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arXiv 2018年

作者： Liu, Yanan Fan, Rui Yu, Bin Junaid Bocus, M. Liu, Ming Ni, Hepeng Fan, Jiahe Mao, Shixin Bristol Robotics Laboratory University of Bristol Bristol United Kingdom Robotics and Multi-Perception Laboratory Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1UB United Kingdom School of Mechanical Engineering Shandong University Jinan250061 China School of Communication Engineering Jilin University Changchun130000 China Shenzhen Sanhang Industrial Technology Research Institute Shenzhen518000 China

Mobile robots are becoming increasingly important both for individuals and industries. Mobile robotic technology is not only utilised by experts in this field but is also very popular among amateurs. However, implementing a mobile robot to perform tasks autonomously can be expensive because of the need for various types of sensors and the high price of robot platforms. Hence, in this paper we present a mobile robot localisation and navigation system which uses a LEGO ultrasonic sensor in an indoor map based on the LEGO MINDSTORM NXT. This provides an affordable and ready-to-use option for most robot fans. In this paper, an effective method is proposed to extract useful information from the distorted readings collected by the ultrasonic sensor. Then, the particle filter is used to localise the robot. After robot's position is estimated, a sampling-based path planning method is proposed for the robot navigation. This method reduces the robot accumulative motion error by minimising robot turning times and covering distances. The robot localisation and navigation algorithms are implemented in MATLAB. Simulation results show an average accuracy between 1 and 3 cm for three different indoor map locations. Furthermore, experiments performed in a real setup show the effectiveness of the proposed methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile robots

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Quantum optical metrology of correlated phase and loss

arXiv

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arXiv 2019年

作者： Birchall, Patrick M. Allen, Euan J. Stace, Thomas M. O’Brien, Jeremy L. Matthews, Jonathan C.F. Cable, Hugo Quantum Engineering Technology Labs H. H. Wills Physics Laboratory Department of Electrical & Electronic Engineering University of Bristol BS8 1FD United Kingdom Quantum Engineering Centre for Doctoral Training H. H. Wills Physics Laboratory Department of Electrical & Electronic Engineering University of Bristol Tyndall Avenue BS8 1FD United Kingdom ARC Centre of Excellence for Engineered Quantum Systems School of Mathematics and Physics University of Queensland Saint Lucia Queensland4072 Australia

Optical absorption measurements characterize a wide variety of systems from atomic gases to in-vivo diagnostics of living organisms. Here we study the potential of non-classical techniques to reduce statistical noise below the shot-noise limit in absorption measurements with concomitant phase shifts imparted by a sample. We consider both cases where there is a known relationship between absorption and a phase shift, and where this relationship is unknown. For each case we derive the fundamental limit and provide a practical strategy to reduce statistical noise. Furthermore, we find an intuitive correspondence between measurements of absorption and of lossy phase shifts, which both show the same scope for precision enhancement. Our results demonstrate that non-classical techniques can aid real-world tasks with present-day laboratory techniques. Copyright © 2019, The Authors. All rights reserved.

关键词： Shot noise

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The CMS Statistical Analysis and Combination Tool: Combine

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Computing and Software for Big Science 2024年第1期8卷 1-45页

作者： Zhokin, A. Zhizhin, I. Zarubin, A. Yuldashev, B.S. Voytishin, N. Vorotnikov, G. Vorobyev, A. Volkov, P. Uzunian, A. Uvarov, L. Toropin, A. Tlisova, I. Teryaev, O. Terkulov, A. Tcherniaev, E. Sulimov, V. Sosnov, D. Smirnov, V. Slabospitskii, S. Skovpen, Y. Shulha, S. Shmatov, S. Shalaev, V. Savrin, V. Savina, M. Radchenko, O. Popov, V. Polikarpov, S. Perfilov, M. Perelygin, V. Palichik, V. Oreshkin, V. Obraztsov, S. Nikitenko, A. Murzin, V. Matveev, V. Malakhov, A. Makarenko, V. Lychkovskaya, N. Levchenko, P. Lanev, A. Krasnikov, N. Kozyrev, A. Korenkov, V. Konstantinov, D. Kodolova, O. Klyukhin, V. Kirsanov, M. Kirpichnikov, D. Kirakosyan, M. Kim, V. Karneyeu, A. Karjavine, V. Kachanov, V. Ivanov, Y. Gribushin, A. Gorbunov, I. Golutvin, I. Golubev, N. Golovtcov, V. Gninenko, S. Gavrilov, V. Gavrilov, G. Dudko, L. Dubinin, M. Druzhkin, D. Dimova, T. Dermenev, A. Chistov, R. Chekhovsky, V. Chadeeva, M. Bunichev, V. Budkouski, D. Borshch, V. Boos, E. Blinov, V. Babaev, A. Azarkin, M. Aushev, T. Andreev, Yu. Andreev, V. Alexakhin, V. Afanasiev, S. Warden, A. Vetens, W. Tsoi, H.F. Teague, D. Smith, W.H. Sharma, V. Shang, V. Savin, A. Pinna, D. Pétré, L. Parida, G. Mondal, S. Mohammadi, A. Mallampalli, A. Sreekala, J. Madhusudanan Loveless, R. Lanaro, A. Koraka, C.K. Herve, A. Herndon, M. He, H. Galloni, C. Everaerts, P. De Bruyn, I. Dasu, S. Bose, T. Black, K. Banerjee, S. Aravind, A. Karchin, P.E. Bhattacharya, S. Neu, C. Ledovskoy, A. Hirosky, R. Hakala, J. Cox, B. Cardwell, B. Viinikainen, J. Velkovska, J. Tuo, S. Sheldon, P. Romeo, F. Melo, A. Elayavalli, R. Kunnawalkam Johns, W. Gurrola, A. Greene, S. Chen, Y. Appelt, E. Volobouev, I. Peltola, T. Mankel, A. Lee, S.W. Lamichhane, K. Kazhykarim, Y. Hussain, A. Hegde, V. Gogate, N. Damgov, J. Akchurin, N. Safonov, A. Rathjens, D. Overton, D. Mueller, R. Luo, S. Kim, H. Kamon, T. Huang, T. Gilmore, J. Eusebi, R. Bouhali, O. Akhter, T. Ahmad, M. Aebi, D. Spanier, S. Nibigira, E. Lee, L. Karunarathna, N. Kanuganti, A.R. Holmes, T. Higginbotham, S. Fiorendi, S. Delannoy Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Guangdong Provincial Key Laboratory of Nuclear Science and Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern Physics Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Venezuela Universidad de Antioquia Medellin Colombia Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split Split Croatia Faculty of Science University of Split Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Universidad San Francisco de Quito Quito Ecuador Egyptian Network of High Energy Physics Academy of Scientific Research and Technology of the Arab Republic of Egypt Cairo Egypt Center for High

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. © CERN, for the benefit of the CMS Collaboration 2024.

关键词： CMS Combine Higgs Higgs boson Statistics

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Mobile Robot Localisation and Navigation Using LEGO NXT and Ultrasonic Sensor

Mobile Robot Localisation and Navigation Using LEGO NXT and ...

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IEEE International Conference on robotics and Biomimetics

作者： Yanan Liu Rui Fan Bin Yu M. Junaid Bocus Ming Liu Hepeng Ni Jiahe Fan Shixin Mao Bristol Robotics Laboratory University of Bristol Bristol United Kingdom Hong Kong University of Science and Technology Kowloon HK Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong University of Bristol Bristol Bristol GB Department of Electrical and Electronic Engineering University of Bristol Bristol United Kingdom School of Mechanical Engineering Shandong University Jinan China School of Communication Engineering Jilin University Changchun China Shenzhen Sanhang Industrial Technology Research Institute Shenzhen China

ISBN: (纸本)9781728103785;9781728103778

关键词： Mobile robot LEGO NXT Localisation and navigation Particle filter Path plan

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Correction: CEPC Technical Design Report: Accelerator

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Radiation Detection technology and Methods 2024年第1期9卷 184-192页

作者： Abdallah, Waleed de Freitas, Tiago CarlosAdorno Afanaciev, Konstantin Ahmad, Shakeel Ahmed, Ijaz Ai, Xiaocong Aleem, Abid Altmannshofer, Wolfgang Alves, Fabio An, Weiming An, Rui Anderle, Daniele Paolo Antusch, Stefan Arai, Yasuo Arbuzov, Andrej Arhrib, Abdesslam Ashry, Mustafa Bai, Sha Bai, Yu Bai, Yang Bairathi, Vipul Balazs, Csaba Bambade, Philip Ban, Yong Bandyopadhyay, Triparno Bao, Shou-Shan Barber, Desmond P. Bat, Ays¸e Batozskaya, Varvara Behera, Subash Chandra Belyaev, Alexander Bertucci, Michele Bi, Xiao-Jun Bi, Yuanjie Bian, Tianjian Bianchi, Fabrizio Bieko¨tter, Thomas Biglietti, Michela Bilanishvili, Shalva Binglin, Deng Bodrov, Denis Bogomyagkov, Anton Bondarenko, Serge Boogert, Stewart Boonekamp, Maarten Borri, Marcello Bosotti, Angelo Boudry, Vincent Boukidi, Mohammed Boyko, Igor Bozovic, Ivanka Bozzi, Giuseppe Brient, Jean-Claude Budzinskaya, Anastasiia Bukhari, Masroor Bytev, Vladimir Cacciapaglia, Giacomo Cai, Hua Cai, Wenyong Cai, Wujun Cai, Yijian Cai, Yizhou Cai, Yuchen Cai, Haiying Cai, Huacheng Calibbi, Lorenzo Cang, Junsong Cao, Guofu Cao, Jianshe Chance, Antoine Chang, Xuejun Chang, Yue Chang, Zhe Chang, Xinyuan Chao, Wei Chatrabhuti, Auttakit Che, Yimin Che, Yuzhi Chen, Bin Chen, Danping Chen, Fuqing Chen, Fusan Chen, Gang Chen, Guoming Chen, Hua-Xing Chen, Huirun Chen, Jinhui Chen, Ji-Yuan Chen, Kai Chen, Mali Chen, Mingjun Chen, Mingshui Chen, Ning Chen, Shanhong Chen, Shanzhen Chen, Shao-Long Chen, Shaomin Chen, Shiqiang Chen, Tianlu Chen, Wei Chen, Xiang Chen, Xiaoyu Chen, Xin Chen, Xun Chen, Xurong Chen, Ye Chen, Ying Chen, Yukai Chen, Zelin Chen, Zilin Chen, Boping Chen, Chunhui Cheng, Hok Chuen Cheng, Huajie Cheng, Shan Cheng, Tongguang Chi, Yunlong Chimenti, Pietro Chiu, Wen Han Cho, Guk Chu, Ming-Chung Chu, Xiaotong Chu, Ziliang Coloretti, Guglielmo Crivellin, Andreas Cui, Hanhua Cui, Xiaohao Cui, Zhaoyuan D’Anzi, Brunella Dai, Ling-Yun Dai, Xinchen Dai, Xuwen De Maria, Antonio De Filippis, Nicola De La Taille, Christophe De Mori, Francesca De Sio, Chiara Del Core, Elisa Deng, Cairo University Giza Egypt Xi’an Jiaotong-Liverpool University Suzhou China Institute of Power Engineering of National Academy of Sciences of Belarus Minsk Belarus Pakistan Institute of Nuclear Science and Technology (PINSTECH) Islamabad Pakistan Applied Physics Department Science and Technology Federal Urdu University of Arts Islamabad Pakistan Zhengzhou University Zhengzhou China Institute of High Energy Physics Chinese Academy of Sciences Beijing China University of California Santa Cruz Santa Cruz USA Nanjing University Nanjing China Beijing Normal University Beijing China Harvard University Cambridge USA South China Normal University Guangzhou China University of Basel Basel Switzerland High Energy Accelerator Research Organization (KEK) Tsukuba Japan Joint Institute for Nuclear Research Dubna Russia Faculty of Sciences and Techniques Université Abdelmalek Essaadi Tangier Morocco Southeast University Nanjing China Department of Physics University of Wisconsin–Madison Madison USA Instituto de Alta Investigación Universidad de Tarapacá Arica Chile Monash University Melbourne Australia Laboratoire de Physique des 2 infinis Irène Joliot-Curie – IJCLab Orsay France Peking University Beijing China Department of Physics and Nanotechnology SRM Institute of Science and Technology Kattankulathur India Shandong University Jinan China University of New Mexico Albuquerque USA Bandirma Onyedi Eylul University Bandırma Turkey National Centre for Nuclear Research Warsaw Poland Indian Institute of Technology Madras (IN) Chennai India University of Southampton Southampton UK INFN Milano - LASA Segrate Italy Sun Yat-Sen University Guangzhou China China Institute of Atomic Energy Beijing China INFN-University of Torino Turin Italy Karlsruhe Institute of Technology Institute for Theoretical Physics Karlsruhe Germany INFN-Sezione di Roma Tre Rome Italy Kutaisi International University Kutaisi Georgia Soochow University Suzhou China Budker Institute

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Cyber Awareness Trends in Avionics

Cyber Awareness Trends in Avionics

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Conference on Digital Avionics Systems (DASC)

作者： Erik Blasch Roberto Sabatini Aloke Roy Kathleen A. Kramer George Andrew George T. Schmidt Carlos C. Insaurralde Giancarmine Fasano Data Analytics Portfolio Air Force Office of Scientific Research Arlington VA USA School of Engineering AE&A RMIT University Bundoora VIC Australia Aerospace Advanced Technology Honeywell Columbia MD USA University of San Diego San Diego CA USA GNA Aerospace Consulting Group Washington DC USA MIT Instrumentation Laboratory/Draper (Ret.) Boston MA USA Bristol Robotics Laboratory Univ. of the West of England Bristol UK University of Naples “Federico II” Naples ITALY

ISBN: (数字)9781728106496

ISBN: (纸本)9781728114972

Recent examples driving an increased need for cyber awareness include unmanned aerial vehicles (DAVs) in the airspace, development of the Automatic dependent surveillance-broadcast (ADS-B), and the risk of cyber intrusion. The incident of a civilian UAV disrupting a major airport, is one example of many incidents raising questions on the future of airspace security. While a civilian hobbyist might be ignorant of the impending harm, the situation could pose a threat to the air operations. Using this incident and others like it, ideas on the future trends in cyber awareness applied to avionics are considered. Three general ideas are incorporated: (1) mandates for new rules for airspace restrictions (e.g., geofence), (2) advanced display analytics to support the airport staff and pilots with visual displays, such as collision avoidance, and (3) electronics to support the mitigation of electronic cyber effects posed by the obtrusive aircraft. With a variety of opinions posed, the summary is intended to foster a discussion on research, industry, and commercial directions for the avionics community to consider with respect to cyber awareness.

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A study of the K+ → π0e+νγ decay

arXiv

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arXiv 2023年

作者： Gil, E. Cortina Kleimenova, A. Minucci, E. Padolski, S. Petrov, P. Shaikhiev, A. Volpe, R. Numao, T. Petrov, Y. Velghe, B. Wong, V.W.S. Bryman, D. Fu, J. Hives, Z. Husek, T. Jerhot, J. Kampf, K. Zamkovsky, M. De Martino, B. Perrin-Terrin, M. Akmete, A.T. Aliberti, R. Khoriauli, G. Kunze, J. Lomidze, D. Peruzzo, L. Vormstein, M. Wanke, R. Dalpiaz, P. Fiorini, M. Mazzolari, A. Neri, I. Norton, A. Petrucci, F. Soldani, M. Wahl, H. Bandiera, L. Ramusino, A. Cotta Gianoli, A. Romagnoni, M. Sytov, A. Iacopini, E. Latino, G. Lenti, M. Lo Chiatto, P. Panichi, I. Parenti, A. Bizzeti, A. Bucci, F. Antonelli, A. Georgiev, G. Kozhuharov, V. Lanfranchi, G. Martellotti, S. Moulson, M. Spadaro, T. Tinti, G. Ambrosino, F. Capussela, T. Corvino, M. D’Errico, M. Di Filippo, D. Fiorenza, R. Giordano, R. Massarotti, P. Mirra, M. Napolitano, M. Rosa, I. Saracino, G. Anzivino, G. Brizioli, F. Imbergamo, E. Lollini, R. Piandani, R. Santoni, C. Barbanera, M. Cenci, P. Checcucci, B. Lubrano, P. Lupi, M. Pepe, M. Piccini, M. Costantini, F. Di Lella, L. Doble, N. Giorgi, M. Giudici, S. Lamanna, G. Lari, E. Pedreschi, E. Sozzi, M. Cerri, C. Fantechi, R. Pontisso, L. Spinella, F. Mannelli, I. D’Agostini, G. Raggi, M. Biagioni, A. Cretaro, P. Frezza, O. Leonardi, E. Lonardo, A. Turisini, M. Valente, P. Vicini, P. Ammendola, R. Bonaiuto, V. Fucci, A. Salamon, A. Sargeni, F. Arcidiacono, R. Bloch-Devaux, B. Boretto, M. Menichetti, E. Migliore, E. Soldi, D. Biino, C. Filippi, A. Marchetto, F. Olvera, A. Briano Engelfried, J. Estrada-Tristan, N. Santos, M.A. Reyes Boboc, P. Bragadireanu, A.M. Ghinescu, S.A. Hutanu, O.E. Bician, L. Blazek, T. Cerny, V. Kucerova, Z. Bernhard, J. Ceccucci, A. Ceoletta, M. Danielsson, H. De Simone, N. Duval, F. Döbrich, B. Federici, L. Gamberini, E. Gatignon, L. Guida, R. Hahn, F. Holzer, E.B. Jenninger, B. Koval, M. Laycock, P. Miotto, G. Lehmann Lichard, P. Mapelli, A. Marchevski, R. Massri, K. Noy, M. Palladino, V. Pinzino, J. Ryjov, V. Université Catholique de Louvain Louvain-La-Neuve Belgium TRIUMF VancouverBC Canada University of British Columbia VancouverBC Canada Charles University Prague Czech Republic Aix Marseille University CNRS IN2P3 CPPM Marseille France Institut für Physik PRISMA Cluster of Excellence Universität Mainz Mainz Germany Dipartimento di Fisica e Scienze della Terra Università e INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Ferrara Ferrara Italy Dipartimento di Fisica e Astronomia dell’Università INFN Sezione di Firenze Sesto Fiorentino Italy INFN Sezione di Firenze Sesto Fiorentino Italy Laboratori Nazionali di Frascati Frascati Italy Dipartimento di Fisica "Ettore Pancini" INFN Sezione di Napoli Napoli Italy Dipartimento di Fisica e Geologia Università e INFN Sezione di Perugia Perugia Italy INFN Sezione di Perugia Perugia Italy Dipartimento di Fisica dell’Università INFN Sezione di Pisa Pisa Italy INFN Sezione di Pisa Pisa Italy Scuola Normale Superiore INFN Sezione di Pisa Pisa Italy Dipartimento di Fisica Sapienza Università di Roma INFN Sezione di Roma I Roma Italy INFN Sezione di Roma I Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Dipartimento di Fisica dell’Università INFN Sezione di Torino Torino Italy INFN Sezione di Torino Torino Italy Instituto de Física Universidad Autónoma de San Luis Potosí San Luis Potosí Mexico Horia Hulubei National Institute for R&D in Physics and Nuclear Engineering Magurele Bucharest Romania Faculty of Mathematics Physics and Informatics Comenius University Bratislava Slovakia CERN European Organization for Nuclear Research Geneva Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom School of Physics University of Bristol Bristol United Kingdom School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Faculty of Science and Technology University of Lancaster Lancaster United Kingdom School of Physical Sciences

A sample of 1.3 × 105 K+ → π0e+νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017–2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinematic regions, improving on existing results by a factor larger than two. An asymmetry, possibly related to T-violation, is investigated with no evidence observed within the achieved precision. © 2023, CC BY.

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Improved calorimetric particle identification in NA62 using machine learning techniques

arXiv

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arXiv 2023年

作者： Cortina Gil, E. Kleimenova, A. Minucci, E. Padolski, S. Petrov, P. Shaikhiev, A. Volpe, R. Fedorko, W. Numao, T. Petrov, Y. Velghe, B. Wong, V.W.S. Yu, M. Bryman, D. Fu, J. Hives, Z. Husek, T. Jerhot, J. Kampf, K. Zamkovsky, M. Akmete, A.T. Aliberti, R. Khoriauli, G. Kunze, J. Lomidze, D. Peruzzo, L. Vormstein, M. Wanke, R. Dalpiaz, P. Fiorini, M. Neri, I. Norton, A. Petrucci, F. Soldani, M. Wahl, H. Bandiera, L. Cotta Ramusino, A. Gianoli, A. Mazzolari, A. Romagnoni, M. Sytov, A. Iacopini, E. Latino, G. Lenti, M. Lo Chiatto, P. Panichi, I. Parenti, A. Bizzeti, A. Bucci, F. Antonelli, A. Georgiev, G. Kozhuharov, V. Lanfranchi, G. Martellotti, S. Moulson, M. Spadaro, T. Tinti, G. Ambrosino, F. Capussela, T. Corvino, M. D’Errico, M. Di Filippo, D. Fiorenza, R. Giordano, R. Massarotti, P. Mirra, M. Napolitano, M. Saracino, G. Anzivino, G. Brizioli, F. Imbergamo, E. Lollini, R. Piandani, R. Santoni, C. Barbanera, M. Cenci, P. Checcucci, B. Lubrano, P. Lupi, M. Pepe, M. Piccini, M. Costantini, F. Di Lella, L. Doble, N. Giorgi, M. Giudici, S. Lamanna, G. Lari, E. Pedreschi, E. Sozzi, M. Cerri, C. Fantechi, R. Pontisso, L. Spinella, F. Mannelli, I. D’Agostini, G. Raggi, M. Biagioni, A. Cretaro, P. Frezza, O. Leonardi, E. Lonardo, A. Turisini, M. Valente, P. Vicini, P. Ammendola, R. Bonaiuto, V. Fucci, A. Salamon, A. Sargeni, F. Arcidiacono, R. Bloch-Devaux, B. Boretto, M. Menichetti, E. Migliore, E. Soldi, D. Biino, C. Filippi, A. Marchetto, F. Briano Olvera, A. Engelfried, J. Estrada-Tristan, N. Reyes Santos, M.A. Boboc, P. Bragadireanu, A.M. Ghinescu, S.A. Hutanu, O.E. Bician, L. Blazek, T. Cerny, V. Kucerova, Z. Bernhard, J. Ceccucci, A. Danielsson, H. De Simone, N. Duval, F. Döbrich, B. Federici, L. Gamberini, E. Gatignon, L. Guida, R. Hahn, F. Holzer, E.B. Jenninger, B. Koval, M. Laycock, P. Lehmann Miotto, G. Lichard, P. Mapelli, A. Marchevski, R. Massri, K. Noy, M. Palladino, V. Perrin-Terrin, M. Pinzino, J. Ryjov, V. Schuchmann, S. Université Catholique de Louvain Louvain-La-Neuve Belgium TRIUMF VancouverBC Canada University of British Columbia VancouverBC Canada Charles University Prague Czech Republic Institut für Physik and PRISMA Cluster of Excellence Universität Mainz Mainz Germany Dipartimento di Fisica e Scienze della Terra dell’Università INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Ferrara Ferrara Italy Dipartimento di Fisica e Astronomia dell’Università INFN Sezione di Firenze Sesto Fiorentino Italy INFN Sezione di Firenze Sesto Fiorentino Italy Laboratori Nazionali di Frascati Frascati Italy Dipartimento di Fisica "Ettore Pancini" INFN Sezione di Napoli Napoli Italy Dipartimento di Fisica e Geologia dell’Università INFN Sezione di Perugia Perugia Italy INFN Sezione di Perugia Perugia Italy Dipartimento di Fisica dell’Università INFN Sezione di Pisa Pisa Italy INFN Sezione di Pisa Pisa Italy Scuola Normale Superiore INFN Sezione di Pisa Pisa Italy Dipartimento di Fisica Sapienza Università di Roma INFN Sezione di Roma I Roma Italy INFN Sezione di Roma I Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Dipartimento di Fisica dell’Università INFN Sezione di Torino Torino Italy INFN Sezione di Torino Torino Italy Instituto de Física Universidad Autónoma de San Luis Potosí San Luis Potosí Mexico Horia Hulubei National Institute for R&D in Physics and Nuclear Engineering Bucharest-Magurele Romania Faculty of Mathematics Physics and Informatics Comenius University Bratislava Slovakia CERN European Organization for Nuclear Research Geneva Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom School of Physics University of Bristol Bristol United Kingdom School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Faculty of Science and Technology University of Lancaster Lancaster United Kingdom School of Physical Sciences University of Liverpool Liverpool United Kingdom Ph

Measurement of the ultra-rare K+ → π+νν¯ decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2 × 10−5 for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10−5 © 2023, CC BY.

关键词： Efficiency

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Search for K+ decays into the π+e+e−e+e− final state

arXiv

引用

arXiv 2023年

作者： Cortina Gil, E. Kleimenova, A. Minucci, E. Padolski, S. Petrov, P. Shaikhiev, A. Volpe, R. Numao, T. Petrov, Y. Velghe, B. Wong, V.W.S. Bryman, D. Fu, J. Hives, Z. Husek, T. Jerhot, J. Kampf, K. Zamkovsky, M. De Martino, B. Perrin-Terrin, M. Akmete, A.T. Aliberti, R. Khoriauli, G. Kunze, J. Lomidze, D. Peruzzo, L. Vormstein, M. Wanke, R. Dalpiaz, P. Fiorini, M. Mazzolari, A. Neri, I. Norton, A. Petrucci, F. Soldani, M. Wahl, H. Bandiera, L. Cotta Ramusino, A. Gianoli, A. Romagnoni, M. Sytov, A. Iacopini, E. Latino, G. Lenti, M. Lo Chiatto, P. Panichi, I. Parenti, A. Bizzeti, A. Bucci, F. Antonelli, A. Georgiev, G. Kozhuharov, V. Lanfranchi, G. Martellotti, S. Moulson, M. Spadaro, T. Tinti, G. Ambrosino, F. Capussela, T. Corvino, M. D’Errico, M. Di Filippo, D. Fiorenza, R. Giordano, R. Massarotti, P. Mirra, M. Napolitano, M. Rosa, I. Saracino, G. Anzivino, G. Brizioli, F. Imbergamo, E. Lollini, R. Piandani, R. Santoni, C. Barbanera, M. Cenci, P. Checcucci, B. Lubrano, P. Lupi, M. Pepe, M. Piccini, M. Costantini, F. Di Lella, L. Doble, N. Giorgi, M. Giudici, S. Lamanna, G. Lari, E. Pedreschi, E. Sozzi, M. Cerri, C. Fantechi, R. Pontisso, L. Spinella, F. Mannelli, I. D’Agostini, G. Raggi, M. Biagioni, A. Cretaro, P. Frezza, O. Leonardi, E. Lonardo, A. Turisini, M. Valente, P. Vicini, P. Ammendola, R. Bonaiuto, V. Fucci, A. Salamon, A. Sargeni, F. Arcidiacono, R. Bloch-Devaux, B. Boretto, M. Menichetti, E. Migliore, E. Soldi, D. Biino, C. Filippi, A. Marchetto, F. Briano Olvera, A. Engelfried, J. Estrada-Tristan, N. Reyes Santos, M.A. Boboc, P. Bragadireanu, A.M. Ghinescu, S.A. Hutanu, O.E. Bician, L. Blazek, T. Cerny, V. Kucerova, Z. Bernhard, J. Ceccucci, A. Ceoletta, M. Danielsson, H. De Simone, N. Duval, F. Döbrich, B. Federici, L. Gamberini, E. Gatignon, L. Guida, R. Hahn, F. Holzer, E.B. Jenninger, B. Koval, M. Laycock, P. Lehmann Miotto, G. Lichard, P. Mapelli, A. Marchevski, R. Massri, K. Noy, M. Palladino, V. Pinzino, J. Ryjov, V. Université Catholique de Louvain Louvain-La-Neuve Belgium TRIUMF VancouverBC Canada University of British Columbia VancouverBC Canada Charles University Prague Czech Republic Aix Marseille University CNRS IN2P3 CPPM Marseille France Institut für Physik and PRISMA Cluster of Excellence Universität Mainz Mainz Germany Dipartimento di Fisica e Scienze della Terra dell’Università e INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Ferrara Ferrara Italy Dipartimento di Fisica e Astronomia dell’Università INFN Sezione di Firenze Sesto Fiorentino Italy INFN Sezione di Firenze Sesto Fiorentino Italy Laboratori Nazionali di Frascati Frascati Italy Dipartimento di Fisica "Ettore Pancini" INFN Sezione di Napoli Napoli Italy Dipartimento di Fisica e Geologia dell’Università INFN Sezione di Perugia Perugia Italy INFN Sezione di Perugia Perugia Italy Dipartimento di Fisica dell’Università INFN Sezione di Pisa Pisa Italy INFN Sezione di Pisa Pisa Italy Scuola Normale Superiore INFN Sezione di Pisa Pisa Italy Dipartimento di Fisica Sapienza Università di Roma INFN Sezione di Roma I Roma Italy INFN Sezione di Roma I Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Dipartimento di Fisica dell’Università INFN Sezione di Torino Torino Italy INFN Sezione di Torino Torino Italy Instituto de Física Universidad Autónoma de San Luis Potosí San Luis Potosí Mexico Horia Hulubei National Institute for R&D in Physics and Nuclear Engineering Bucharest-Magurele Romania Faculty of Mathematics Physics and Informatics Comenius University Bratislava Slovakia CERN European Organization for Nuclear Research Geneva Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom School of Physics University of Bristol Bristol United Kingdom School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Faculty of Science and Technology University of Lancaster Lancaster United Kingdom School of Physical

The first search for ultra-rare K+ decays into the π+e+e−e+e− final state is reported, using a dataset collected by the NA62 experiment at CERN in 2017–2018. An upper limit of 1.4 × 10−8 at 90% CL is obtained for the branching ratio of the K+ → π+e+e−e+e− decay, predicted in the Standard Model to be (7.2 ± 0.7) × 10−11. Upper limits at 90% CL are obtained at the level of 10−9 for the branching ratios of two prompt decay chains involving pair-production of hidden-sector mediators: K+ → π+aa, a → e+e− and K+ → π+S, S → A′A′, A′ → e+e− © 2023, CC BY.

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Energetic electron precipitation driven by electromagnetic ion cyclotron waves from ELFIN’s low altitude perspective

arXiv

引用

arXiv 2022年

作者： Angelopoulos, V. Zhang, X.-J. Artemyev, A.V. Mourenas, D. Tsai, E. Wilkins, C. Runov, A. Liu, J. Turner, D.L. Li, W. Khurana, K. Wirz, R.E. Sergeev, V.A. Meng, X. Wu, J. Hartinger, M.D. Raita, T. Shen, Y. An, X. Shi, X. Bashir, M.F. Shen, X. Gan, L. Qin, M. Capannolo, L. Ma, Q. Russell, C.L. Masongsong, E.V. Caron, R. He, I. Iglesias, L. Jha, S. King, J. Kumar, S. Le, K. Mao, J. McDermott, A. Nguyen, K. Norris, A. Palla, A. Roosnovo Tam, J. Xie, E. Yap, R.C. Ye, S. Young, C. Adair, L.A. Shaffer, C. Chung, M. Cruce, P. Lawson, M. Leneman, D. Allen, M. Anderson, M. Arreola-Zamora, M. Artinger, J. Asher, J. Branchevsky, D. Cliffe, M. Colton, K. Costello, C. Depe, D. Domae, B.W. Eldin, S. Fitzgibbon, L. Flemming, A. Frederick, D.M. Gilbert, A. Hesford, B. Krieger, R. Lian, K. McKinney, E. Miller, J.P. Pedersen, C. Qu, Z. Rozario, R. Rubly, M. Seaton, R. Subramanian, A. Sundin, S.R. Tan, A. Thomlinson, D. Turner, W. Wing, G. Wong, C. Zarifian, A. Earth Planetary and Space Sciences Department Institute of Geophysics and Planetary Physics University of California Los Angeles Los AngelesCA90095 United States University of Texas at Dallas RichardsonTX75080 United States CEA DAM DIF Arpajon France Atmospheric and Oceanic Sciences Departments University of California Los AngelesCA United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States Department of Astronomy Center for Space Physics Boston University BostonMA United States Mechanical and Aerospace Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States School of Mechanical Industrial Manufacturing Engineering Oregon State University CorvallisOR97331 United States University of St. Petersburg St. Petersburg Russia Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Space Science Institute BoulderCO80301 United States Sodankylä Geophysical Observatory University of Oulu Sodankylä Finland Materials Science and Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Deloitte Consulting New YorkNY10112 United States Computer Science Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Microsoft RedmondWA98052 United States Physics and Astronomy Department University of California Los AngelesCA90095 United States Department of Astronomy and Astrophysics The University of Chicago ChicagoIL60637 United States Raybeam Inc. Mountain ViewCA94041 United States SpaceX HawthorneCA90250 United States Reliable Robotics Corporation Mountain ViewCA94043 United States Los Alamos National Laboratory Los AlamosNM87545 United States Mathematics Department University of California Los AngelesCA90095 United States Planet Labs PBC San FranciscoCA94107 United States KSAT Inc. De

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data from the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ∼17s, or ∆L ∼ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using 2 years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ∼50 events of strong EMIC wave-driven precipitation. Most reside at L ∼ 5 − 7 at dusk, while a smaller subset exists at L ∼ 8 − 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ∼ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive

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