhaokan Cui, Xiangyi Fan, Yingjie Fang, Deqing Gao, Zhixing Geng, Lisheng Giboni, Karl Guo, Xunan Guo, Xuyuan Guo, Zichao Han, Chencheng Han, Ke He, Changda He, Jinrong Huang, Di Huang, Houqi Huang, Junting Hou, Ruquan Hou, Yu Ji, Xiangdong Ji, Xiangpan Ju, Yonglin Li, Chenxiang Li, Jiafu Li, Mingchuan Li, Shuaijie Li, Tao Li, Zhiyuan Lin, Qing Liu, Jianglai Lu, Congcong Lu, Xiaoying Luo, Lingyin Luo, Yunyang Ma, Wenbo Ma, Yugang Mao, Yajun Meng, Yue Ning, Xuyang Pang, Binyu Qi, Ningchun Qian, Zhicheng Ren, Xiangxiang Shan, Dong Shang, Xiaofeng Shao, Xiyuan Shen, Guofang Shen, Manbin Sun, Wenliang Tao, Yi Wang, Anqing Wang, Guanbo Wang, Hao Wang, Jiamin Wang, Lei Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Xu Wang, Zhou Wu, Weihao Wu, Yuan Xiao, Mengjiao Xiao, Xiang Xiong, Kaizhi Xu, Yifan Yao, Shunyu Yan, Binbin Yan, Xiyu Yang, Yong Ye, Peihua Yu, Chunxu Yuan, Ying Yuan, Zhe Yun, Youhui Zhang, Minzhen Zhang, Peng Zhang, Shibo Zhang, Shu Zhang, Tao Zhang, Wei Zhang, Yang Zhang, Yingxin Zhang, Yuanyuan Zhao, Li Zhou, Jifang Zhou, Jiaxu Zhou, Jiayi Zhou, Ning Zhou, Xiaopeng Zhou, Yubo Zhou, Zhizhen New Cornerstone Science Laboratory Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai201210 China Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai200240 China Shanghai Jiao Tong University Sichuan Research Institute Chengdu610213 China Jinping Deep Underground Frontier Science and Dark Matter Key Laboratory of Sichuan Province China Yalong River Hydropower Development Company Ltd. 288 Shuanglin Road Chengdu610051 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai519082 China Department of Physics Yantai University Yantai264005 China Institute of Modern Physics Fudan University Shanghai200433 China School of Physics Beihang University Beijing102206 China Peng Huanwu Collaborative Center for Research and Education Beihang University Beijing100191 China International Research Center for Nuclei and Particles in the Cosmos Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing100191 China Institute of Modern Physics Chinese Academy of Sciences Huizhou516000 China SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Physics University of Maryland College ParkMD20742 United States School of Physics Nankai University Tianjin300071 China School of Physics Sun Yat-Sen University Guangzhou510275 China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei230026 China Department of Modern Physics University of Science and Technology of China Hefei230026 China Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Shandong Qingdao266237

New particles beyond the standard model of particle physics, such as axions, can be effectively searched through their interactions with electrons. We use the large liquid xenon detector PandaX-4T to search for novel electronic recoil signals induced by solar axions, neutrinos with anomalous magnetic moment, axionlike particles, dark photons, and light fermionic dark matter. A detailed background model is established using the latest datasets with 1.54 ton·yr exposure. No significant excess above the background has been observed, and we have obtained competitive constraints for axion couplings, neutrino magnetic moment, and fermionic dark matter interactions. © 2024, CC BY-NC-SA.

关键词： Magnetic moments

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Energy spectra test of glass scintillator 38

Energy spectra test of glass scintillator

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Hua, Zhehao Qian, Sen Cai, Hua Chen, Danping Du, Dejing Fan, Ruirui Han, Jifeng Hu, Peng Li, Weichang Liu, Shan Liu, Yong Ma, Lishuang Qin, Laishun Ren, Jing Sui, Zexuan Sun, Xinyuan Tang, Gao Wang, Zhile Yang, Dong Yin, Shenghua Zhang, Minghui Zhu, Yao Institute of High Energy Physics Chinese Academy of Sciences Yuquan Road 19A Beijing100049 China State Key Laboratory of Particle Detection and Electronics Yuquan Road 19A Beijing100049 China China building materials academy Guanzhuang East No.1 Beijing100024 China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Qinghe Road 390 Shanghai201800 China Neutron source Road 1 Dongguan523803 China Institute of Nuclear Science and Technology Sichuan University No. 24 Section 1 South of Ring Road 1 Chengdu610065 China Beijing Glass Research Institute East Tai Street 1 Beijing101111 China College of Materials and Chemistry China Jiliang University Xueyuan Road 258 Hangzhou310018 China College of Physics and Optoelectronic Engineering Harbin Engineering University Nantong Street 145 Harbin150001 China Department of Physics Jinggangshan University Xueyuan Road 28 Ji′an343009 China School of Astronautics Harbin Institute of Technology West Tai Chi Street 92 Harbin150001 China Nuclear Instrument CO. LTD. Hongda South Road 3 Beijing100176 China Shanghai Institute of Ceramics Chinese Academy of Sciences Heshuo Road 585 Shanghai201899 China

Hadronic calorimeter (HCAL) is an important part of the calorimeter system in Circular Electron Positron Collider (CEPC). The design of glass scintillator coupled with silicon photomultiplier (SiPM) was proposed by the Institute of High Energy Physics of Chinese Academy of Sciences. How to explore and improve the scintillation performance of the glass is the key of current research. The energy spectra of the glasses under X-ray, γ-ray, proton beam were measured. And the relationship between X-ray luminescence intensity, Gamma light yield (LY) and minimum ionizing particle (MIP) response of the glasses was investigated. The results indicate that Gamma light yield and MIP response can accurately reflect the scintillation properties of the glass scintillator. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Calorimeters

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Carbon dioxide bubble dynamics and wall heat transfer in flash chambers: Nucleation departure and cold bubble effects

引用

Annals of nuclear Energy 2025年 223卷

作者： Qifan Wang Yansong Han Ailing Fu Shanfang Huang Ruohan Zheng Yanping Huang Houjun Gong Department of Engineering Physics Tsinghua University Beijing 100086 China State Key Laboratory of Advanced Nuclear Energy Technology Nuclear Power Institute of China Chengdu 610213 China Nuclear Power Technology Innovation Center of China Nuclear Power Institute of China Chengdu 610213 China College of Finearts Chongqing Normal University Chongqing 400000 China

This study uses the lattice Boltzmann method to explore bubble dynamics and phase-change heat transfer of carbon dioxide during reduced pressure flash evaporation near overheated wall surfaces. The findings show that the bubble advancing rate decreases linearly with increasing superheat and contact angle. Similarly, the detachment diameter decreases linearly as superheat increases. The relationship between detachment diameter and contact angle is strongly influenced by wall wettability: hydrophilic surfaces exhibit a negative linear correlation, while hydrophobic surfaces show a positive linear correlation. A correction term based on the Ca number is introduced to enhance bubble rising velocity predictions. Heat transfer analysis reveals that wall wettability significantly impacts heat flux, with hydrophobic surfaces boosting heat transfer by up to three times. Mechanistically, cold nuclei induced by low-pressure conditions are crucial for improved flash evaporation heat transfer, particularly on hydrophobic surfaces.

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First Indication of Solar 8B Neutrino Flux through Coherent Elastic Neutrino-Nucleus Scattering in PandaX-4T

arXiv

引用

arXiv 2024年

作者： Bo, Zihao Chen, Wei Chen, Xun Chen, Yunhua Cheng, Zhaokan Cui, Xiangyi Fan, Yingjie Fang, Deqing Gao, Zhixing Geng, Lisheng Giboni, Karl Guo, Xunan Guo, Xuyuan Guo, Zichao Han, Chencheng Han, Ke He, Changda He, Jinrong Huang, Di Huang, Houqi Huang, Junting Hou, Ruquan Hou, Yu Ji, Xiangdong Ji, Xiangpan Ju, Yonglin Li, Chenxiang Li, Jiafu Li, Mingchuan Li, Shuaijie Li, Tao Li, Zhiyuan Lin, Qing Liu, Jianglai Lu, Congcong Lu, Xiaoying Luo, Lingyin Luo, Yunyang Ma, Wenbo Ma, Yugang Mao, Yajun Meng, Yue Ning, Xuyang Pang, Binyu Qi, Ningchun Qian, Zhicheng Ren, Xiangxiang Shan, Dong Shang, Xiaofeng Shao, Xiyuan Shen, Guofang Shen, Manbin Sun, Wenliang Tao, Yi Wang, Anqing Wang, Guanbo Wang, Hao Wang, Jiamin Wang, Lei Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Xu Wang, Zhou Wei, Yuehuan Wu, Weihao Wu, Yuan Xiao, Mengjiao Xiao, Xiang Xiong, Kaizhi Xu, Yifan Yao, Shunyu Yan, Binbin Yan, Xiyu Yang, Yong Ye, Peihua Yu, Chunxu Yuan, Ying Yuan, Zhe Yun, Youhui Zeng, Xinning Zhang, Minzhen Zhang, Peng Zhang, Shibo Zhang, Shu Zhang, Tao Zhang, Wei Zhang, Yang Zhang, Yingxin Zhang, Yuanyuan Zhao, Li Zhou, Jifang Zhou, Jiaxu Zhou, Jiayi Zhou, Ning Zhou, Xiaopeng Zhou, Yubo Zhou, Zhizhen New Cornerstone Science Laboratory Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai201210 China Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai200240 China Shanghai Jiao Tong University Sichuan Research Institute Chengdu610213 China Jinping Deep Underground Frontier Science and Dark Matter Key Laboratory of Sichuan Province China Yalong River Hydropower Development Company Ltd. 288 Shuanglin Road Chengdu610051 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai519082 China Department of Physics Yantai University Yantai264005 China Institute of Modern Physics Fudan University Shanghai200433 China School of Physics Beihang University Beijing102206 China Peng Huanwu Collaborative Center for Research and Education Beihang University Beijing100191 China International Research Center for Nuclei and Particles in the Cosmos Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing100191 China Institute of Modern Physics Chinese Academy of Sciences Huizhou516000 China SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Physics University of Maryland College ParkMD20742 United States School of Physics Nankai University Tianjin300071 China School of Physics Sun Yat-Sen University Guangzhou510275 China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei230026 China Department of Modern Physics University of Science and Technology of China Hefei230026 China Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary Science Shandong University Qingdao266237 China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao266237 China School of Phy

The PandaX-4T liquid xenon detector at the China Jinping Underground Laboratory is used to measure the solar 8B neutrino flux by detecting neutrinos through coherent scattering with xenon nuclei. Data samples requiring the coincidence of scintillation and ionization signals (paired), as well as unpaired ionization-only signals (US2), are selected with energy threshold of approximately 1.1 keV (0.33 keV) nuclear recoil energy. Combining the commissioning run and the first science run of PandaX-4T, a total exposure of 1.20 and 1.04 tonne·year are collected for the paired and US2, respectively. After unblinding, 3 and 332 events are observed with an expectation of 2.8±0.5 and 251±32 background events, for the paired and US2 data, respectively. A combined analysis yields a best-fit 8B neutrino signal of 3.5 (75) events from the paired (US2) data sample, with ∼37% uncertainty, and the background-only hypothesis is disfavored at 2.64 σ significance. This gives a solar 8B neutrino flux of (8.4 ± 3.1)×106 cm−2s−1, consistent with the standard solar model prediction. It is also the first indication of solar 8B neutrino "fog" in a dark matter direct detection experiment. © 2024, CC BY.

关键词： Coherent scattering

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