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arXiv 2024年

作者： Cao, Zhen Aharonian, F. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Bian, W. Bukevich, A.V. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, 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. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, J.H. Fang, K. Feng, C.F. Feng, H. Feng, L. Feng, S.H. Feng, X.T. Feng, Y. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. Hasan, M. He, H.H. He, H.N. He, J.Y. He, Y. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Karpikov, I. Kuleshov, D. Kurinov, K. Li, 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 Liang, E.W. Liang, Y.F. Lin, S.J. Liu, 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. Luo, Q. Luo, Y. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, L.J. Pattarakijwanich, P. Pei, Z.Y. Qi, J.C. Qi, M.Y. Qiao, B.Q. Qin, J.J. Raza, A. Ruffolo, D. S'aiz, A. Saeed, M. Semikoz, D. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, D.X. University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Institute for Nuclear Research Russian Academy of Sciences Moscow117312 Russia Hebei Normal University Hebei Shijiazhuang050024 China University of Science and Technology of China Anhui Hefei230026 China State Key Laboratory of Particle Detection and Electronics China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Research Center for Astronomical Computing Zhejiang Laboratory Zhejiang Hangzhou311121 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China Key Laboratory of Radio Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai51900 China Sun Yat-sen University Guangdong Guangzhou510275 China Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China APC Universit'e Paris Cit'e CNRS IN2P3 CEA IRFU Observatoire de Paris Paris11

The interplanetary magnetic field (IMF) between the Sun and Earth is an extension of the solar magnetic field carried by the solar wind into interplanetary space. Monitoring variations in the IMF upstream of the Earth would provide very important information for the prediction of space weather effects, such as effects of solar storms and the solar wind, on human activity. In this study, the IMF between the Sun and Earth was measured daily for the first time using a cosmic-ray observatory. Cosmic rays mainly consist of charged particles that are deflected as they pass through a magnetic field. Therefore, the cosmic-ray Sun shadow, caused by high-energy charged cosmic rays blocked by the Sun and deflected by the magnetic field, can be used to explore the transverse IMF between the Sun and Earth. By employing the powerful kilometer-square array at the Large High Altitude Air Shower Observatory, the cosmic-ray Sun shadows were observed daily with high significance for the first time. The displacement of the Sun shadow measured in 2021 correlates well with the transverse IMF component measured in situ by spacecraft near the Earth, with a time lag of 3:31 ± 0:12 days. The displacement of the Sun shadow was also simulated using Parker’s classic IMF model, yielding a time lag of 2:06 ± 0:04 days. This deviation may provide valuable insights into the magnetic field structure, which can improve space weather research. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

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Detection of the 2021 Outburst of RS Ophiuchi with the LST-1 38

Detection of the 2021 Outburst of RS Ophiuchi with the LST-1

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38th International Cosmic Ray Conference, ICRC 2023

作者： Kobayashi, Yukiho Aguasca-Cabot, Arnau Bernardos Martín, María Isabel Green, David López-Coto, Rubén Abe, K. Abe, S. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Baxter, J. Becerra González, J. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Carrasco, M.S. Cassol, F. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Gasbarra, C. Gasparrini, D. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Iarlori, M. Imazawa, R. Inada, T. Inome, Y. Ioka, K. Iori, M. Ishio, K. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kohri, K. Kong, A. Kubo, H. Kushida, J. Lainez, M. Lamanna, G. Lamastra, A. Le Flour, T. Linhoff, M. Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Department of Physics Tokai University Japan EMFTEL department IPARCOS Universidad Complutense de Madrid Spain INAF - Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy The Barcelona Institute of Science and Technology Spain LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain CIEMAT Spain Department of Physics TU Dortmund University Germany INFN Sezione di Bari Politecnico di Bari Italy INAF - Osservatorio Astronomico di Brera Italy INFN Sezione di Trieste Università degli Studi di Udine Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Italy Aix Marseille Univ CNRS IN2P3 CPPM France INFN Sezione di Bari Università di Bari Italy INFN Sezione di Torino Italy Palacky University Olomouc Faculty of Science Czech Republic University of Alcalá UAH Spain Port d’Informació Científica Spain University of Rijeka Department of Physics Croatia Institute for Theoretical Physics and Astrophysics Universität Würzburg Germany Institut für Theoretische Physik Lehrstuhl IV: Plasma-Astroteilchenphysik Ruhr-Universität Boch

Novae are luminous explosions in close binaries which host a white dwarf and a companion donor star. They are triggered by a thermonuclear runaway when the white dwarf accretes a critical amount of matter from the secondary. Though novae are established as high-energy gamma-ray emitters through observations by the Fermi Large Area Telescope (LAT), the origin of the gamma-ray emission, whether it is hadronic or leptonic, had been under intense debate until very recently. RS Ophiuchi (RS Oph) is a well-known recurrent symbiotic nova with a recurrence time scale of 15 years. The most recent outburst of RS Oph in 2021 brought the first detection of very-high-energy (VHE) gamma rays from a nova ever. The first Large-Sized Telescope prototype (LST-1) of the Cherenkov Telescope Array observed this historic event along with H.E.S.S. and MAGIC. The LST-1 observations in the first days after the burst onset show a clear VHE gamma-ray signal from RS Oph. The low energy threshold of LST-1 allows us to reconstruct the RS Oph gamma-ray spectrum down to ∼30 GeV, providing the best connection of the VHE gamma-ray data to the Fermi LAT energy range. The results from the analysis of the LST-1 observations are consistent with those obtained with H.E.S.S. and MAGIC, and also support a hadronic origin for the observed gamma-ray fluxes. In this contribution, we will present the analysis results of the LST-1 observations of the 2021 outburst of RS Oph. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： White dwarfs

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Low energy performance boost through a hardware stereoscopic trigger between CTA LST-1 and MAGIC 38

Low energy performance boost through a hardware stereoscopic...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Baxter, J. Barrio, J.A. Bitossi, M. Donini, A. Mazin, D. Paoletti, R. Pérez Aguilera, A. Tejedor Álvarez, L.Á. Abe, H. Abe, K. Abe, S. Abhir, J. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Aniello, T. Ansoldi, S. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Cornelia, A. Artero, M. Asano, K. Aubert, P. Baack, D. Babić, A. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Besenrieder, J. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Biland, A. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bošnjak, Ž. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Busetto, G. Campoy-Ordaz, A. Cardillo, M. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.S. Carretero-Castrillo, M. Cassol, F. Castro-Tirado, A.J. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chilingarian, A. Chytka, L. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Costantini, H. Covino, S. D’Amico, G. Dalchenko, M. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delfino, M. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Del Popolo, A. Depaoli, D. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Fariña, L. Fattorini, A. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Font, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Garczarczyk, M. Gasbarra, C. Gasparrini, D. Gasparyan, S. Gaug, M. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid Spain Sezione di Pisa Pisa56127 Italy Osservatorio Astronomico di Roma Italy Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Università degli Studi di Siena via Roma 56 Siena53100 Italy Department of Physics Tokai University Japan ETH Zürich Switzerland Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía-CSIC Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain Italy INFN Sezione di Trieste Università degli Studi di Udine Italy Italy INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy The Barcelona Institute of Science and Technology Spain LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Department of Physics TU Dortmund University Germany Croatia Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil Faculty of Physics and Applied Informatics University of Lodz Poland CIEMAT Spain INFN Sezione di Bari Politecnico di Bari Italy INAF Osservatorio Astronomico di Brera Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Departament de Física CERES-IEEC Universitat Autónoma de Barcelona Spain Italy Università di Pisa INFN Pisa Italy Aix Marseille Univ CNRS IN2P3 CPPM France INFN Sezione di Bari Università di Bari Italy INFN Sezione di Torino Italy ICRANet-Armenia at

The next generation facility for gamma-ray ground-based observations is the Cherenkov Telescope Array (CTA) observatory, which comprises three types of imaging atmospheric Cherenkov telescopes (IACTs). The Large-Sized Telescopes (LSTs) of CTA are the largest telescope type with a mirror dish of 23 m diameter. They cover the low energy end of the accessible gamma-ray energies for IACTs, starting from about 20 GeV up to a few TeV. The first LST prototype, known as LST-1, was officially inaugurated at the Observatorio del Roque de Los Muchachos in La Palma (Canary Islands, Spain) in 2018 and has since performed calibration observations of various known gamma-ray sources. Additionally, the site houses the MAGIC telescopes, two 17 m IACTs situated approximately 100 m away from LST-1, which have been performing stereo observations since 2009. Currently, joint observations between LST-1 and MAGIC are being carried on, and the data taken independently by the two IACT systems is analyzed by combining events via software. However, this method increases the energy threshold, as it discards all but the relatively high-energy events triggered by all three telescopes. To address this issue, we have developed a novel hardware stereo trigger system between LST-1 and MAGIC, which is capable of handling events triggered by any-two out of the three telescopes. In this contribution, we will report on the performance estimation of joint LST-1 and MAGIC observations using the hardware trigger. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Performance of the Large-Sized Telescope prototype of the Cherenkov Telescope Array 38

Performance of the Large-Sized Telescope prototype of the Ch...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Morcuende, D. López-Coto, R. Moralejo, A. Nozaki, S. Vuillaume, T. Abe, K. Abe, S. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Baxter, J. Becerra González, J. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Carrasco, M.S. Cassol, F. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Gasbarra, C. Gasparrini, D. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Iarlori, M. Imazawa, R. Inada, T. Inome, Y. Ioka, K. Iori, M. Ishio, K. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kohri, K. Kong, A. Kubo, H. Kushida, J. Lainez, M. Lamanna, G. Lamastra, A. Le Flour, T. Linhoff, M. Longo, F. López-Oramas, A. IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Univ. Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules IN2P3 Annecy74000 France Department of Physics Tokai University Japan Institute for Cosmic Ray Research University of Tokyo Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain CIEMAT Spain Department of Physics TU Dortmund University Germany INFN Sezione di Bari Politecnico di Bari Italy INAF Osservatorio Astronomico di Brera Italy INFN Sezione di Trieste Università degli Studi di Udine Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Italy Aix Marseille Univ CNRS IN2P3 CPPM France INFN Sezione di Bari Università di Bari Italy INFN Sezione di Torino Italy Palacky University Olomouc Faculty of Science Czech Republic University of Alcalá UAH Spain Port d’Informació Científica Spain University of Rijeka Department of Physics Croatia Institute for Theoretical Physics and Astrophysics Universität W

The next-generation ground-based gamma-ray Cherenkov Telescope Array Observatory (CTAO) will consist of imaging atmospheric Cherenkov telescopes (IACTs) of three different sizes distributed in two sites. The Large-Sized Telescopes will cover the low-energy end of the CTA energy range, starting at about 20 GeV. After its first years of operation at the CTA northern site, the Large-Sized Telescope prototype (LST-1) is in the final stage of its commissioning phase, having collected a significant amount of scientific data to date. In this contribution, we present the physics performance of the telescope using low-zenith Crab Nebula observations and Monte Carlo simulations fine-tuned accordingly. We show performance figures of merit such as the energy threshold, effective area, energy and angular resolution, and sensitivity based on the standard Hillas-parameters approach and following the source-independent and dependent analysis methods. The analysis threshold is estimated at 30 GeV. The energy resolution is around 30%, and the angular resolution is 0.3 degrees at 100 GeV. The best integral sensitivity of LST-1 is about 1.1% of the Crab Nebula flux above 250 GeV for 50 hours of observations. We also show the spectral energy distribution and light curve from Crab Nebula observations, which agree with results from other IACTs and link smoothly with Fermi-LAT when considering statistical and systematic uncertainties near the energy threshold. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Shellfish

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Network Model with Application to Allergy Diseases

arXiv

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arXiv 2023年

作者： Furmańczyk, Konrad Niemiro, Wojciech Chrzanowska, Mariola Zalewska, Marta Department of Applied Mathematics Institute of Information Technology Warsaw University of Life Sciences Poland Department of Prevention of Environmental Hazards Allergology and Immunology Medical University of Warsaw Poland Faculty of Mathematics Informatics and Mechanics University of Warsaw Poland Faculty of Mathematics and Computer Science Nicolaus Copernicus University Torun Poland Department of Statistics and Econometrics Institute of Economics and Finance Warsaw University of Life Sciences Poland

We propose a new graphical model to describe the comorbidity of allergic diseases. We present our model in two versions. First, we introduce a generative model that correctly reflects the variables’ causal relationship. Then we propose an approximation of the generative model by another misspecified model that is computationally more efficient and easily interpretable. We will focus on the misspecified version, which we consider more practical. We include in the model two directed graphs, one graph of known dependency between the main binary variables (diseases), and a second graph of the dependence between the occurrence of the diseases and their symptoms. In the model, we also consider additional auxiliary variables. The proposed model is evaluated on a cross-sectional multicentre study in Poland on the ECAP database (***). An assessment of the stability of the proposed model was obtained using bootstrap and jackknife techniques. Copyright © 2023, The Authors. All rights reserved.

关键词： Bayesian networks

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Linguistic Relational Database Systems with a Unified Formalism Representing Different Data Types by Their Neighborhoods

SSRN

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SSRN 2023年

作者： Nguyen, Cat Ho Huynh, Van Nam Nguyen, Minh Nhat Pham, Dinh Phong Hoang, Van Thong Doan, Van Ban Le, Nguyen Bao Nguyen, Gia Nhu School of Computer Science Duy Tan University 254 Nguyen Van Linh Thanh Khe Da Nang City550000 Viet Nam Japan Advanced Institute of Science and Technology Ishikawa Japan Information Technology Department Duy Tan University K7/25 Quang Trung Da Nang City550000 Viet Nam Faculty of Information Technology University of Transport and Communications 3 Cau Giay street Dong Da Hanoi1000000 Viet Nam Institute of Information Technology Vietnam Academy of Science and Technology 18 Hoang Quoc Viet Ha Noi 1000000 Vietnam1000000 Viet Nam Institute of Theoretical and Applied Research Duy Tan University Hanoi1000000 Viet Nam Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

Many approaches are established based on different formalisms to develop database models for uncertain data, like the similarity-based approach, the fuzzy set theory, or the possibility theory. However, no database models can deal with numeric and linguistic data with intrinsic qualitative semantics and their inherent interactions and can handle linguistic queries in a proper formalism established based on the data’ topological neighborhood systems. For dealing with such datatypes, the study proposes a so-called linguistic database model, which requires equipping a formalism established based on an axiomatic formalization and quantification of the domains of the linguistic attributes. Such a formalism is essential for simulating the human domain expert’s capability in handling words and their inherent relationships with the attributes’ numeric values. It permits running with the data semantics of different types, including ordinary, linguistic, incomplete, and null values, in a unified formalism using the so-called uncertain (lambda,rho)-comparators, =_(lambda,rho), ==_(lambda,rho), _(lambda,rho), where the integer pair (lambda,rho) indicates the uncertain comparators degree. Since the qualitative semantics of the words is specific, sophisticated, and entirely different from the ordinary datatypes, it demands equipping the proposed linguistic database with a particular metadata component to manage different multi-aspect linguistic semantics. © 2023, The Authors. All rights reserved.

关键词： Comparators (optical)

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Characterization of two electronic subsystems in cuprates through optical conductivity

arXiv

引用

arXiv 2022年

作者： Kumar, C.M.N. Akrap, A. Homes, C.C. Martino, E. Klebel-Knobloch, B. Tabis, W. Barišić, O.S. Sunko, D.K. Barišić, N. Institute of Solid State Physics TU Wien Vienna1040 Austria Institute of Physics Bijenička cesta 46 ZagrebHR-10000 Croatia The Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences 152 Radzikowskiego Str. Krakow31-342 Poland Department of Physics University of Fribourg Chemin du Musée 3 FribourgCH-1700 Switzerland Condensed Matter Physics and Materials Science Department Brookhaven National Laboratory UptonNY11973 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States LausanneCH-1015 Switzerland AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow30-059 Poland Department of Physics Faculty of Science University of Zagreb Bijenička cesta 32 ZagrebHR-10000 Croatia

Understanding the physical properties of unconventional superconductors as well as of other correlated materials presents a formidable challenge. Their unusual evolution with doping, frequency, and temperature has frequently led to non-Fermi-liquid (non-FL) interpretations. Optical conductivity is a major challenge in this context. Here, the optical spectra of two archetypal cuprates, underdoped HgBa2CuO4+δ and optimally-doped Bi2Sr2CaCu2O8+δ, are interpreted based on the standard Fermi liquid (FL) paradigm. At both dopings, perfect frequency-temperature FL scaling is found to be modified by the presence of a second, gapped electronic subsystem. This non-FL component emerges as a well-defined mid-infrared spectral feature after the FL contribution—determined independently by transport—is subtracted. Temperature, frequency, and doping evolution of the MIR feature identify a gapped rather than dissipative response. In contrast, the dissipative response is found to be relevant for pnictides and ruthenates. Such an unbiased FL/non-FL separation is extended across the cuprate phase diagram, capturing all the key features of the normal state and providing a natural explanation why the superfluid density is attenuated on the overdoped side. Thus, we obtain a unified interpretation of optical responses and transport measurements in all analyzed physical regimes and all analyzed compounds. © 2022, CC BY.

关键词： Fermi liquids

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NMR Spectra Denoising with Vandermonde Constraints

arXiv

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arXiv 2023年

作者： Guo, Di Xu, Runmin Wu, Jinyu Lin, Meijin Du, Xiaofeng Qu, Xiaobo School of Computer and Information Engineering Fujian Engineering Research Center for Medical Data Mining and Application Xiamen University of Technology Xiamen361024 China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China Department of Applied Marine Physics and Engineering Xiamen University Xiamen361102 China

Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool to analyze chemicals and proteins in bioengineering. However, NMR signals are easily contaminated by noise during the data acquisition, which can affect subsequent quantitative analysis. Therefore, denoising NMR signals has been a long-time concern. In this work, we propose an optimization model-based iterative denoising method, CHORD-V, by treating the time-domain NMR signal as damped exponentials and maintaining the exponential signal form with a Vandermonde factorization. Results on both synthetic and realistic NMR data show that CHORD-V has a superior denoising performance over typical Cadzow and rQRd methods, and the state-of-the-art CHORD method. CHORD-V restores low-intensity spectral peaks more accurately, especially when the noise is relatively high. © 2023, CC BY.

关键词： Nuclear magnetic resonance spectroscopy

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A Hybrid Deep Learning Paradigm for Robust Feature Extraction and Classification for Cataracts

Applied AI Letters

引用

applied AI Letters 2025年第2期6卷

作者： Ramakrishnan, Akshay Bhuvaneswari Madavan, Mukunth Manikandan, R. Gandomi, Amir H. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD United States Mukunth Madhavan AI Security Engineer Banglore India School of Computing SASTRA Deemed University Thanjavur India Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary Department of Computer Science Khazar University Baku Azerbaijan

The study suggests using a hybrid convolutional neural networks-support vector machines architecture to extract reliable characteristics from medical images and classify them as an ensemble using four different models. Manual processing of fundus images for the automated identification of ocular disorders is laborious, error-prone, and time-consuming. This necessitates computer-assisted technologies that can automatically identify different ocular illnesses from fundus images. The interpretation of the photos also plays a massive role in the diagnosis. Automating the diagnosing procedure reduces human mistakes and helps with early cataract detection. The oneDNN library available in the oneAPI Environment provided by Intel has been used to optimize all transfer learning models for better performance. The suggested approach is verified through a range of metrics in experiments using the openly accessible Ocular Disease Intelligent Recognition dataset. The MobileNet Model outperformed other transfer learning techniques with an accuracy of 0.9836. © 2025 The Author(s). applied AI Letters published by John Wiley & Sons Ltd.

关键词： cataract computer-assisted fundus hybrid ocular oneAPI oneDNN transfer learning

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ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces

arXiv

引用

arXiv 2022年

作者： Ali, Omair Saif-Ur-Rehman, Muhammad Glasmachers, Tobias Iossifidis, Ioannis Klaes, Christian Faculty of Medicine Department of Neurosurgery University hospital Knappschaftskrankenhaus Bochum GmbH Germany Institut für Neuroinformatik Ruhr University Bochum Germany Department of Computer Science Ruhr-West University of Applied Science Mülheim an der Ruhr Germany Department of Electrical Engineering and Information Technology Ruhr-University Bochum Germany

Objective: Electroencephalography (EEG) and electromyography (EMG) are two noninvasive bio-signals, which are widely used in human machine interface (HMI) technologies (EEG-HMI and EMG-HMI paradigm) for the rehabilitation of physically disabled people. Successful decoding of EEG and EMG signals into respective control command is a pivotal step in the rehabilitation process. Recently, several Convolutional neural networks (CNNs) based architectures are proposed that directly map the raw time-series (EEG and EMG signal) into decision space (intended action of the user). Since CNNs are end-to-end learning algorithms, the process of meaningful features extraction and classification are performed simultaneously. However, these networks are tailored to the learn the expected characteristics of the given bio-signal. Henceforth, the implication of these algorithms is usually limited to single HMI paradigm. In this work, we addressed the question that can we build a single architecture which is capable of learning distinct features from different HMI paradigms and still successfully classify them. Approach: In this work, we introduce a single hybrid model called ConTraNet, which is based on CNN and Transformer architectures that is equally useful for EEG-HMI and EMG-HMI paradigms. ConTraNet uses CNN block to introduce inductive bias in the model and learn local dependencies, whereas the Transformer block uses the self-attention mechanism to learn the long-range or global dependencies in the signal, which are crucial for the classification of EEG and EMG signals. Main results: We evaluated and compared the ConTraNet with state-of-the-art methods on three publicly available datasets (BCI Competition IV dataset 2b, Physionet MI-EEG dataset, Mendeley sEMG dataset) which belong to EEG-HMI and EMG-HMI paradigms. ConTraNet outperformed its counterparts in all the different category tasks (2-class, 3-class, 4-class, and 10-class decoding tasks). Significance: Most HMI studies introd

关键词： Electroencephalography

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