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arXiv 2024年

作者： Abusleme, Angel Adam, Thomas Adamowicz, Kai Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Beretta, Marco Bergnoli, Antonio Bick, Daniel Bieger, Lukas Biktemerova, Svetlana Birkenfeld, Thilo Blake, Iwan Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callier, Stéphane Calvez, Steven Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Cerrone, Vanessa Chang, Jinfan Chang, Yun Chatrabhuti, Auttakit Chen, Chao Chen, Guoming Chen, Pingping Chen, Shaomin Chen, Xin Chen, Yiming Chen, Yixue Chen, Yu Chen, Zelin Chen, Zhangming Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Cheng, Yu Chin Chepurnov, Alexander Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chin, Yen-Ting Chou, Po-Lin Chu, Ziliang Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Molla, Marta Colomer Di Lorenzo, Selma Conforti Coppi, Alberto Corti, Daniele Csakli, Simon Cui, Chenyang Corso, Flavio Dal Dalager, Olivia Datta, Jaydeep De La Taille, Christophe Deng, Zhi Deng, Ziyan Ding, Xiaoyu Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dittrich, Carsten Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dou, Wei Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Duan, Yujie Dugas, Katherine Dusini, Stefano Duyang, Hongyue Eck, Jessica Enqvist, Timo Fabbri, Andrea Fahrendholz, Ulrike Fan, Lei Fang, Jian Fang, Wenxing Fedoseev, Dmitry Feng, Li-Cheng Feng, Qichun Ferraro, Federico Fournier, Amélie Fritsch, Fritsch Gan, Haonan Gao, Feng Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco G Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil ANID Chile Pontificia Universidad Católica de Chile Santiago Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chengdu University of Technology Chengdu China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi’an Jiaotong University Xi’an China Xiamen University Xiamen China School of Physics and Microelectronics Zhengzhou University Z

We explore the bound neutrons decay into invisible particles (e.g., n → 3ν or nn → 2ν) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: n → inv and nn → inv. The invisible decays of s-shell neutrons in 12C will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino ν¯e, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are τ/B(n → inv) > 5.0 × 1031 yr and τ/B(nn → inv) > 1.4 × 1032 yr. Copyright © 2024, The Authors. All rights reserved.

关键词： Neutrons

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JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo

arXiv

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arXiv 2023年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad Aleem, Abid Alexandros, Tsagkarakis An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chan, Chi Chang, Jinfan Chang, Yun Chen, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Cheng, Yu Chin Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chu, Ziliang Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Di Lorenzo, Selma Conforti Corti, Daniele Corso, Flavio Dal Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dou, Wei Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Eck, Jessica Enqvist, Timo Fabbri, Andrea Fahrendholz, Ulrike Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fei, Zhengyong Feng, Li-Cheng Feng, Qichun Ferraro, Federico Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guan, Yuduo Guard Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil Pontificia Universidad Católica de Chile Santiago Chile Universidad Tecnica Federico Santa Maria Valparaiso Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi’an Jiaotong University Xi’an China Xiamen University Xiamen

We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande. © 2023, CC BY.

关键词： Annihilation

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Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

arXiv

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arXiv 2023年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad Aleem, Abid An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Beretta, Marco Bergnoli, Antonio Bick, Daniel Bieger, Lukas Biktemerova, Svetlana Birkenfeld, Thilo Morton-Blake, Iwan Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callier, Stéphane Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Cerrone, Vanessa Chan, Chi Chang, Jinfan Chang, Yun Chatrabhuti, Auttakit Chen, Chao Chen, Guoming Chen, Pingping Chen, Shaomin Chen, Yixue Chen, Yu Chen, Zhangming Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Cheng, Yu Chin Chepurnov, Alexander Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chin, Yen-Ting Chu, Ziliang Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Molla, Marta Colomer Di Lorenzo, Selma Conforti Coppi, Alberto Corti, Daniele Csakli, Simon Corso, Flavio Dal Dalager, Olivia Datta, Jaydeep De La Taille, Christophe Deng, Zhi Deng, Ziyan Ding, Xiaoyu Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dittrich, Carsten Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dou, Wei Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dugas, Katherine Dusini, Stefano Duyang, Hongyue Eck, Jessica Enqvist, Timo Fabbri, Andrea Fahrendholz, Ulrike Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fei, Zhengyong Feng, Li-Cheng Feng, Qichun Ferraro, Federico Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giudic Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil ANID Chile Pontificia Universidad Católica de Chile Santiago Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi'an Jiaotong University Xi'An China Xiamen University Xiamen China School of Physics and Microelectronics Zhengzhou University Zhengzhou China Institute of Physics National Ya

The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the univ.rse. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector currently under construction in South China. The real-time monitoring system is designed to ensure both prompt alert speed and comprehensive coverage of progenitor stars. It incorporates prompt monitors on the electronic board as well as online monitors at the data acquisition stage. Assuming a false alert rate of 1 per year, this monitoring system exhibits sensitivity to pre-SN neutrinos up to a distance of approximately 1.6 (0.9) kiloparsecs and SN neutrinos up to about 370 (360) kiloparsecs for a progenitor mass of 30 solar masses, considering both normal and inverted mass ordering scenarios. The pointing ability of the CCSN is evaluated by analyzing the accumulated event anisotropy of inverse beta decay interactions from pre-SN or SN neutrinos. This, along with the early alert, can play a crucial role in facilitating follow-up multi-messenger observations of the next galactic or nearby extragalactic CCSN. © 2023, CC BY.

关键词： Supernovae

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Automatic Knowledge Graph Construction: A Report on the 2019 ICDM/ICBK Contest

Automatic Knowledge Graph Construction: A Report on the 2019...

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IEEE International Conference on Data Mining (ICDM)

作者： Xindong Wu Jia Wu Xiaoyi Fu Jiachen Li Peng Zhou Xu Jiang Mininglamp Academy of Sciences Mininglamp Technology Beijing China Key Laboratory of Knowledge Engineering with Big Data (Hefei Univ. of Technology) Ministry of Education Hefei China Department of Computing Macquarie University Sydney Australia School of Computer Science and Technology Anhui University Hefei China

Automatic knowledge graph construction seeks to build a knowledge graph from unstructured text in a specific domain or cross multiple domains, without human intervention. IEEE ICDM 2019 and ICBK 2019 invited teams from both degree-granting institutions and industrial labs to compete in the 2019 Knowledge Graph Contest by automatically constructing knowledge graphs in at least two different domains. This article reports the outcomes of the Contest. The participants were expected to build a model to extract knowledge represented as triplets from text data and develop a web application to visualize the triplets. Awards were given to five teams. Their models and key techniques used to construct knowledge graphs are summarized.

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Study of b-hadron decays to Λ+c h-h′- final states

arXiv

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arXiv 2024年

作者： Aaij, R. Abellán Beteta, C. Ackernley, T. Adeva, B. Adinolfi, M. Afsharnia, H. Aidala, C.A. Aiola, S. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Aliouche, Z. Alkhazov, G. Alvarez Cartelle, P. Amato, S. Amhis, Y. An, L. Anderlini, L. Andreianov, A. Andreotti, M. Archilli, F. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Bachmayer, M. Back, J.J. Baker, S. Baladron Rodriguez, P. Balagura, V. Baldini, W. Baptista Leite, J. Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Basels, J.M. Bassi, G. Batsukh, B. Battig, A. Bay, A. Becker, M. Bedeschi, F. Bediaga, I. Beiter, A. Belavin, V. Belin, S. Bellee, V. Belous, K. Belov, I. Belyaev, I. Bencivenni, G. Ben-Haim, E. Berezhnoy, A. Bernet, R. Berninghoff, D. Bernstein, H.C. Bertella, C. Bertolin, A. Betancourt, C. Betti, F. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bian, L. Bieker, M.S. Bifani, S. Billoir, P. Birch, M. Bishop, F.C.R. Bitadze, A. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Boelhauve, J.A. Boente Garcia, O. Boettcher, T. Boldyrev, A. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Borsuk, J.T. Bouchiba, S.A. Bowcock, T.J.V. Boyer, A. Bozzi, C. Bradley, M.J. Braun, S. Brea Rodriguez, A. Brodski, M. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buonaura, A. Burr, C. Bursche, A. Butkevich, A. Butter, J.S. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calefice, L. Calero Diaz, L. Cali, S. Calladine, R. Calvi, M. Calvo Gomez, M. Camargo Magalhaes, P. Camboni, A. Campana, P. Campoverde Quezada, A.F. Capelli, S. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carli, I. Carniti, P. Carus, L. Carvalho Akiba, K. Casais Vidal, A. Casse, G. Cattaneo, M. Cavallero, G. Celani, S. Cerasoli, J. Chadwick, A.J. Chapman, M.G. Charles, M. Charpentier, Ph. Chatzikonstantinidis, G. Chavez Barajas, C.A. Chefdeville, M. Chen, C. Rio de Janeiro Brazil Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China Beijing China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Chinese Academy of Sciences Beijing China Institute of Particle Physics Central China Normal University Hubei Wuhan China Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano Milano Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma La Sapienza Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics VU University Amsterdam Amsterdam Netherlands AGH - University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Henryk Niewodniczanski Institute of Nuclear Physics Polish

Decays of Ξb- and Ωb- baryons to Λ+c h-h′- final states, with h-h′- being π-π-, K-π- and K-K- meson pairs, are searched for using data collected with the LHCb detector. The data sample studied corresponds to an integrated luminosity of 8.7 fb-1 of pp collisions collected at centre-of-mass energies √s = 7, 8 and 13 TeV. The products of the relative branching fractions and fragmentation fractions for each signal mode, relative to the B- → Λ+c pπ- mode, are measured, with Ξb- → Λ+c K-π-, Ξb- → Λ+c K-K- and Ωb- → Λ+c K-K- decays being observed at over 5 σ significance. The Ξb- → Λ+c K-π- mode is also used to measure the Ξb- production asymmetry, which is found to be consistent with zero. In addition, the B- → Λ+c pK- decay is observed for the first time, and its branching fraction is measured relative to that of the B- → Λ+c pπ- mode. © 2024, CC BY.

关键词： Hadrons

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Observation of exotic J/ψ resonances in diffractive processes in proton-proton collisions

arXiv

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arXiv 2024年

The first study of J/ψ production in diffractive processes in proton-proton collisions is presented. The study is based on an LHCb dataset recorded at centreof-mass energy of 13 TeV, corresponding to an integrated luminosity of 5 fb-1. The data disfavour a nonresonant J/ψ production but are consistent with a resonant model including several resonant states observed previously only in B+ → J/ψK+ decays. The χc0(4500) state is observed with a significance over 5 σ and the χc1(4274) is confirmed with a significance of more than 4 σ. © 2024, CC BY.

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Measurement of the CKM angle γ in B± → D K∗(892)± decays

arXiv

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arXiv 2024年

Measurements of CP observables and the CKM angle γ are performed in B± → DK∗(892)± decays, where D represents a superposition of D0 and D0 states, using the LHCb dataset collected during Run 1 (2011–2012) and Run 2 (2015–2018). A comprehensive study of this channel is presented with the D meson reconstructed in two-body final states K±π, K+K- and π+π-;four-body final states K±ππ±π and π+π-π+π-;and three-body final states KS0π+π- and KS0K+K-. This analysis includes the first observation of the suppressed B± → [π+K-]DK∗± and B± → [π+K-π+π-]DK∗± decays. The combined result gives γ = (63 ± 13)◦ © 2024, CC BY.

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Search for the doubly charmed baryon Ω_(cc)^(+)

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science China(Physics,Mechanics & Astronomy) 2021年第10期64卷 2-13页

作者： LHCb Collaboration Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool UK Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol UK CNRS/IN2P3 LPC Université Clermont Auvergne Clermont-Ferrand France University of Michigan Ann Arbor USA INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow UK ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester UK Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge UK Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil CNRS/IN2P3 IJCLab Université Paris-Saclay Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse USA Yandex School of Data Analysis Moscow Russia CNRS/IN2P3 CPPM Aix Marseille Univ Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry UK Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil Imperial College London London UK INFN Sezione di Genova Genova Italy National University of Science and T

A search for the doubly charmed baryon ?cc+ with the decay mode c Ω_(cc)^(+)→ Ξc+K-π+ is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the LHCb experiment from 2016 to 2018, corresponding to an integrated luminosity of 5.4 fb-1. No significant signal is observed within the invariant mass range of 3.6 to 4.0 GeV/c2. Upper limits are set on the ratio R of the production cross-section times the total branching fraction of the Ω_(cc)^(+)→ Ξc+K-π+ decay with respect to the Ξcc++→ Λc+K-π+π+ decay. Upper limits at 95% credibility level for R in the range 0.005 to 0.11 are obtained for diferent hypotheses on the ?cc+ mass and lifetime in the rapidity range from 2.0 to 4.5 and transverse momentum range from 4 to 15 GeV/c.

关键词： charmed baryons limits on production of particles charmed quarks experimental tests

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Taking the pulse of COVID-19: A spatiotemporal perspective

arXiv

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arXiv 2020年

作者： Yang, Chaowei Sha, Dexuan Liu, Qian Li, Yun Lan, Hai Guan, Weihe Wendy Hu, Tao Li, Zhenlong Zhang, Zhiran Thompson, John Hoot Wang, Zifu Wong, David Ruan, Shiyang Yu, Manzhu Richardson, Douglas Zhang, Luyao Hou, Ruizhi Zhou, You Zhong, Cheng Tian, Yifei Beaini, Fayez Carte, Kyla Flynn, Colin Liu, Wei Pfoser, Dieter Bao, Shuming Li, Mei Zhang, Haoyuan Liu, Chunbo Jiang, Jie Du, Shihong Zhao, Liang Lu, Mingyue Li, Lin Zhou, Huan NSF Spatiotemporal Innovation Center George Mason Univ. FairfaxVA22030 United States Department of Geography and GeoInformation Science George Mason Univ. FairfaxVA22030 United States Department of Geographical Sciences University of Maryland College ParkMD20742 United States Center for Geographic Analysis Harvard University CambridgeMA02138 United States Geoinformation and Big Data Research Lab Department of Geography University of South Carolina ColumbiaSC29208 United States Chinese Academy of Surveying and Mapping Beijing China Cloud Compute and Storage Operations Information Technology Services George Mason University FairfaxVA22030 United States Department of Geography Pennsylvania State University State CollegePA16801 United States School of Business Management East China Normal University Zhongshanbei Road Shanghai3663 China School of Mathematical Sciences East China Normal University Zhongshanbei Road Shanghai3663 China Department of Psychology George Mason University FairfaxVA22030 United States Department of Computer Science George Mason University FairfaxVA22030 United States Department of Information Technology George Mason University FairfaxVA22030 United States Department of Biology George Mason University FairfaxVA22030 United States College of Land Science and Technology China Agricultural University Beijing100083 China China Data Institute Ann ArborMI United States Institute of Remote Sensing and GIS Peking University Beijing100871 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing100044 China School of Geographical Sciences Nanjing University of Information Science & Technology 219 Ningliu Road Nanjing Jiangsu210044 China School of Resource and Environmental Sciences Wuhan University 129 Luoyu Rd Wuhan Hubei430079 China School of Geodesy a

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts;in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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Point cloud modelling based on the tunnel axis and block estimation for monitoring the Badaling Tunnel, China

Point cloud modelling based on the tunnel axis and block est...

引用

ISPRS Geospatial Week 2017

作者： Wang, J. Zheng, H.B. Huang, H. Ma, G.W. Beijing Key Laboratory of Traffic Engineering Beijing University of Technology China College of Civil Engineering and Architecture Beijing University of Technology China Institute for Applied Computer Science Bundeswehr University Munich Germany School of Civil Environmental and Mining Engineering University of Western Australia Australia

Recent years have witnessed a growing investigation of terrestrial laser scanning (TLS) for monitoring the deformation of tunnels. TLS provides the ability to obtain a more accurate and complete description of the tunnel surfaces, allowing the determination of the mechanism and magnitude of tunnel deformation, because the entire surface of the tunnel is more concretely modelled rather than being represented by a number of points. This paper models and analyses the point clouds from TLS to detect the possible deformation of a newly built tunnel. In the application of monitoring the Badaling Tunnel for the Winter Olympics 2020 in beijing, China, the proposed method includes the following components: the tunnel axis is automatically estimated based on a 3D quadratic form estimation;all of the point clouds are segmented into axis-based blocks;and representative points, solved by a singular value decomposition (SVD) method, are estimated to describe the tunnel surface and establish the correspondence of data between days. The deformations are detected in the form of the distance discrepancies of representative points and verified by the measurements using total station. © Authors 2017. CC BY 4.0 License.

关键词： Deformation

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