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IEEE International Conference on Computational Photography

作者： Vadim Holodovsky Yoav Y. Schechner Anat Levin Aviad Levis Amit Aides Viterbi Faculty of Electrical Engineering Technion - Israel Inst. Technology Dept. Mathematics and Computer Science Weizmann Inst. Science

ISBN: (纸本)9781467386241

To recover the three dimensional (3D) volumetric matter distribution in an object, the object is imaged from multiple directions and locations. Using these images, tomographic computations seek the distribution. When scattering is significant and under constrained irradiance, tomography must explicitly account for off-axis scattering. Furthermore, tomographic recovery must function when imaging is done in-situ, as occurs in medical imaging and ground-based at-mospheric sensing. We formulate tomography that handles arbitrary orders of scattering, using a Monte-Carlo model. The model is highly parallelizable in our formulation. This can enable large scale rendering and recovery of volumetric scenes having a large number of variables. We solve stability and conditioning problems that stem from radiative transfer modeling in-situ.

关键词： Tomography Scattering Medical imaging broadcasting radiative transfer

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A Score Recommendation System Towards Automating Assessment In Professional Courses

A Score Recommendation System Towards Automating Assessment ...

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International Workshop on technology for Education, T4E

作者： Anirudh Kashi Sachin Shastri Akshay R. Deshpande Jawahar Doreswamy Gowri Srinivasa PES Center for Pattern Recognition Dept. of Computer Science and Engineering PES Inst. of Technology Bengaluru India Dept. of Information Science and Engineering PES Inst. of Technology Bengaluru India PES University Bengaluru India Dept. of Computer Science and Engineering PESIT Bangalore South Campus Bengaluru India

ISBN: (纸本)9781509061167

We present a preliminary version of an automated evaluation system that provides recommended scores for descriptive answers. The system is designed in the context of professional courses, such as from Applied Sciences, for questions that have an answer-key. The recommendation of a score is based on an analysis of the student's answer against.an answer-key that comprises key phrases of the solution and alternatives, if any. We rely on five algorithms from literature on natural language processing to assess various aspects of a student's answer, such as the quantity and extent of match between keywords in a student's answer and the answer-key, while ensuring merely verbatim comparisons are not performed. The similarity scores are then combined using machine learning to output a recommended score for the answer. The system learns weights for the output of each of the five methods to map these to a score based on training data, comprising questions with answer-keys, student answers from actual exams and the scores provided by course inst.uctors/ graders. It is noteworthy that the methods presented in this paper do not rely on any kind of a corpus or prior-knowledge that is subject-specific. Even though the accuracies are modest and improvements ought to be made to accommodate the kind of variety observed in students' answers, the avenue is a promising one towards enhancing learning assessment.

关键词： Mathematical model Logistics Semantics Plagiarism Dictionaries Matrix decomposition Frequency measurement

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Incentivization schemes for vehicle allocation in one-way vehicle sharing systems

Incentivization schemes for vehicle allocation in one-way ve...

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IEEE International Smart Cities Conference (ISC2)

作者： Alexandros Angelopoulos Damianos Gavalas Charalampos Konstantopoulos Damianos Kypriadis Grammati Pantziou School of Electrical & Computer Engineering Computer Technology Institute & Press “Diophantus” Patras Greece Dept. of Cultural Technology and Communication Institute & Press “Diophantus” Patras Greece Dept. of Informatics University of Piraeus Greece Dept. of Informatics & Telecommunications Institute & Press “Diophantus” Patras Greece Dept. of Informatics Computer Technology Institute & Press “Diophantus” Patras Greece

ISBN: (纸本)9781509018475

The major operational problem in one-way vehicle sharing systems is the vehicle stock imbalance problem. In this paper, we address this problem by proposing a new approach for dynamically allocating vehicles to users based on “incentivization” schemes which use reservations to coordinate supply-and-demand mismatches and price incentives for rewarding users, if they accept to pick up their vehicle from an oversupplied station and/or to drop off it to an under-supplied station. The system incentivizes users based on the priorities of vehicle relocations from station to station, taking into account the fluctuating demand for vehicles and parking places at different stations over time. We present two different schemes for incentivizing users to act in favour of the system. Both schemes consider budget constraints and are truthful and budget-feasible. We extensively evaluated our approach through simulations and observed significant improvements in the number of completed trips and system revenue.

关键词： Vehicles computers Resource management Presses informatics Legged locomotion Pricing

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Energy efficient context based forwarding strategy in named data networking of things 3

Energy efficient context based forwarding strategy in named ...

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3rd ACM International Conference on Information-Centric Networking, ACM-ICN 2016

作者： Lenord Melvix, J.S.M. Lokesh, Vikas Polyzos, George C. Dept. of Computer Science and Engineering Jacobs School of Engineering University of California San Diego San DiegoCA92093-0114 United States Mobile Multimedia Lab Dept. of Informatics School of Information Sciences and Technology Athens University of Economics and Business Evelpidon 47A Athens113 62 Greece

ISBN: (纸本)9781450344678

Named Data Networking (NDN) of Things has gathered interest among the Internet-of-Things (IoT) research community due to its hassle-free deployment and configurability. This approach to interconnecting devices provides the network with additional information about the data transported, which can be used for improved efficiency. This is one of the targets for mass IoT or Machine-to-Machine (M2M) communications modes of 5G. In this paper, we propose a context based forwarding strategy that makes forwarding decisions based on the tolerance to inaccuracies in data defined for the application requesting it. We also propose a modification to the hierarchical naming scheme by appending the name of the application generating the interest. In addition to faster context based forwarding, this modification simplifies the naming as it is easier to understand the context under which the interest was generated even with generic names. We demonstrate an improvement in energy efficiency of the system using the proposed technique compared to an IP based implementation. In addition, the proposed technique offers a platform to implement application level access control and Quality-of-Service support. ©2016 ACM.

关键词： Middleware

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SemEval-2016 task 5: Aspect based sentiment analysis 10

SemEval-2016 task 5: Aspect based sentiment analysis

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10th International Workshop on Semantic Evaluation, SemEval 2016

作者： Pontiki, Maria Galanis, Dimitrios Papageorgiou, Haris Androutsopoulos, Ion Manandhar, Suresh Al-Smadi, Mohammad Al-Ayyoub, Mahmoud Zhao, Yanyan Qin, Bing De Clercq, Orphée Hoste, Véronique Apidianaki, Marianna Tannier, Xavier Loukachevitch, Natalia Kotelnikov, Evgeny Bel, Nuria Jiménez-Zafra, Salud María Eryigit, Gülsen Institute for Language and Speech Processing Athena R.C. Athens Greece Dept. of Informatics Athens University of Economics and Business Greece Dept. of Computer Science University of York United Kingdom Computer Science Dept. Jordan University of Science and Technology Irbid Jordan Harbin Institute of Technology Harbin Heilongjiang China LT3 Ghent University Ghent Belgium LIMSI CNRS Univ. Paris-Sud Université Paris-Saclay Orsay France Lomonosov Moscow State University Moscow Russia Vyatka State University Kirov Russia Universitat Pompeu Fabra Barcelona Spain Dept. of Computer Science Universidad de Jaén Spain Dept. of Computer Engineering Istanbul Technical University Turkey

ISBN: (纸本)9781941643952

This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. From these datasets, 25 were for sentence-level and 14 for text-level ABSA;the latter was introduced for the first time as a subtask in SemEval. The task attracted 245 submissions from 29 teams. © 2016 Association for Computational Linguistics.

关键词： Sentiment analysis

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Search for Gamma-ray Spectral Lines from Dark Matter Annihilation up to 100 TeV towards the Galactic Center with MAGIC

arXiv

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arXiv 2022年

作者： Abe, H. Abe, S. Acciari, V.A. Aniello, T. Ansoldi, S. Antonelli, L.A. Engels, A. Arbet Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. de Almeida, U. Barres Barrio, J.A. Batković, I. Baxter, J. González, J. Becerra Bednarek, W. Bernardini, E. Bernardos, M. Berti, A. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Carosi, R. Carretero-Castrillo, M. Ceribella, G. Chai, Y. Chilingarian, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Mendez, C. Delgado Depaoli, D. Di Pierro, F. Di Venere, L. Espiñeira, E. Do Souto Prester, D. Dominis Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Ramazani, V. Fallah Fariña, L. Fattorini, A. Font, L. Fruck, C. Fukami, S. Fukazawa, Y. López, R.J. García Garczarczyk, M. Gasparyan, S. Gaug, M. Paiva, J.G. Giesbrecht Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Iotov, R. Ishio, K. Martínez, I. Jiménez Jormanainen, J. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. de Oliveira Fraga, B. Machado Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Aguilar, A. Mas Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Moreno, V. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Rosillo, M. Nievas Nigro, C. Nilsson, K. Nishijima, K. Ekoume, T. Njoh Noda, K. Nozaki, S. Ohtani, Y. Oka, T. Otero-Santos, J. Paiano, S. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. The University of Tokyo Chiba Kashiwa277-8582 Japan Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna La Laguna TenerifeE-38200 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Rome Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain ZeuthenD-15738 Germany ETH Zürich ZürichCH-8093 Switzerland Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Department for Physics and Technology University of Bergen Norway University of Innsbruck Institute for Astro and Particle Physics Austria INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy Bellaterra BarcelonaE-08193 Spain INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Department of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany University of Geneva Chemin d’Ecogia 16 VersoixCH-1290 Switzerland Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku T

Line-like features in TeV $\gamma$-rays constitute a ''smoking gun'' for TeV-scale particle dark matter and new physics. Probing the Galactic Center region with ground-based Cherenkov telescopes enables the search for TeV spectral features in immediate association with a dense dark matter reservoir at a sensitivity out of reach for satellite $\gamma$-ray detectors, and direct detection and collider experiments. We report on 223 hours of observations of the Galactic Center region with the MAGIC stereoscopic telescope system reaching $\gamma$-ray energies up to 100 TeV. We improved the sensitivity to spectral lines at high energies using large-zenith-angle observations and a novel background modeling method within a maximum-likelihood analysis in the energy domain. No line-like spectral feature is found in our analysis. Therefore, we constrain the cross section for dark matter annihilation into two photons to $\langle \sigma v \rangle \lesssim 5 \times 10^{-28}\,\mathrm{cm^3\,s^{-1}}$ at 1 TeV and $\langle \sigma v \rangle \lesssim 1 \times 10^{-25}\,\mathrm{cm^3\,s^{-1}}$ at 100 TeV, achieving the best limits to date for a dark matter mass above 20 TeV and a cuspy dark matter profile at the Galactic Center. Finally, we use the derived limits for both cuspy and cored dark matter profiles to constrain supersymmetric wino models. Copyright © 2022, The Authors. All rights reserved.

关键词： Galaxies

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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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Utilization of hybrid access femtocells during multicast transmissions in mobile networks

Utilization of hybrid access femtocells during multicast tra...

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European Conference on Networks and Communications (EuCNC)

作者： Christos Bouras Nikolaos Kanakis Vasileios Kokkinos Nikolaos Papachristos Demosthenes Vouyioukas Computer Engineering and Informatics Dept. Univ. of Patras Greece Computer Technology Institute & Press “Diophantus” Patras Greece Dept. of Information & Communication System Engineering Univ. of Aegean Greece

ISBN: (纸本)9781509028948

Femtocells enhance indoor coverage of mobile services using the owner's broadband connection. They were initially designed to serve a number of subscribed User Equipments within their range. This design however, resulted in underutilization of the femtocells resources, and simultaneously in high interference levels for nearby non-subscribed users. Nowadays, femtocells can support multicast transmissions, while their hybrid operation allows non-subscribed users to use a portion of their resources. In this paper we propose a novel mechanism that is based on the selection of the appropriate Modulation and Coding Scheme. The mechanism allows non-subscribed users to utilize a portion of the femtocells' resources for multicast transmissions when located inside their coverage, without affecting the owners' satisfaction. The simulation results show that depending on the portion of the femtocells' resources allocated to non-subscribed users, the mechanism may significantly increase the average user throughput.

关键词： Femtocells Throughput Interference Signal to noise ratio Macrocell networks Encoding

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Gamma/hadron discrimination using a small-WCD with four PMTs 37

Gamma/hadron discrimination using a small-WCD with four PMTs

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37th International Cosmic Ray Conference, ICRC 2021

作者： Conceição, R. Assis, P. Assunção, F. Bakalová, A. Barres de Almeida, U. Bom, C.R. Correia, J. De Angelis, A. Dias, L. González, B.S. Guillén, A. La Mura, G. Lourenço, N. Machado, P. Marques, S. Mendes, L. Pimenta, M. Shellard, R. Tomé, B. Vicha, J. Abreu, P. Albert, A. Angüner, E.O. Arcaro, C. Arnaldi, L.H. Arteaga-Velázquez, J.C. Batković, I. Bellido, J. Belmont-Moreno, E. Bisconti, F. Blanco, A. Bohacova, M. Bottacini, E. Bretz, T. Brisbois, C. Brogueira, P. Brown, A.M. Bulik, T. Caballero Mora, K.S. Campos, S.M. Chiavassa, A. Chytka, L. Consolati, G. Cotzomi Paleta, J. Dasso, S. De Bom, C.R. de la Fuente, E. de Souza, V. Depaoli, D. Di Sciascio, G. Dib, C.O. Dorner, D. Doro, M. Du Vernois, M. Ergin, T. Fan, K.L. Fraija, N. Funk, S. García, J.I. García-González, J.A. García Roca, S.T. Giacinti, G. Goksu, H. Guarino, F. Haist, F. Hansen, P.M. Harding, J.P. Hinton, J. Hofmann, W. Hona, B. Hoyos, D. Huentemeyer, P. Hueyotl-Zahuantitla, F. Insolia, A. Janecek, P. Joshi, V. Khelifi, B. Kunwar, S. Lapington, J. Laspiur, M.R. Leitl, F. Longo, F. Lopes, L. Lopez-Coto, R. Mandat, D. Mariazzi, A.G. Mariotti, M. Marques Moraes, A. Martínez-Castro, J. Martínez-Huerta, H. May, S. Melo, D.G. Mendes, L.F. Mendes, L.M. Mineeva, T. Mitchell, A. Mohan, S. Morales Olivares, O.G. Moreno-Barbosa, E. Nellen, L. Novotny, V. Olivera-Nieto, L. Orlando, E. Pech, M. Pichel, A. Portes de Albuquerque, M. Prandini, E. Rado Cuchills, M.S. Reisenegger, A. Reville, B. Rho, C.D. Rovero, A.C. Ruiz-Velasco, E. Salazar, G.A. Sandoval, A. Santander, M. Schoorlemmer, H. Schüssler, F. Serrano, V.H. Shellard, R.C. Sinha, A. Smith, A.J. Surajbali, P. Torres Aguilar, I. van Eldik, C. Vergara-Quispe, I.D. Viana, A. Vigorito, C.F. Wang, X. Werner, F. White, R. Zamalloa Jara, M.A. LIP - Laboratório de Instrumentação e Física Experimental de Partículas Lisbon Portugal IST - Instituto Superior Técnico Lisboa Portugal Department of Informatics Engineering CISUC University of Coimbra Coimbra Portugal Institute of Physics of the Czech Academy of Sciences Prague Czech Republic CBPF - Centro Brasileiro de Pesquisas Físicas Rio de Janeiro Brazil INFN Università di Padova Italy Computer Architecture and Technology Department University of Granada Granada Spain Av. Prof. Gama Pinto 2 Lisboa1649-003 Portugal Physics Division Los Alamos National Laboratory P.O. Box 1663 Los AlamosNM87545 United States Aix Marseille Univ CNRS IN2P3 CPPM 163 avenue de Luminy - Case 902 Marseillecedex 09 13288 France University of Padova Department of Physics and Astronomy INFN Padova Via Marzolo 8 Padova35131 Italy Centro Atómico Bariloche Comisión Nacional de Energía Atómica RN S. C. de Bariloche8400 Argentina Universidad Michoacana de San Nicolás de Hidalgo Calle de Santiago Tapia 403 Centro Mich. Morelia58000 Mexico FZU Institute of Physics of the Czech Academy of Sciences Na Slovance 1999/2 Praha 8182 00 Czech Republic Centro Brasileiro de Pesquisas Físicas R. Dr. Xavier Sigaud 150 RJ Rio de Janeiro22290-180 Brazil Av. de la Cultura 733 Pabellón CuscoC-358 Peru Instituto de Física Universidad Nacional Autónoma de México Sendero Bicipuma C.U. Coyoacán CDMX Ciudad de México04510 Mexico Dipartimento di Fisica Università degli Studi di Torino Via Pietro Giuria 1 Torino10125 Italy RWTH Aachen University Physics Institute 3 Otto-Blumenthal-Straße Aachen52074 Germany University of Maryland College ParkMD20742 United States Durham University Stockton Road DurhamDH1 3LE United Kingdom Astronomical Observatory University of Warsaw Aleje Ujazdowskie 4 Warsaw00478 Poland Facultad de Ciencias en Física y Matemáticas UNACH Boulevard Belisario Domínguez Km. 1081 Sin Número Terán Chiapas Tuxtla Gutiérrez Mexico Facultad de

The Southern Wide-field Gamma-ray Observatory (SWGO) is the next-generation gamma-ray observatory, currently in an R&D phase. The experiment is expected to have a large array of water Cherenkov detectors (WCD) placed at a high elevation (> 4.4 km a.s.l.) in South America. Here we present a WCD concept with reduced surface area and height of stations comprising four PMTs at the bottom. We show that it is possible to reach an excellent gamma/hadron discrimination by analysing the data gathered by this station with machine learning techniques. Such performance can be achieved by analysing the shower patterns at the ground or through the PMTs signal time structure to tag muons. Moreover, it is shown that the station's performance does not depend on the array configuration (dense or sparse) nor on the shower inclination (θ◦). Such a concept reduces the cost associated with the transport of massive amounts of water to high elevation sites while keeping a high physics performance. Therefore, it could be a good candidate station for SWGO, enabling to reach good sensitivities from low energies (∼ 100 GeV) up to the PeV region, covering large ground surface areas (few square km). © 2022 Sissa Medialab Srl. All rights reserved.

关键词： Observatories

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Long-term multi-wavelength study of 1ES 0647+250

arXiv

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arXiv 2022年

作者： Acciari, MAGIC Collaboration V.A. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Berti, A. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Carosi, R. Carretero-Castrillo, M. Ceribella, G. Chai, Y. Chilingarian, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do Souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Fallah Ramazani, V. Fariña, L. Fattorini, A. Font, L. Fruck, C. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Inada, T. Iotov, R. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Mas Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Moreno, V. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Nievas Rosillo, M. Nigro, C. Nilsson, K. Nishijima, K. Njoh Ekoume, T. Noda, K. Nozaki, S. Ohtani, Y. Oka, T. Otero-Santos, J. Paiano, S. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. Pavletić, L. Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna La LagunaE-38200 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain ZeuthenD-15738 Germany ETH Zürich ZürichCH-8093 Switzerland Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Department of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany University of Geneva Chemin d’Ecogia 16 VersoixCH-1290 Switzerland Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku TurkuFI-20014 Finland Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Japanese MAGIC Grou

Context. The BL Lac object 1ES 0647+250 is one of the few distant γ-ray emitting blazars detected at very high energies (VHEs;&100 GeV) during a non-flaring state. It was detected with the MAGIC telescopes during a period of low activity in the years 2009-2011 as well as during three flaring activities in the years 2014, 2019, and 2020, with the highest VHE flux in the last epoch. An extensive multi-inst.ument data set was collected as part of several coordinated observing campaigns over these years. Aims. We aim to characterise the long-term multi-band flux variability of 1ES 0647+250, as well as its broadband spectral energy distribution (SED) during four distinct activity states selected in four different epochs, in order to constrain the physical parameters of the blazar emission region under certain assumptions. Methods. We evaluated the variability and correlation of the emission in the different energy bands with the fractional variability and the Z-transformed discrete correlation function, as well as its spectral evolution in X-rays and γ rays. Owing to the controversy in the redshift measurements of 1ES 0647+250 reported in the literature, we also estimated its distance in an indirect manner through a comparison of the GeV and TeV spectra from simultaneous observations with Fermi-LAT and MAGIC during the strongest flaring activity detected to date. Moreover, we interpret the SEDs from the four distinct activity states within the framework of one-component and two-component leptonic models, proposing specific scenarios that are able to reproduce the available multi-inst.ument data. Results. We find significant long-term variability, especially in X-rays and VHE γ rays. Furthermore, significant (3-4σ) correlations were found between the radio, optical, and high-energy (HE) γ-ray fluxes, with the radio emission delayed by about ∼400 days with respect to the optical and γ-ray bands. The spectral analysis reveals a harder-when-brighter trend during the non-flar

关键词： Gamma rays

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