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2016 IEEE National Aerospace and Electronics Conference and Ohio Innovation Summit, NAECON-OIS 2016

作者： Zarafshani, Ali Chatwin, Chris Bach, Thomas Zheng, Bin School of Engineering and Informatics University of Sussex Brighton United Kingdom Head of Research Sensatech Research Brighton United Kingdom School of Electrical and Computer Engineering University of Oklahoma NormanOK73019 United States

ISBN: (纸本)9781509034413

electrical Impedance Tomography (EIT) is an emerging imaging modality that produces either a 2D or 3D impedance image (conductivity or impedivity) of the subject under test. In this study we tested and demonstrated a new application of applying an EIT system to detect delamination and evaluate the damage location, size, strain and severity for Structure Health Monitoring (SHM) of composites (i.e. Carbonfibre-reinforced polymer (CFRP) composites). © 2016 IEEE.

关键词： Damage detection

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Forecasting: theory and practice

arXiv

引用

arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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A coalition formation approach to coordinated task allocation in heterogeneous uav networks

arXiv

引用

arXiv 2017年

作者： Afghah, Fatemeh Zaeri-Amirani, Mohammad Razi, Abolfazl Chakareski, Jacob Bentley, Elizabeth School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ United States Department of Electrical & Computer Engineering University of Alabama TuscaloosaAL United States Air Force Research Laboratory RomeNY United States

The problem of adversary target detection and the subsequent task completion using a heterogeneous network of resource-constrained UAVs is considered. No prior knowledge about locations and required resources to identify these targets is available to the UAVs. In the proposed leader-follower coalition formation model, the UAV that first locates a target serves as the coalition leader and selects a group of follower UAVs to complete the task associated with the identified target. The goal of the coalition formation is to complete the designated tasks with minimal resource utilization. Another role of coalition members is to make the ground station aware of the detected adversary target by forwarding its signal to the station via a distributed cooperative relaying scheme. We also propose a reputation-based mechanism for coalition formation to monitor the cooperative behavior of the UAVs over the course of time and exclude potentially untrustworthy UAVs. Simulation results show the efficiency of the proposed method in forming optimal coalitions compared to alternative methods.1. Copyright © 2017, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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A data-driven QoT decision approach for multicast connections in metro optical networks

A data-driven QoT decision approach for multicast connection...

引用

International Conference on Optical Network Design and Modeling, ONDM

作者： Tania Panayiotou Georgios Ellinas Sotirios P. Chatzis Department of Electrical and Computer Engineering University of Cyprus Cyprus Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Cyprus

A data-driven technique for analyzing Quality-of-Transmission (QoT) data of previously established connections is proposed for accurately deciding the QoT of the newly arriving multicast requests in metro optical networks. The proposed approach is self-adaptive, it is a function of data that are independent from the physical layer impairment (PLIs) and thus does not require specific measurement equipment, and it does not assume the existence of a system with extensive processing and storage capabilities. It is also fast in processing new data, and fast in finding a near-accurate QoT model provided that such a model exists. The proposed technique can replace the existing Q-factor models that are not self-adaptive, they are a function of the PLIs, and their evaluation requires time-consuming simulations, lab experiments, specific measurement equipment, and considerable human effort. The proposed data-driven QoT approach is based on the utilization of a feed-forward neural network that is trained on a dataset previously generated from a known Q-factor model. The dataset fed to the neural network is represented in a way that specifically describes the QoT of the multicast connections requesting to be established in the network but it is independent from the PLIs. The validity of the proposed approach is examined for two distinct networks, exhibiting a high accuracy when compared to the results of the Q-factor model utilized for generating the QoT data.

关键词： Neural networks Data models Optical fiber networks Q-factor Training Physical layer Optical noise

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Control and Notification Automatic Water Pump with Arduino and SMS Gateway

引用

IOP Conference Series: Materials Science and engineering 2018年第1期407卷

作者： R Ratnadewi H Nurdiyanto A Najmurrokhman C Prabowo R Idmayanti H Eteruddin C A Sugianto N Kurniasih H K Siburian D Nababan R Rahim Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Department of Informatics STMIK Dharma Wacana Metro Lampung Indonesia Department of Electrical Engineering Universitas Jenderal Achmad Yani Cimahi Indonesia Department of Information Technology Politeknik Negeri Padang Padang Indonesia Department of Electrical Universitas Lancang Kuning Pekanbaru Indonesia Departement of Informatics Politeknik TEDC Bandung Bandung Indonesia Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Informatics Sekolah Tinggi Manajemen Informatika dan Komputer Medan Indonesia Department of Information System Universitas Pelita Harapan Medan Medan Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia

This paper aims to facilitate the owner to control water pump machine from the vacuum, and the condition of the water is it full or not in house or apartment. The current control system still has many limitations in controlling the water pump machine at home or apartment. The water machine control system was designed with device that has a smart surveillance system that can be accessed with Android smartphone and all information from or to machine control system will command by using SMS, this device create a development of Arduino UNO microcontroller technology that allows the reading of the GSM Module and connected with SMS Gateway. Experiment results facilitate real-time water control and much easy for the owner to control water tank.

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Pixel image steganography using EOF method and modular multiplication block cipher algorithm

引用

IOP Conference Series: Materials Science and engineering 2018年第1期420卷

作者： Robbi Rahim Darmawan Napitupulu Heri Nurdiyanto Usti Fatimah Sari Firahmi Rizky Dicky Nofriansyah Oris Krianto Sulaiman Abdurrozzaq Hasibuan R Ratnadewi Mohamad Ihwani School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Jakarta Indonesia Department of Informatics STMIK Dharma Wacana Metro Lampung Indonesia Department of Computer System STMIK Triguna Dharma Medan Indonesia Department of Information System STMIK Triguna Dharma Medan Indonesia Department of Informatics Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Industry Engineering Universitas Islam Sumatera Utara Medan Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Universitas Negeri Medan Medan Indonesia

This study aims to hide data or information on pixel image using EOF method and to improve the security of hidden data than combine with cryptography algorithm Modular Multiplication Block Cipher algorithm for the encryption process. The image file used as the test sample consists of 3 types of image types (JPG, BMP, PNG), this file type is the most widely used by users with different width and height as well as various file sizes. The results of this study prove that the data could embed in pixel image using EOF method and the file size of carrier will increase its capacity as byte of embedded text.

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A Nonstationary Hidden Markov Model with Approximately Infinitely-Long Time-Dependencies

A Nonstationary Hidden Markov Model with Approximately Infin...

引用

作者： Chatzis, Sotirios Kosmopoulos, Dimitrios Papadourakis, George Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus Department of Cultural Heritage Management and New Technologies University of Patras Agrinion30100 Greece Department of Applied Informatics and Multimedia Technological Educational Institute of Crete Heraclion71500 Greece

Hidden Markov models (HMMs) are a popular approach for modeling sequential data, typically based on the assumption of a first-order Markov chain. In other words, only one-step back dependencies are modeled which is a rather unrealistic assumption in most applications. In this paper, we propose a method for postulating HMMs with approximately infinitely-long time-dependencies. Our approach considers the whole history of model states in the postulated dependencies, by making use of a recently proposed nonparametric Bayesian method for modeling label sequences with infinitely-long time dependencies, namely the sequence memoizer. We manage to derive training and inference algorithms for our model with computational costs identical to simple first-order HMMs, despite its entailed infinitely-long time-dependencies, by employing a mean-field-like approximation. The efficacy of our proposed model is experimentally demonstrated. © 2016 World Scientific Publishing Company.

关键词： Hidden Markov models

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Measurements of inclusive and differential cross sections for the Higgs boson production and decay to four-leptons in proton-proton collisions at s = 13 TeV

引用

Journal of High Energy Physics 2023年第8期2023卷 40页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Putte, S. Vannerom, D. Clerbaux, B. Dansana, S. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Rebello Teles, P. Aldá Júnior, W.L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. Bauer, G. Hu, Z. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, J. Zhang, C. Zhang, H. Agapitos, A. Ba Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

Measurements of the inclusive and differential fiducial cross sections for the Higgs boson production in the H → ZZ → 4ℓ (ℓ = e, μ) decay channel are presented. The results are obtained from the analysis of proton-proton collision data recorded by the CMS experiment at the CERN LHC at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb⁻¹. The measured inclusive fiducial cross section is 2.73 ± 0.26 fb, in agreement with the standard model expectation of 2.86 ± 0.1 fb. Differential cross sections are measured as a function of several kinematic observables sensitive to the Higgs boson production and decay to four leptons. A set of double-differential measurements is also performed, yielding a comprehensive characterization of the four leptons final state. Constraints on the Higgs boson trilinear coupling and on the bottom and charm quark coupling modifiers are derived from its transverse momentum distribution. All results are consistent with theoretical predictions from the standard model. © The Author(s) 2023.

关键词： Hadron-Hadron Scattering Higgs Physics

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Structured singular value analysis for spintronics network information transfer control

arXiv

引用

arXiv 2017年

作者： Jonckheere, Edmond A. Schirmer, Sophie G. Langbein, Frank C. Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States College os Science Swansea Univesity Swansea Wales United Kingdom School of Computer Science and Informatics Cardiff University Cardiff Wales United Kingdom

Control laws for selective transfer of information encoded in excitations of a quantum network, based on shaping the energy landscape using time-invariant, spatially-varying bias fields, can be successfully designed using numerical optimization. Such control laws, already departing from classicality by replacing closed-loop asymptotic stability with alternative notions of localization, have the intriguing property that for all practical purposes they achieve the upper bound on the fidelity, yet the (logarithmic) sensitivity of the fidelity to such structured perturbation as spin coupling errors and bias field leakages is nearly vanishing. Here, these differential sensitivity results are extended to large structured variations using μ-design tools to reveal a crossover region in the space of controllers where objectives usually thought to be conflicting are actually concordant. Copyright © 2017, The Authors. All rights reserved.

关键词： Robust control

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Higher-order moments of the elliptic flow distribution in PbPb collisions at sNN = 5.02 TeV

引用

Journal of High Energy Physics 2024年第2期2024卷 1-45页

作者： Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Paulitsch, P. Pitters, F.M. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Rejeb Sfar, H. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Taliercio, A. Tran, T.T. Vischia, P. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Rebello Teles, P. Aldá Júnior, W.L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Thakur, S. Cheng, T. Javaid, T. Mittal, M. Yuan, L. Ahmad, M. Bauer, G. Hu, Z. Lezki, S. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Milosevic, V. Monti, F. Sharma, R. Tao, J. Thomas-Wilsker Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

The hydrodynamic flow-like behavior of charged hadrons in high-energy lead-lead collisions is studied through multiparticle correlations. The elliptic anisotropy values based on different orders of multiparticle cumulants, v₂{2k}, are measured up to the tenth order (k = 5) as functions of the collision centrality at a nucleon-nucleon center-of-mass energy of s_NN = 5.02 TeV. The data were recorded by the CMS experiment at the LHC and correspond to an integrated luminosity of 0.607 nb⁻¹. A hierarchy is observed between the coefficients, with v₂{2} > v₂{4} ≳ v₂{6} ≳ v₂{8} ≳ v₂{10}. Based on these results, centrality-dependent moments for the fluctuation-driven event-by-event v₂ distribution are determined, including the skewness, kurtosis and, for the first time, superskewness. Assuming a hydrodynamic expansion of the produced medium, these moments directly probe the initial-state geometry in high-energy nucleus-nucleus collisions. © The Author(s) 2024.

关键词： Event-by-Event fluctuation Harmonic Flow Heavy Ion Experiments Relativistic Heavy Ion Physics

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