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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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Erratum to: Search for single top-quark production via flavour-changing neutral currents at 8 TeV with the ATLAS detector

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The European Physical Journal C 2022年第1期82卷 1-15页

作者： Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Aben, R. Abolins, M. AbouZeid, O. S. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adamczyk, L. Adams, D. L. Adelman, J. Adomeit, S. Adye, T. Affolder, A. A. Agatonovic-Jovin, T. Agricola, J. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akerstedt, H. Åkesson, T. P. A. Akimov, A. V. Alberghi, G. L. Albert, J. Albrand, S. Alconada Verzini, M. J. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Alimonti, G. Alio, L. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Altheimer, A. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amako, K. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amorim, A. Amoroso, S. Amram, N. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, G. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Anger, P. Angerami, A. Anghinolfi, F. Anisenkov, A. V. Anjos, N. Annovi, A. Antonelli, M. Antonov, A. Antos, J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Arce, A. T. H. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Arnaez, O. Arnal, V. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Asai, S. Asbah, N. Ashkenazi, A. Åsman, B. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Aurousseau, M. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baak, M. A. Baas, A. E. Baca, M. J. Bacci, C. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagiacchi, P. Bagnaia, P. Bai, Y. Bain, T. Baines, J. T. Baker, O. K. Baldin, E. M. Balek, P. Balestri, T. Balli, F. Banas, E. Banerjee, Sw. Bannoura, A. A. E. Bansil, H. S. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisonzi, M. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska, Z. Baroncelli, A. Barone, G. Barr, A. J. Barreiro, F. Barreiro Guimarães da Costa, J. Bartol CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA Institute of Physics Academia Sinica Taipei Taiwan Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam The Netherlands Department of Physics and Astronomy Michigan State University East Lansing USA Department of Physics University of Toronto Toronto Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene USA Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Physics Department Brookhaven National Laboratory Upton USA Department of Physics Northern Illinois University De Kalb USA Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany Particle Physics Department Rutherford Appleton Laboratory Didcot UK Oliver Lodge Laboratory University of Liverpool Liverpool UK Institute of Physics University of Belgrade Belgrade Serbia II Physikalisches Institut Georg-August-Universität Göttingen Germany Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Department of Physics Boston University Boston USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Rome Italy Dipartimento di Fisica Università di Roma Tor Vergata Rome Italy Fysiska institutionen Lunds uni

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Analyticity constraints for hadron amplitudes: Going high to heal low energy issues

arXiv

引用

arXiv 2017年

作者： Mathieu, V. Nys, J. Pilloni, A. Fernández-Ramírez, C. Jackura, A. Mikhasenko, M. Pauk, V. Szczepaniak, A.P. Fox, G. Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Physics Department Indiana University BloomingtonIN47405 United States Department of Physics and Astronomy Ghent University Belgium Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Universität Bonn Helmholtz-Institut für Strahlen- und Kernphysik Bonn53115 Germany School of Informatics Computing and Engineering Indiana University BloomingtonIN47405 United States

Analyticity constitutes a rigid constraint on hadron scattering amplitudes. This property is used to relate models in different energy regimes. Using meson photoproduction as a benchmark, we show how to test contemporary low energy models directly against high energy data. This method pinpoints deficiencies of the models and treads a path to further improvement. The implementation of this technique enables one to produce more stable and reliable partial waves for future use in hadron spectroscopy and new physics searches. Copyright © 2017, The Authors. All rights reserved.

关键词： Hadrons

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On the η and η0 Photoproduction Beam Asymmetry at High Energies

arXiv

引用

arXiv 2017年

作者： Mathieu, V. Nys, J. Fernández-Ramírez, C. Jackura, A. Mikhasenko, M. Pilloni, A. Szczepaniak, A.P. Fox, G. Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Physics Department Indiana University BloomingtonIN47405 United States Department of Physics and Astronomy Ghent University GhentB-9000 Belgium Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Universität Bonn Helmholtz-Institut für Strahlen- und Kernphysik Bonn53115 Germany Theory Center Thomas Jefferson National Accelerator Facility 12000 Jefferson Avenue Newport NewsVA23606 United States School of Informatics and Computing Indiana University BloomingtonIN47405 United States

We show that, in the Regge limit, beam asymmetries in η and η0 photoproduction are sensitive to hidden strangeness components. Under reasonable assumptions about the couplings we estimate the contribution of the φ Regge pole, which is expected to be the dominant hidden strangeness contribution. The ratio of the asymmetries in η0 and η production is estimated to be close to unity in the forward region 0 2 ≤ 1 at the photon energy Elab = 9 GeV, relevant for the upcoming measurements at Jefferson Lab. Copyright © 2017, The Authors. All rights reserved.

关键词： Germanium alloys

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Radar interferometry based settlement monitoring in tunnelling: Visualisation and accuracy analyses

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Visualization in Engineering 2016年第1期4卷 1-16页

作者： Schindler, Steffen Hegemann, Felix Koch, Christian König, Markus Mark, Peter HOCHTIEF Engineering GmbH Consult IKS Energy Lyoner Straße 25 Frankfurt am Main 60528 Germany Chair of Computing in Engineering Faculty of Civil and Environmental Engineering Ruhr-Universität Bochum Universitätstraße 150 Bochum 44801 Germany Centre for Structural Engineering and Informatics University of Nottingham University Park Nottingham NG7 2RD United Kingdom Institute of Concrete Structures Faculty of Civil and Environmental Engineering Ruhr-Universität Bochum Universitätstraße 150 Bochum 44801 Germany

Background: The accurate, efficient and economical monitoring of settlements caused by tunnel boring machines, especially in regions of particular interest such as critical inner city areas, has become an important aspect of the tunnelling operation. Besides conventional terrestrial based methods to capture settlements, satellite based techniques that can accurately determine displacements remotely, are increasingly being used to augment standard terrestrial measurements. However, not much attention has been paid to analyse the accuracy of satellite based measurement data. In addition, there is also a lack of studies on how to visualise the resulting huge amount of data in the context of both the tunnel advancement and the existing building infrastructure. Methods: This paper introduces the basics of settlement monitoring using radar interferometry methods, in particular showing the results obtained by processing radar images from the TerraSAR-X satellite to monitor a downtown construction site in Düsseldorf, Germany, where a new underground line (“Wehrhahn-Linie”) is being built. By comparing terrestrial measurements with remote satellite based settlement data in temporal and spatial corridors, the accuracy of the radar interferometry method is shown. Moreover, a 4D visualisation concept is presented that correlates satellite and terrestrial based settlement data correlated with above-ground buildings and boring machine performance parameters within a Virtual Reality (VR) environment. Results: By comparing up to 23,000 pairs of satellite and terrestrial based settlement data points of a real tunnelling project an accuracy of about ±1.5 mm in the measurement of deformation using the method of radar interferometry in urban areas can be stated. In addition, providing a visual analysis of data sources within a VR environment, the accuracy of terrestrial and satellite-based measurements can be visualised in different time steps. Sources of error that affect the degree o

关键词： Accuracy analysis Mechanised tunnelling Settlement monitoring Settlement visualisation

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Finite-energy sum rules in eta photoproduction off a nucleon

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Physical Review D 2017年第3期95卷 034014-034014页

作者： J. Nys V. Mathieu C. Fernández-Ramírez A. N. Hiller Blin A. Jackura M. Mikhasenko A. Pilloni A. P. Szczepaniak G. Fox J. Ryckebusch Department of Physics and Astronomy Ghent University B-9000 Ghent Belgium Center for Exploration of Energy and Matter Indiana University Bloomington Indiana 47403 USA Physics Department Indiana University Bloomington Indiana 47405 USA Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México 04510 Mexico Departamento de Física Teórica and IFIC Centro Mixto Universidad de Valencia-CSIC Institutos de Investigación de Paterna E-46071 Valencia Spain Universität Bonn Helmholtz-Institut für Strahlen- und Kernphysik 53115 Bonn Germany Theory Center Thomas Jefferson National Accelerator Facility Newport News Virginia 23606 USA School of Informatics and Computing Indiana University Bloomington Indiana 47405 USA

The reaction γN→ηN is studied in the high-energy regime (with photon lab energies Eγlab>4 GeV) using information from the resonance region through the use of finite-energy sum rules. We illustrate how analyticity allows one to map the t dependence of the unknown Regge residue functions. We provide predictions for the energy dependence of the beam asymmetry at high energies.

关键词： Particle interactions Photon & charged-lepton interactions with hadrons Resonance reactions

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Features of πΔ photoproduction at high energies

arXiv

引用

arXiv 2017年

作者： Nys, J. Mathieu, V. Fernández-Ramírez, C. Jackura, A. Mikhasenko, M. Pilloni, A. Sherrill, N. Ryckebusch, J. Szczepaniak, A.P. Fox, G. Department of Physics and Astronomy Ghent University GhentB-9000 Belgium Physics Department Indiana University BloomingtonIN47405 United States Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States George Washington University WashingtonDC20052 United States Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Universität Bonn Helmholtz-Institut für Strahlen- und Kernphysik Bonn53115 Germany School of Informatics Computing and Engineering Indiana University BloomingtonIN47405 United States

Hybrid/exotic meson spectroscopy searches at Jefferson Lab require the accurate theoretical de- scription of the production mechanism in peripheral photoproduction. We develop a model for πΔ photoproduction at high energies (5 ≤ Elab≤ 16 GeV) that incorporates both the absorbed pion and natural-parity cut contributions. We fit the available observables, providing a good description of the energy and angular dependencies of the experimental data. We also provide predictions for the photon beam asymmetry of charged pions at Elab= 9 GeV which is expected to be measured by GlueX and CLAS12 experiments in the near future. Copyright © 2017, The Authors. All rights reserved.

关键词： Germanium alloys

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PennyLane: Automatic differentiation of hybrid quantum-classical computations

arXiv

引用

arXiv 2018年

作者： Bergholm, Ville Izaac, Josh Schuld, Maria Gogolin, Christian Ahmed, Shahnawaz Ajith, Vishnu Alam, M. Sohaib Alonso-Linaje, Guillermo AkashNarayanan, B. Asadi, Ali Arrazola, Juan Miguel Azad, Utkarsh Banning, Sam Blank, Carsten Bromley, Thomas R. Cordier, Benjamin A. Ceroni, Jack Delgado, Alain Matteo, Olivia Di Dusko, Amintor Garg, Tanya Guala, Diego Hayes, Anthony Hill, Ryan Ijaz, Aroosa Isacsson, Theodor Ittah, David Jahangiri, Soran Jain, Prateek Jiang, Edward Khandelwal, Ankit Kottmann, Korbinian Lang, Robert A. Lee, Christina Loke, Thomas Lowe, Angus McKiernan, Keri Meyer, Johannes Jakob Montañez-Barrera, J.A. Moyard, Romain Niu, Zeyue O’Riordan, Lee James Oud, Steven Panigrahi, Ashish Park, Chae-Yeun Polatajko, Daniel Quesada, Nicolás Roberts, Chase Sá, Nahum Schoch, Isidor Shi, Borun Shu, Shuli Sim, Sukin Singh, Arshpreet Strandberg, Ingrid Soni, Jay Száva, Antal Thabet, Slimane Vargas-Hernández, Rodrigo A. Vincent, Trevor Vitucci, Nicola Weber, Maurice Wierichs, David Wiersema, Roeland Willmann, Moritz Wong, Vincent Zhang, Shaoming Killoran, Nathan Xanadu 777 Bay Street Toronto Canada Wallenberg Centre for Quantum Technology Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg412 96 Sweden Indian Institute of Information Technology Kottayam India NASA Ames Research Center Moffett FieldCA94035 United States Mountain ViewCA94043 United States data cybernetics Martin-Kolmsperger-Str 26 Landsberg86899 Germany Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University PortlandOR97202 United States Dept. of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Physics Indian Institute of Technology Roorkee Uttarakhand Roorkee India qBraid 5235 South Harper Court ChicagoIL60615 United States Factal Analytics Level 2 Chimes Building Plot 61 Sector - 44 Haryana Gurgaon122003 India Centre for High Energy Physics Indian Institute of Science Karnataka Bengaluru560012 India ICFO - Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Av. Carl Friedrich Gauss 3 Castelldefels Barcelona08860 Spain Chemical Physics Theory Group Department of Chemistry University of Toronto Canada DUG Technology 76 Kings Park Rd West PerthWA6005 Australia Rigetti Computing 2919 Seventh Street BerkeleyCA94710 United States Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute for Advanced Simulation Jülich Supercomputing Centre Forschungszentrum Jülich Jülich52425 Germany University of Amsterdam Netherlands School of Physical Sciences National Institute of Science Education and Research HBNI Odisha Jatni752 050 India Cervest United Kingdom Centro Brasileiro de Pesquisas Físicas Rua Dr. Xavier Sigaud 150 Rio de Janeiro22290-180 Brazil Zurich8092 Switzerland Neo4j UK Ltd United Kingdom Zapata Computing Inc. United States ITC Infotech Bangalore India Department of Microtechnology and Nanoscienc

PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices, supporting both qubit and continuous-variable paradigms. PennyLane’s core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation. PennyLane thus extends the automatic differentiation algorithms common in optimization and machine learning to include quantum and hybrid computations. A plugin system makes the framework compatible with any gate-based quantum simulator or hardware. We provide plugins for hardware providers including the Xanadu Cloud, Amazon Braket, and IBM Quantum, allowing PennyLane optimizations to be run on publicly accessible quantum devices. On the classical front, PennyLane interfaces with accelerated machine learning libraries such as TensorFlow, PyTorch, JAX, and Autograd. PennyLane can be used for the optimization of variational quantum eigensolvers, quantum approximate optimization, quantum machine learning models, and many other applications. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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Author Correction: Proton acceleration in thermonuclear nova explosions revealed by gamma rays

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Nature Astronomy 2022年 760页

作者： V. A. Acciari J. Becerra González E. Colombo R. J. García López J. Herrera A. López-Oramas C. Maggio V. Moreno M. Nievas Rosillo J. Otero-Santos G. Vanzo M. Vazquez Acosta S. Ansoldi B. De Lotto A. Donini F. Longo D. Miceli M. Palatiello M. Persic L. A. Antonelli C. Bigongiari S. Covino V. D’Elia F. Dazzi A. Lamastra F. Leone S. Lombardi L. Maraschi L. Nava S. Paiano C. Righi F. G. Saturni A. Stamerra F. Tavecchio A. Tutone A. Biland S. Fukami M. Artero O. Blanch S. M. Colak M. Delfino J. Delgado E. Do Souto Espiñeira L. Fariña Alonso L. Jouvin D. Kerszberg M. Martínez A. Moralejo E. Moretti C. Nigro C. Priyadarshi J. Rico K. Asano D. Hadasch M. Hütten T. Inada Y. Iwamura Y. Kobayashi D. Mazin K. Noda Y. Ohtani T. Saito S. Sakurai J. Sitarek M. Strzys M. Takahashi R. Takeishi M. Teshima I. Vovk D. Baack H. Bökenkamp D. Elsaesser A. Fattorini L. Linhoff S. Mender W. Rhode K. Schmidt A. Babić Ž. Bošnjak S. Cikota A. Baquero J. A. Barrio J. L. Contreras M. V. Fonseca J. Hoang M. López-Moya A. Mas Aguilar T. Miener D. Morcuende P. Peñil U. Barres de Almeida B. Machado de Oliveira Fraga I. Batković M. Bernardos G. Busetto A. De Angelis M. Doro R. López-Coto M. Mallamaci M. Mariotti E. Prandini A. Spolon W. Bednarek P. Gliwny K. Ishio D. Sobczynska L. Bellizzi S. Menchiari J. M. Miranda R. Paoletti S. Truzzi S. Ventura C. Wunderlich E. Bernardini W. Bhattacharyya M. Garczarczyk K. Satalecka A. Arbet Engels A. Berti J. Besenrieder G. Ceribella Y. Chai G. D’Amico C. Fruck J. G. Green D. Green A. Hahn L. Heckmann R. Mirzoyan D. Paneque M. Pihet T. Schweizer D. Strom J. van Scherpenberg M. Will G. Bonnoli R. Carosi P. Da Vela P. G. Prada Moroni A. Rugliancich M. Cerruti E. Molina J. M. Paredes M. Ribó A. Chilingarian J. Cortina C. Delgado Mendez T. Hassan I. Jiménez Martínez A. Del Popolo D. Depaoli F. Di Pierro C. F. Vigorito L. Di Venere N. Giglietto F. Giordano S. Loporchio D. Dominis Prester M. Manganaro S. Mićanović L. Pavletić T. Terzić D. Dorner K. Mannheim B. Schleicher V. Fallah Ramazani J. Jormanainen E. Lindfors Instituto de Astrofísica de Canarias and Dpto. de Astrofísica Universidad de La Laguna La Laguna Tenerife Spain Departament de Física and CERES-IEEC Universitat Autònoma de Barcelona Bellaterra Spain Università di Udine and INFN Trieste Udine Italy International Center for Relativistic Astrophysics (ICRA) Rome Italy Dipartimento di Fisica Università di Trieste Trieste Italy Laboratoire d’Annecy de Physique des Particules (LAPP) CNRS-IN2P3 Annecy Cedex France INAF Trieste and Dept. of Physics and Astronomy University of Bologna Bologna Italy National Institute for Astrophysics (INAF) Rome Italy ETH Zürich Zürich Switzerland Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology (BIST) Bellaterra Barcelona Spain Port d’Informació Científica (PIC) Bellaterra Barcelona Spain Japanese MAGIC Group: Institute for Cosmic Ray Research (ICRR) The University of Tokyo Kashiwa Chiba Japan Max-Planck-Institut für Physik München Germany Technische Universität Dortmund Dortmund Germany Croatian MAGIC Group: University of Zagreb Faculty of Electrical Engineering and Computing (FER) Zagreb Croatia IPARCOS Institute and EMFTEL Department Universidad Complutense de Madrid Madrid Spain Department of Astronomy University of California Berkeley Berkeley CA USA Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro RJ Brazil Università di Padova and INFN Padova Italy University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz Poland Università di Siena and INFN Pisa Siena Italy Deutsches Elektronen-Synchrotron (DESY) Zeuthen Germany Department for Physics and Technology University of Bergen Bergen Norway Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada Spain Università di Pisa and INFN Pisa Pisa Italy University of Innsbruck Innsbruck Austria Universitat de Barcelona ICCUB IEEC-UB Barcelona Spain Armenian MAGIC Group: A. Alikhanyan National Science Labo

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Full diffusion history reconstruction in networks

Full diffusion history reconstruction in networks

引用

IEEE International Conference on Big Data

作者： Zhen Chen Hanghang Tong Lei Ying School of Electrical Computer and Energy Engineering School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe Arizona

Diffusion processes in networks can be used to model many real-world processes. Analysis of diffusion traces can help us answer important questions such as the source of diffusion and the role of each node in the diffusion process. However, in large-scale networks, it is very expensive if not impossible to monitor the entire network to collect the complete diffusion trace. This paper considers diffusion history reconstruction from a partial observation and develops a greedy, step-by-step reconstruction algorithm. It is proved that the algorithm always produces a diffusion history that is consistent with the partial observation. Our experimental results based on real networks and real diffusion data show that the algorithm significantly outperforms some existing methods.

关键词： History Diffusion processes TV Heuristic algorithms Algorithm design and analysis Silicon Approximation algorithms

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