检索结果-内蒙古大学图书馆

Evidence for particle acceleration approaching PeV energies in the W51 complex

science Bulletin 2024年第18期69卷 2833-2841页

作者： LHAASO Collaboration 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.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 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 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 D.H.Huang T.Q.Huang W.J.Huang X.T.Huang X.Y.Huang Y.Huang X.L.Ji H.Y.Jia K.Jia K.Jiang X.W.Jiang Z.J.Jiang M.Jin M.M.Kang I.Karpikov 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 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 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.Yu Q.Yuan H.Yue H.D.Zeng T.X.Zeng W.Zeng M.Zha B.B.Zhang F.Zhang H.Zhang 不详 Key Laboratory of Particle Astrophysics&Experimental Physics Division&Computing Center Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China TIANFU Cosmic Ray Research Center ChengduChina Dublin Institute for Advanced Studies 31 Fitzwilliam Place2 DublinIreland Max-Planck-Institut for Nuclear Physics P.O.Box 103980Heidelberg 69029Germany School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031China School of Astronomy and Space Science Nanjing UniversityNanjing 210023China Center for Astrophysics Guangzhou UniversityGuangzhou 510006China Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China Institute for Nuclear Research of Russian Academy of Sciences Moscow 117312Russia Hebei Normal University Shijiazhuang 050024China University of Science and Technology of China Hefei 230026China State Key Laboratory of Particle Detection and Electronics China Key Laboratory of Dark Matter and Space Astronomy&Key Laboratory of Radio Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China Research Center for Astronomical Computing Zhejiang LaboratoryHangzhou 311121China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China School of Physics and Astronomy Yunnan UniversityKunming 650091China Key Laboratory of Cosmic Rays(Tibet University) Ministry of EducationLhasa 850000China 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 UniversityZhuhai 519000&Guangzhou 510275GuangdongChina Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237China APC UniversitéParis Cité

Theγ-ray emission from the W51 complex is widely acknowledged to be attributed to the interaction between the cosmic rays(CRs)accelerated by the shock of supernova remnant(SNR)W51C and the dense molecular clouds in the adjacent star-forming region,***,the maximum acceleration capability of W51C for CRs remains *** on observations conducted with the Large high Altitude Air Shower Observatory(LHAASO),we report a significant detection ofγrays emanating from the W51 complex,with energies from 2 to 200 *** LHAASO measurements,for the first time,extend theγ-ray emission from the W51 complex beyond 100 TeV and reveal a significant spectrum bending at tens of *** combining the"π^(0)-decay bump"featured data from Fermi-LAT,the broadbandγ-ray spectrum of the W51 region can be well-characterized by a simple pp-collision *** observed spectral bending feature suggests an exponential cutoff at~400 TeV or a power-law break at~200 TeV in the CR proton spectrum,most likely providing the first evidence of SNRs serving as CR accelerators approaching the PeV ***,two young star clusters within W51B could also be theoretically viable to produce the most energeticγrays observed by *** findings strongly support the presence of extreme CR accelerators within the W51 complex and provide new insights into the origin of Galactic CRs.

关键词： UHE c-ray Cosmic rays SNR W51C Star clusters

来源：评论

学校读者我要写书评

暂无评论

Investigating Polarization characteristics of GRB 200503A and GRB 201009A

arXiv

引用

arXiv 2024年

作者： Saraogi, Divita Bala, Suman Joshi, Jitendra Iyyani, Shabnam Bhalerao, Varun Aditya, J. Venkata Svinkin, D.S. Frederiks, D.D. Lysenko, A.L. Ridnaia, A.V. Kozyrev, A.S. Golovin, D.V. Mitrofanov, I.G. Litvak, M.L. Sanin, A.B. Chattopadyay, Tanmoy Gupta, Soumya Waratkar, Gaurav Bhattacharya, Dipankar Vadawale, Santosh Dewangan, Gulab Department of Physics Indian Institute of Technology Bombay Maharashtra Mumbai400076 India Science and Technology Institute Universities Space Research Association HuntsvilleAL35805 United States Inter University Centre for Astronomy and Astrophysics Maharashtra Pune411007 India School of Physics Indian Institute of Science Education and Research Thiruvananthapuram695551 India Centre of High Performance Computing Indian Institute of Science Education and Research Thiruvananthapuram695551 India Department of Computer Science and Engineering Indian Institute of Technology Bombay Powai Maharashtra Mumbai400076 India Ioffe Institute Polytekhnicheskaya 26 St. Petersburg194021 Russia 84/32 Profsoyuznaya Moscow117997 Russia Kavli Institute of Particle Astrophysics and Cosmology 452 Lomita Mall StanfordCA94305 United States Astrophysical Science Division Homi Bhabha National Institute Anushakti Nagar Maharashtra Mumbai400094 India Department of Physics Ashoka University Haryana Sonepat131029 India Physical Research Laboratory Gujarat Ahmedabad380009 India

We present results of a comprehensive analysis of the polarization characteristics of GRB 200503A and GRB 201009A observed with the Cadmium Zinc Telluride Imager (CZTI) on board AstroSat. Despite these GRBs being reasonably bright, they were missed by several spacecraft and had thus far not been localized well, hindering polarization analysis. We present positions of these bursts obtained from the Inter-Planetary Network (IPN) and the newly developed CZTI localization pipeline. We then undertook polarization analyses using the standard CZTI pipeline. We cannot constrain the polarization properties for GRB 200503A, but find that GRB 201009A has a high degree of polarization. © 2024, CC BY.

关键词： Gamma rays

来源：评论

学校读者我要写书评

暂无评论

Understanding the design space of mouth microgestures

arXiv

引用

arXiv 2021年

作者： Chen, Victor Shi, Yuanchun Xu, Xuhai Patel, Shwetak Li, Richard Wang, Yuntao Department of Computer Science Stanford University StanfordCA United States Department of Computer Science and Technology Key Laboratory of Pervasive Computing Ministry of Education Tsinghua University Beijing China Information School University of Washington SeattleWA United States Paul G. Allen School of Computer Science & Engineering University of Washington SeattleWA United States

As wearable devices move toward the face (i.e. smart earbuds, glasses), there is an increasing need to facilitate intuitive interactions with these devices. Current sensing techniques can already detect many mouth-based gestures;however, users' preferences of these gestures are not fully understood. In this paper, we investigate the design space and usability of mouth-based microgestures. We first conducted brainstorming sessions (N=16) and compiled an extensive set of 86 user-defined gestures. Then, with an online survey (N=50), we assessed the physical and mental demand of our gesture set and identified a subset of 14 gestures that can be performed easily and naturally. Finally, we conducted a remote Wizard-of-Oz usability study (N=11) mapping gestures to various daily smartphone operations under a sitting and walking context. From these studies, we develop a taxonomy for mouth gestures, finalize a practical gesture set for common applications, and provide design guidelines for future mouth-based gesture interactions. Copyright © 2021, The Authors. All rights reserved.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

SecureShare: Blockchain based Secure and Verifiable Knowledge Sharing for AI-Generated Content (AIGC) Services

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Fan, Mochan Li, Zonghang Sun, Gang Du, Hongyang Yu, Hongfang Niyato, Dusit University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu610054 China Agile and Intelligent Computing Key Laboratory of Sichuan Province Chengdu China Department of Electrical and Electronic Engineering 999077 Hong Kong Peng Cheng Laboratory Shenzhen China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore

Benefiting from the rapidly expanding Internet of Things (IoT) data and powerful computing devices, AI-generated content (AIGC) trains models with vast knowledge to provide automated content generation services. Sharing knowledge through the ciphertext-policy attribute-based encryption (CP-ABE) algorithm is beneficial for training high-quality AIGC models to offer better services. However, existing CP-ABE sharing schemes often involve untrusted third parties, which can result in issues such as knowledge deletion, unverifiable access, and single points of failure. To address these challenges, some blockchain-based sharing schemes have been developed. However, they still face privacy leakage problems. In this paper, we propose SecureShare, a secure and verifiable knowledge sharing scheme based on a consortium blockchain for AIGC services. We begin by outlining a blockchain knowledge sharing architecture and optimizing the Delegated Proof of Stake (DPOS) committee node selection method to ensure that entities can achieve verifiable access control. Additionally, to achieve fine-grained access to knowledge ciphertext while preserving privacy, we propose a CP-ABE scheme with Policy Hiding, attribute privacy preservation, and Revocation, referred to as PHR-CP-ABE. PHR-CP-ABE ensures the privacy of access policies and attributes, and users whose attributes have been revoked cannot decrypt knowledge further. A case study on Dall-E clearly illustrates the operational mechanism of the proposed scheme. We provide theoretical analysis of the security of both the AIGC knowledge sharing scheme and PHR-CP-ABE. Through extensive performance analysis and comparisons with existing schemes, our approach demonstrates significant advantages in terms of computation and communication overhead. © 1967-2012 IEEE.

关键词： Ciphertext

来源：评论

学校读者我要写书评

暂无评论

Multi-modal remote sensory learning for multi-objects over autonomous devices

引用

Frontiers in bioengineering and biotechnology 2025年 13卷 1430222页

作者： Aysha Naseer Naif Almudawi Hanan Aljuaid Abdulwahab Alazeb Yahay AlQahtani Asaad Algarni Ahmad Jalal Hui Liu Department of Computer Science Air University Islamabad Pakistan. Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia. Department of Computer Science College of Computer Science and Information System Najran University Najran Saudi Arabia. Department of Informatics and Computer Systems King Khalid University Abha Saudi Arabia. Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia. Department of Computer Science and Engineering College of Informatics Korea University Seoul South Korea. Guodian Nanjing Automation Co. Ltd. Nanjing China. Jiangsu Key Laboratory of Intelligent Medical Image Computing School of Future Technology Nanjing University of Information Science and technology Nanjing China. Cognitive Systems Lab University of Bremen Bremen Germany.

Introduction:There has been an increasing focus on object segmentation within remote sensing images in recent years due to advancements in remote sensing technology and the growing significance of these images in both military and civilian realms. In these situations, it is critical to accurately and quickly identify a wide variety of objects. In many computer vision applications, scene recognition in aerial-based remote sensing imagery presents a common issue. Method:However, several challenging elements make this work especially difficult: (i) Different objects have different pixel densities; (ii) objects are not evenly distributed in remote sensing images; (iii) objects can appear differently depending on viewing angle and lighting conditions; and (iv) there are fluctuations in the number of objects, even the same type, in remote sensing images. Using a synergistic combination of Markov Random Field (MRF) for accurate labeling and Alex Net model for robust scene recognition, this work presents a novel method for the identification of remote sensing objects. During the labeling step, the use of MRF guarantees precise spatial contextual modeling, which improves comprehension of intricate interactions between nearby aerial objects. By simultaneously using deep learning model, the incorporation of Alex Net in the following classification phase enhances the model's capacity to identify complex patterns in aerial images and adapt to a variety of object attributes. Results:Experiments show that our method performs better than others in terms of classification accuracy and generalization, indicating its efficacy analysis on benchmark datasets such as UC Merced Land Use and AID. Discussion:Several performance measures were calculated to assess the efficacy of the suggested technique, including accuracy, precision, recall, error, and F1-Score. The assessment findings show a remarkable recognition rate of around 97.90% and 98.90%, on the AID and the UC Merced Land datasets,

关键词： autonomous devices deep learning computer vision likelihood estimation multi-modal multi-objects posterior probability remote sensing scene analysis

来源：评论

学校读者我要写书评

暂无评论

Principled design of translation, scale, and rotation invariant variation operators for metaheuristics

arXiv

引用

arXiv 2021年

作者： Tian, Ye Zhang, Xingyi He, Cheng Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Guangdong Provincial Key Laboratory of Braininspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Computing The Hong Kong Polytechnic University Hong Kong Department of Computer Science University of Surrey Guildford SurreyGU2 7XH United Kingdom

In the past three decades, a large number of metaheuristics have been proposed and shown high performance in solving complex optimization problems. While most variation operators in existing metaheuristics are empirically designed, this paper aims to design new operators automatically, which are expected to be search space independent and thus exhibit robust performance on different problems. For this purpose, this work first investigates the influence of translation invariance, scale invariance, and rotation invariance on the search behavior and performance of some representative operators. Then, we deduce the generic form of translation, scale, and rotation invariant operators. Afterwards, a principled approach is proposed for the automated design of operators, which searches for highperformance operators based on the deduced generic form. The experimental results demonstrate that the operators generated by the proposed approach outperform state-of-theart ones on a variety of problems with complex landscapes and up to 1000 decision variables. © 2021, CC BY.

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Size-fixed group discovery via multi-constrained graph pattern matching

引用

information sciences 2025年 690卷

作者： Guliu Liu Lei Li Guanfeng Liu Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education 230601 Hefei China School of Computer Science and Information Engineering Hefei University of Technology 230601 Hefei China Department of Computing Macquarie University Sydney 2122 Australia

Multi-Constrained Graph Pattern Matching (MC-GPM) aims to match a pattern graph with multiple attribute constraints on its nodes and edges, and has garnered significant interest in various fields, including social-based e-commerce and trust-based group discovery. However, the existing MC-GPM methods do not consider situations where the number of each node in the pattern graph needs to be fixed, such as finding experts group with expert quantities and relations specified. In this paper, a Multi-Constrained Strong Simulation with the Fixed Number of Nodes (MCSS-FNN) matching model is proposed, and then a Trust-oriented Optimal Multi-constrained Path (TOMP) matching algorithm is designed for solving it. Additionally, two heuristic optimization strategies are designed, one for combinatorial testing and the other for edge matching, to enhance the efficiency of the TOMP algorithm. Empirical experiments are conducted on four real social network datasets, and the results demonstrate the effectiveness and efficiency of the proposed algorithm and optimization strategies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-Modal Transformer for Accelerated MR Imaging

arXiv

引用

arXiv 2021年

作者： Feng, Chun-Mei Yan, Yunlu Chen, Geng Xu, Yong Hu, Ying Shao, Ling Fu, Huazhu Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen518055 China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Terminus Group China Institute of High Performance Computing A*STAR Singapore138632 Singapore

Accelerated multi-modal magnetic resonance (MR) imaging is a new and effective solution for fast MR imaging, providing superior performance in restoring the target modality from its undersampled counterpart with guidance from an auxiliary modality. However, existing works simply combine the auxiliary modality as prior information, lacking in-depth investigations on the potential mechanisms for fusing different modalities. Further, they usually rely on the convolutional neural networks (CNNs), which is limited by the intrinsic locality in capturing the long-distance dependency. To this end, we propose a multi-modal transformer (MTrans), which is capable of transferring multi-scale features from the target modality to the auxiliary modality, for accelerated MR imaging. To capture deep multi-modal information, our MTrans utilizes an improved multi-head attention mechanism, named cross attention module, which absorbs features from the auxiliary modality that contribute to the target modality. Our framework provides three appealing benefits: (i) Our MTrans use an improved transformers for multi-modal MR imaging, affording more global information compared with existing CNN-based methods. (ii) A new cross attention module is proposed to exploit the useful information in each modality at different scales. The small patch in the target modality aims to keep more fine details, the large patch in the auxiliary modality aims to obtain high-level context features from the larger region and supplement the target modality effectively. (iii) We evaluate MTrans with various accelerated multi-modal MR imaging tasks, e.g., MR image reconstruction and super-resolution, where MTrans outperforms state-of-the-art methods on fastMRI and real-world clinical datasets. © 2021, CC BY.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Augmenting photoluminescence of monolayer MoS_(2) using high order modes in a metal dimer-on-film nanocavity

引用

Photonics Research 2021年第4期9卷 501-506页

作者： Shiyin Cao Liping Hou Qifa Wang Chenyang Li Weixing Yu Xuetao Gan Kaihui Liu Malin Premaratne Fajun Xiao Jianlin Zhao MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710129China Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences Xi’an 710119China State Key Laboratory for Mesoscopic Physics Collaborative Innovation Centre of Quantum MatterSchool of PhysicsPeking UniversityBeijing 100871China Advanced Computing and Simulation Laboratory(AχL) Department of Electrical and Computer Systems EngineeringMonash UniversityClaytonVIC 3800Australia

Plasmonic particle-on-film nanocavities,supporting gap modes with ultra-small volume,provide a great solution to boost light–matter interactions at the *** this work,we report on the photoluminescence(PL)enhancement of monolayer MoS_(2) using high order modes of an Au nanosphere dimer-on-film nanocavity(DoFN).The high order plasmon modes,consisting of two bonding quadrupoles in the dimer and their images in the Au film,are revealed by combining the polarization-resolved scattering spectra with the numerical *** integrating the monolayer MoS_(2) into the DoFN,these high order modes are used to enhance PL intensity through simultaneously boosting the absorption and emission processes,producing a 1350-fold enhancement *** opens an avenue to enhance the light–matter interaction with high order plasmon modes and may find applications in future optoelectronics and nanophotonics devices.

关键词： cavity high integrating

来源：评论

学校读者我要写书评

暂无评论

Quasi-Phase-Matching Enabled by van der Waals Stacking

arXiv

引用

arXiv 2024年

作者： Tang, Yilin Sripathy, Kabilan Qin, Hao Lu, Zhuoyuan Guccione, Giovanni Janousek, Jiri Zhu, Yi Hasan, Md Mehedi Iwasa, Yoshihiro Lam, Ping Koy Lu, Yuerui School of Engineering College of Engineering Computing and Cybernetics The Australian National University CanberraACT2601 Australia ARC Centre for Quantum Computation and Communication Technology The Australian National University CanberraACT2601 Australia Research School of Physics College of Science The Australian National University CanberraACT2601 Australia Department of Computer Engineering TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Clarendon Laboratory University of Oxford OxfordOX1 3PU United Kingdom RIKEN Center for Emergent Matter Science Hirosawa 2-1 Wako Saitama351-0198 Japan 2 Fusionopolis Way Innovis #08-03 Singapore138634 Singapore

Quasi-phase matching (QPM) is a technique extensively utilized in nonlinear optics for enhancing the efficiency and stability of frequency conversion processes. However, the conventional QPM relies on periodically poled ferroelectric crystals, which are limited in availability. The 3R phase of molybdenum disulfide (3R-MoS2), a transition metal dichalcogenide (TMDc) with the broken inversion symmetry, stands out as a promising candidate for QPM, enabling efficient nonlinear process. Here, we experimentally demonstrate the QPM at nanoscale, utilizing van der Waals stacking of 3R-MoS2 layers with specific orientation to realize second harmonic generation (SHG) enhancement beyond the non QPM limit. We have also demonstrated enhanced spontaneous parametric down-conversion (SPDC) via QPM of 3R-MoS2 homo-structure, enabling more efficient generation of entangled photon pairs. The tunable capacity of 3R-MoS2 van der Waals stacking provides a platform for tuning phase-matching condition. This technique opens interesting possibilities for potential applications in nonlinear process and quantum technology. Copyright © 2024, The Authors. All rights reserved.

关键词： Van der Waals forces

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：