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Deep view of composite SNR CTA1 with LHAASO in γ-rays up to 300 TeV

Science China(Physics,Mechanics & Astronomy) 2025年

作者： Zhen Cao F.Aharonian Axikegu Y.X.bai Y.w.bao D.bastieri X.J.bi Y.J.bi w.bian A.V.bukevich Q.Cao w.Y.Cao Zhe Cao J.Chang J.F.Chang A.M.Chen E.S.Chen H.X.Chen Liang Chen Lin Chen Long Chen M.J.Chen M.L.Chen Q.H.Chen S.Chen S.H.Chen S.Z.Chen T.L.Chen Y.Chen N.Cheng Y.D.Cheng M.C.Chu M.Y.Cui S.w.Cui X.H.Cui Y.D.Cui b.Z.Dai H.L.Dai Z.G.Dai Danzengluobu X.Q.Dong K.K.Duan J.H.Fan Y.Z.Fan J.Fang J.H.Fang K.Fang C.F.Feng H.Feng L.Feng S.H.Feng X.T.Feng Y.Feng Y.L.Feng S.Gabici b.Gao C.D.Gao Q.Gao w.Gao w.K.Gao M.M.Ge T.T.Ge L.S.Geng G.Giacinti G.H.Gong Q.b.Gou M.H.Gu F.L.Guo J.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han O.A.Hannuksela M.Hasan H.H.He H.N.He J.Y.He Y.He Y.K.Hor b.w.hou C.hou X.hou H.b.Hu Q.Hu S.C.Hu C.Huang D.H.Huang T.Q.Huang w.J.Huang X.T.Huang X.Y.Huang Y.Huang Y.Y.Huang X.L.Ji H.Y.Jia K.Jia H.b.Jiang K.Jiang X.w.Jiang Z.J.Jiang M.Jin M.M.Kang I.Karpikov D.Khangulyan D.Kuleshov K.Kurinov b.b.Li C.M.Li Cheng Li Cong Li D.Li F.Li H.b.Li H.C.Li Jian Li Jie Li K.Li S.D.Li w.L.Li w.L.Li X.R.Li Xin Li Y.Z.Li Zhe Li Zhuo Li E.w.Liang Y.F.Liang S.J.Lin b.Liu C.Liu D.Liu D.b.Liu H.Liu H.D.Liu J.Liu J.L.Liu M.Y.Liu R.Y.Liu S.M.Liu w.Liu Y.Liu Y.N.Liu Q.Luo Y.Luo H.K.Lv b.Q.Ma L.L.Ma X.H.Ma J.R.Mao Z.Min w.Mitthumsiri H.J.Mu Y.C.Nan A.Neronov K.C.Y.Ng L.J.Ou P.Pattarakijwanich Z.Y.Pei J.C.Qi M.Y.Qi b.Q.Qiao J.J.Qin A.Raza D.Ruffolo A.Sáiz M.Saeed D.Semikoz L.Shao O.Shchegolev X.D.Sheng F.w.Shu H.C.Song Yu.V.Stenkin V.Stepanov Y.Su D.X.Sun Q.N.Sun X.N.Sun Z.b.Sun J.Takata P.H.T.Tam Q.w.Tang R.Tang Z.b.Tang w.w.Tian L.H.wan C.wang C.b.wang G.w.wang H.G.wang H.H.wang J.C.wang Kai wang Kai wang L.P.wang L.Y.wang P.H.wang R.wang w.wang X.G.wang X.Y.wang Y.wang Y.D.wang Y.J.wang Z.H.wang Z.X.wang Zhen wang Zheng wang D.M.wei J.J.wei Y.J.wei T.wen C.Y.wu H.R.wu Q.w.wu S.wu X.F.wu Y.S.wu S.Q.Xi J.Xia G.M.Xiang D.X.Xiao G.Xiao Y.L.Xin Y.Xing D.R.Xiong Z.Xiong D.L.Xu R.F.Xu R.X.Xu w.L.Xu L.Xue D.H.Yan J.Z.Yan T.Yan C.w.Yang C.Y.Yang F.Yang F.F.Yang L.L.Yang M.J.Yang R.Z.Yang w.X.Yang Y.H.Yao Z.G.Yao L.Q.Yin N.Yin X.H.You Z.Y.You Y.H Southwest Jiaotong University School of Astronomy and Space Science Nanjing University Center for Astrophysics Guangzhou University Tsung-Dao Lee Institute & School of Physics and Astronomy Shanghai Jiao Tong University Institute for Nuclear Research of Russian Academy of Sciences Hebei Normal University University of Science and Technology of China LHAASO Collaboration State Key Laboratory of Particle Detection and Electronics Key Laboratory of Dark Matter and Space Astronomy & Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Research Center for Astronomical Computing Zhejiang Laboratory Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Yunnan University Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education Department of Physics The Chinese University of Hong Kong Key Laboratory of Radio Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences School of Physics and Astronomy (Zhuhai) & School of Physics (Guangzhou) & Sino-French Institute of Nuclear Engineering and Technology (Zhuhai) Sun Yat-sen University Institute of High Energy Physics Institute of Frontier and Interdisciplinary Science Shandong University APC Université Paris Cité CNRS/IN2P3 CEA/IRFU Observatoire de Paris Department of Engineering Physics & Department of Astronomy Tsinghua University School of Physics and Microelectronics Chinese Academy of Sciences Zhengzhou University Yunnan Observatories Chinese Academy of Sciences China Center of Advanced Science and Technology College of Physics Sichuan University School of Physics Peking University Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and Technology University of Chinese Academy of Sciences Guangxi University Department of Physics Faculty of Science Mahidol University Moscow Institute

The ultra-high-energy（UHE） gamma-ray source 1LHAASO J0007+7303u is positionally associated with the composite SNR CTA1 that is located at high Galactic Latitude b ≈ 10.5°. This provides a rare opportunity to spatially resolve the component of the pulsar wind nebula（PwN） and supernova remnant（SNR） at UHE. This paper conducted a dedicated data analysis of 1LHAASO J0007+7303u using the data collected from December 2019 to July 2023. This source is well detected with significances of 21σ and 17σ at 8-100 TeV and >100 TeV, respectively. The corresponding extensions are determined to be 0.23°±0.03°and 0.17°±0.03°. The emission is proposed to originate from the relativistic electrons accelerated within the PwN of PSR J0007+7303. The energy spectrum is well described by a power-law with an exponential cutoff function dN/dE =（42.4 ± 4.1）(E/（20 TeV）)-2.31±0.11exp(-E/（110±25 TeV）) TeV-1cm-2s-1in the energy range from 8 to 300 TeV, implying a steady-state parent electron spectrum dNe/dEe∝(Ee/（100 TeV）)-3.13±0.16exp[(-Ee/（373±70 TeV）)2] at energies above ≈ 50 TeV. The cutoff energy of the electron spectrum is roughly equal to the expected current maximum energy of particles accelerated at the PwN terminal shock. Combining the X-ray and gamma-ray emission, the current space-averaged magnetic field can be limited to≈ 4.5 μG. To satisfy the multi-wavelength spectrum and the γ-ray extensions, the transport of relativistic particles within the PwN is likely dominated by the advection process under the free-expansion phase assumption.

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LHAASO detection of very-high-energy γ-ray emission surrounding PSR J0248+6021

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Science China(Physics,Mechanics & Astronomy) 2025年

we report the detection of an extended very-high-energy(VHE) γ-ray source coincident with the location of middle-aged(62.4 kyr) pulsar PSR J0248+6021, by using the LHAASO-wCDA data of live 796 d and LHAASO-KM2A data of live 1216d. A significant excess of γ-ray induced showers is observed both by wCDA in energy bands of 1-25 Te V and KM2A in energy bands of >25 TeV with 7.3σ and 13.5σ, respectively. The best-fit position derived through wCDA data is R.A. = 42.06°± 0.12°and Dec. = 60.24°± 0.13°with an extension of 0.69°±0.15°and that of the KM2A data is R.A.= 42.29°± 0.13°and Dec. =60.38°± 0.07°with an extension of 0.37°±0.07°. No clear extended multiwavelength counterpart of this LHAASO source has been found from the radio band to the GeV band. The most plausible explanation of the VHE γ-ray emission is the inverse Compton process of highly relativistic electrons and positrons injected by the pulsar. These electrons/positrons are hypothesized to be either confined within the pulsar wind nebula or to have already escaped into the interstellar medium, forming a pulsar halo.

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Observation of the γ-ray emission from w43 with LHAASO

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Science China(Physics,Mechanics & Astronomy) 2025年

In this paper, we report the detection of the very-high-energy (VHE, 100 Ge V100 TeV) γ-ray emissions from the direction of the young star-forming region w43, observed by the Large High Altitude Air Shower Observation (LHAASO). The extended γ-ray source was detected with a significance of～16σby KM2A and～17σby wCDA, respectively. The angular extension of this γ-ray source is about 0.5 degrees, corresponding to a physical size of about 50pc. we discuss the origin of the γ-ray emission and possible cosmic ray acceleration in the w43 region using multi-wavelength data. Our findings suggest that w43 is likely another young star cluster capable of accelerating cosmic rays (CRs) to at least several hundred TeV.

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Fe3+ ion quantification with reusable bioinspired nanopores

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Chinese Chemical Letters 2025年第2期36卷 207-212页

作者： Yanqiong wang Yaqi hou Fengwei Huo Xu hou Institute of Flexible Electronics (IFE Future Technologies) Xiang’an Campus Xiamen University State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering Xiamen University Institute of Artificial Intelligence Xiamen University Department of Physics Research Institute for Biomimetics and Soft Matter Fujian Provincial Key Laboratory for Soft Materials Research Jiujiang Research Institute College of Physical Science and Technology Xiamen University Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM) Engineering Research Center of Electrochemical Technologies of Ministry of Education Xiamen University

Excessive Fe3+ion concentrations in wastewater pose a long-standing threat to human *** low-cost,high-efficiency quantification of Fe3+ion concentration in unknown solutions can guide environmental management decisions and optimize water treatment *** this study,by leveraging the rapid,real-time detection capabilities of nanopores and the specific chemical binding affinity of tannic acid to Fe3+,a linear relationship between the ion current and Fe3+ion concentration was *** this linear relationship,quantification of Fe3+ion concentration in unknown solutions was ***,ethylenediaminetetraacetic acid disodium salt was employed to displace Fe3+from the nanopores,allowing them to be restored to their initial conditions and reused for Fe3+ion *** reusable bioinspired nanopores remain functional over 330 days of *** recycling capability and the long-term stability of the nanopores contribute to a significant reduction in *** study provides a strategy for the quantification of unknown Fe3+concentration using nanopores,with potential applications in environmental assessment,health monitoring,and so forth.

关键词： bioinspired nanopores Chemical binding affinity Fe3+ ion quantification Reusability Tannic acid

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Marine dispersion of Fukushima-derived radiocesium in the North Pacific and its implications

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Science China Earth Sciences 2025年第2期68卷 389-406页

作者： Tong ZHANG Xiaolin hou Yukun FAN State Key Laboratory of Loess and Quaternary Geology Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and ApplicationXi’an AMS CenterInstitute of Earth EnvironmentChinese Academy of SciencesXi’an 710061China University of Chinese Academy of Sciences Beijing 100049China Xi’an Institute for Innovative Earth Environment Research Xi’an 710061China

A key scientific approach to addressing the environmental radiation risks from Fukushima nuclear contaminated water(FNCw) discharge into the ocean is understanding and predicting the marine dispersion of *** dispersion of radiocesium(CsF:134Cs,137Cs) from the Fukushima nuclear accident in the North Pacific and its marginal seas post-2011 was systematically summarized,focusing on pathways,vertical distribution changes,and transit *** research examined CsFdispersion through the Kuroshio Extension and denser central mode water(D-CMw) to the eastern North Pacific,as well as through subtropical mode water(STMw),lighter central mode water(L-CMw),and D-CMw to the subtropical western North Pacific,China Seas,and Sea of *** considered broader implications of CsFdispersion in light of ongoing FNCw *** this prolonged liquid discharge and Kuroshio Extension’s barrier effect,it is crucial to emphasize the role of CMw besides STMw in transporting FNCw to the subtropical western North Pacific and its marginal *** research should focus on the key mechanism and longitude range of CMw crossing the Kuroshio *** short-lived134Cs decays rapidly during the storage and dispersion of FNCw,long-lived135Cs and135Cs/137Cs ratios can serve as valuable tracers for detecting and quantifying ***,there is an urgent need for high-precision analysis of these key radionuclides and their characteristic *** promptly detect,assess,and respond to FNCw intrusion,continuous monitoring and identification of nuclear pollution sources in key ocean currents and straits are ***,interdisciplinary research integrating monitoring with marginal sea circulation dynamics and high-resolution numerical simulations should be a priority.

关键词： Fukushima nuclear accident Fukushima nuclear contaminated water Marine dispersion Mode water Kuroshio Extension

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Evolution from the Kondo phase to the RKKY phase in the small impurity spacing regime of the two-impurity Anderson model

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Chinese Physics b 2025年第2期34卷 97-109页

作者： hou-Min Du Yu-Liang Liu Department of Physics Renmin University of ChinaBeijing 100872China

Understanding the quantum critical phenomena is one of the most important and challenging tasks in condensed matter physics and the two-impurity Anderson model(TIAM) is a good starting point for this exploration. To this end,we employ the algebraic equation of motion approach to calculate the TIAM and analytically obtain the explicit singleparticle impurity Green function under the soft cut-off approximation(SCA). This approach effectively incorporates the impurity spacing as an intrinsic parameter. by solving the pole equations of the Green function, we have, for the first time, qualitatively calculated the spectral weight functions of the corresponding low-energy excitations. we find that when the impurity spacing is less than one lattice distance, the dynamic Rudermann–Kittel–Kasuya–Yosida(RKKY) interaction effectively enters, resulting in a rapid increase in the spectral weights of the RKKY phase, which ultimately surpass those of the Kondo phase;while the spectral weights of the Kondo phase are strongly suppressed. From the perspective of spectral weights, we further confirm the existence of a crossover from the Kondo phase to the RKKY phase in the TIAM. based on these results, the reasons for the phenomenon of the Kondo resonance splitting are also discussed.

关键词： multiple-point correlation function soft cut-off approximation Kondo resonance splitting RKKY interaction

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Establishing a new testing protocol of the electrochemical stability window for electric double-layer capacitors

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Science China Chemistry 2025年第1期68卷 217-225页

作者： Ruilin hou Xiaoxi Zhao Tingting Liang Qingyun Dou Shan Xu Xingbin Yan School of Materials Science and Engineering Sun Yat-sen UniversityGuangzhou 510275China Laboratory of Clean Energy Chemistry and Materials Lanzhou Institute of Chemical PhysicsChinese Academy of SciencesLanzhou 730000China Center of Industrial Analysis and Testing Guangdong Academy of ScienceGuangzhou 510651China College of Engineering and Applied Sciences Nanjing UniversityNanjing 210093China

The electrochemical stability window(ESw)is crucial for determining the energy density of electric double-layer capacitors(EDLCs).However,current ESw testing protocols of EDLCs are strongly affected by artificial factors,thereby leading to unreliable *** solve this problem,we first identify the key shortcomings of the traditional protocols by analyzing their test ***,taking an aqueous carbon-based EDLC as an example,we design a side reaction descriptor to represent the response difference in the charging capacitance to side reactions between the cyclic voltammetry and galvanostatic chargedischarge *** the aid of this descriptor,we propose a new ESw testing protocol,which is not only able to completely avoid the adverse influence of subjective factors but also fully consider the operating condition *** protocol can be extended from the single electrode to the full *** work proposes a more rigorous definition of ESw and provides a reliable protocol for evaluating the ESw of EDLCs.

关键词： electric double-layer capacitors electrochemical stability window testing protocol side reaction descriptor operating limitation

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Accurate prediction of essential proteins using ensemble machine learning

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Chinese Physics b 2025年第1期34卷 108-115页

作者： Dezhi Lu Hao wu Yutong hou Yuncheng wu Yuanyuan Liu Jinwu wang School of Medicine Shanghai UniversityShanghai 200444China Shanghai Key Laboratory of Orthopaedic Implants Department of Orthopaedic SurgeryShanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghai 200011China University of Shanghai for Science and Technology Shanghai 200093China

Essential proteins are crucial for biological processes and can be identified through both experimental and computational *** experimental approaches are highly accurate,they often demand extensive time and *** address these challenges,we present a computational ensemble learning framework designed to identify essential proteins more *** method begins by using node2vec to transform proteins in the protein–protein interaction(PPI)network into continuous,low-dimensional *** also extract a range of features from protein sequences,including graph-theory-based,information-based,compositional,and physiochemical ***,we leverage deep learning techniques to analyze high-dimensional position-specific scoring matrices(PSSMs)and capture evolutionary *** then combine these features for classification using various machine learning *** enhance performance,we integrate the outputs of these algorithms through ensemble methods such as voting,weighted averaging,and *** approach effectively addresses data imbalances and improves both robustness and *** ensemble learning framework achieves an AUC of 0.960 and an accuracy of 0.9252,outperforming other computational *** results demonstrate the effectiveness of our approach in accurately identifying essential proteins and highlight its superior feature extraction capabilities.

关键词： protein-protein interaction(PPI) essential proteins deep learning ensemble learning

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ZIF-90-loaded DNAzyme-responsive PROTAC for the self-powered degradation of NF-κb

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Science China Chemistry 2025年第2期68卷 687-693页

作者： Min hou Liang Sun Tianyu Ren Mingda Li Chao Hu Rong Liu Shuang Gu Mingyan Jiang Jian-Hui Jiang Jianjun He College of Physics and Chemistry Hunan First Normal UniversityChangsha 410205China Hunan Provincial Key Laboratory of Animal Models and Molecular Medicine College of Biomedical SciencesCollege of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China Xiangtan Central Hospital Xiangtan 411199China

Transcription factors(TFs)play vital roles in regulating gene *** or mutated TFs are implicated in a wide array of diseases,highlighting their potential as drug ***,TFs are considered undruggable by conventional inhibitor-based *** recently emerged proteolysis targeting chimeras(PROTACs)have exhibited great potential in tackling *** particular,DNA-ligand chimeras that arm E3 ligase-recruiting ligands to TF-binding double-strand DNA represent a promising strategy for the targeted proteolysis of ***,we report a DNAzyme-inducible PROTAC(DzTAC)that selectively degrades NF-κb in a zinc ion-dependent *** further applied zinc-imidazolate metal–organic framework90(ZIF-90)to encapsulate DzTAC(ZIF-90@DzTAC),facilitating its delivery into cancer cells while self-supplying Zn2+via adenosine triphosphate(ATP)-triggered ZIF-90 ***,ZIF-90@DzTAC can enhance the treatment efficacy of doxorubicin-based chemotherapy in tumor-bearing *** developed DzTAC provides specific modulation over TF activity and opens an avenue for more functional nucleic acid-based control over targeted protein degradation.

关键词： inducible proteolysis DNAzyme transcription factor ZIF-90 NF-κb

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LHAASO-KM2A detector simulation using Geant4

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Radiation Detection Technology and Methods 2024年第3期8卷 1437-1447页

作者： Zhen Cao F.Aharonian Q.An Axikegu Y.X.bai Y.w.bao D.bastieri X.J.bi Y.J.bi J.T.Cai Q.Cao w.Y.Cao Zhe Cao J.Chang J.F.Chang 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.Chen N.Cheng Y.D.Cheng M.Y.Cui S.w.Cui X.H.Cui Y.D.Cui b.Z.Dai H.L.Dai Z.G.Dai Danzengluobu X.Q.Dong K.K.Duan J.H.Fan Y.Z.Fan J.Fang K.Fang C.F.Feng L.Feng S.H.Feng X.T.Feng Y.L.Feng S.Gabici b.Gao C.D.Gao L.Q.Gao Q.Gao w.Gao w.K.Gao M.M.Ge L.S.Geng G.Giacinti G.H.Gong Q.b.Gou M.H.Gu F.L.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han H.H.He H.N.He J.Y.He X.b.He Y.He Y.K.Hor b.w.hou C.hou X.hou H.b.Hu Q.Hu S.C.Hu D.H.Huang T.Q.Huang w.J.Huang X.T.Huang X.Y.Huang Y.Huang Z.C.Huang X.L.Ji H.Y.Jia K.Jia K.Jiang X.w.Jiang Z.J.Jiang M.Jin M.M.Kang T.Ke D.Kuleshov K.Kurinov 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 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.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu w.Liu Y.Liu Y.N.Liu R.Lu Q.Luo H.K.Lv b.Q.Ma L.L.Ma X.H.Ma J.R.Mao Z.Min w.Mitthumsiri H.J.Mu Y.C.Nan A.Neronov 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 D.Semikoz C.Y.Shao L.Shao O.Shchegolev X.D.Sheng F.w.Shu H.C.Song Yu.V.Stenkin V.Stepanov Y.Su Q.N.Sun X.N.Sun Z.b.Sun P.H.T.Tam Q.w.Tang Z.b.Tang w.w.Tian C.wang C.b.wang G.w.wang H.G.wang H.H.wang J.C.wang K.wang L.P.wang L.Y.wang P.H.wang R.wang w.wang X.G.wang X.Y.wang Y.wang Y.D.wang Y.J.wang Z.H.wang Z.X.wang Zhen wang Zheng 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.F.Xu R.X.Xu w.L.Xu L.Xue D.H.Yan J.Z.Yan T.Yan C.w.Yang F.Yang F.F.Yang H.w.Yang J.Y.Yang L.L.Yang M.J.Yang R.Z.Yang S.b.Yang Y.H.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.H.You Z.Y.You Y.H.Yu Q.Yuan H.Yue H.D.Zeng T.X.Zeng w.Zeng M.Zha b.b.Zhang F.Zhang H.M.Zhang H.Y.Zhang J.L.Zhang L.X.Zhang Li Zhang P.F.Zhang P.P.Zhang R.Zhang S.b.Zh Key Laboratory of Particle Astrophysics&Experimental Physics Division&Computing Center Institute of High Energy PhysicsChinese Academy of SciencesBeijing100049China University of Chinese Academy of Sciences Beijing100049China TIANFU Cosmic Ray Research Center ChengduSichuanChina Dublin Institute for Advanced Studies 31 Fitzwilliam Place2 DublinIreland Max-Planck-Institute for Nuclear Physics 69029Heidelberg103980Germany State Key Laboratory of Particle Detection and Electronics BeijingChina University of Science and Technology of China Hefei230026AnhuiChina School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu610031SichuanChina School of Astronomy and Space Science Nanjing UniversityNanjing210023JiangsuChina Center for Astrophysics Guangzhou UniversityGuangzhou510006GuangdongChina Hebei Normal University Shijiazhuang050024HebeiChina Key Laboratory of Dark Matter and Space Astronomy&Key Laboratory of Radio Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023JiangsuChina Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Key Laboratory of Cosmic Rays(Tibet University) Ministry of EducationLhasa 850000TibetChina National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Physics and Astronomy(Zhuhai)&School of Physics(Guangzhou)&Sino-French Institute of Nuclear Engineering and Technology(Zhuhai) Sun Yat-sen UniversityGuangzhouZhuhai 510275519000GuangdongChina School of Physics and Astronomy Yunnan UniversityKunming 650091YunnanChina Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237ShandongChina APC UniversitéParis CitéCNRS/IN2P3CEA/IRFUObservatoire de ParisParis 11975205France Department of Engineering Phys

KM2A is one of the main sub-arrays of LHAASO,working on gamma ray astronomy and cosmic ray physics at energies above 10 *** simulation is the important foundation for estimating detector performance and data *** is a big challenge to simulate the KM2A detector in the framework of Geant4 due to the need to track numerous photons from a large number of detector units(>6000)with large altitude difference(30)and huge coverage(1.3).In this paper,the design of the KM2A simulation code G4KM2A based on Geant4 is *** process of G4KM2A is optimized mainly in memory consumption to avoid memory *** simplifications are used to significantly speed up the execution of *** running time is reduced by at least 30 times compared to full detector *** particle distributions and the core/angle resolution comparison between simulation and experimental data of the full KM2A array are also presented,which show good agreement.

关键词： LHAASO KM2A Simulation GEANT4

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