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Search for the decay of the Higgs boson to a Z boson and a light pseudoscalar particle decaying to two photons

Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 850卷

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arbiol Val, S.J. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramonte, M. Bandyopadhyay, A. Bansa CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton NY United States Faculté des Sciences Université Mohammed v Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York NY United States INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King's College London London United Kingdom LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Brandeis University Waltham MA United States School of Physics and Astronomy University of Manchester Manchester United Kingdom Department of Physics Northern Illinois University DeKalb IL United States Department of Physics Istanbul University Istanbul Turkey Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States CERN Geneva Switzerland Institut de Física d'Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Department of Physics McGill University Montreal QC Canada Department of Physics Royal Holloway University of London

A search for the decay of the Higgs boson to a Z boson and a light, pseudoscalar particle, a, decaying respectively to two leptons and to two photons is reported. The search uses the full LHC Run 2 proton–proton collision data at s=13 TeV, corresponding to 139 fb⁻¹ collected by the ATLAS detector. This is one of the first searches for this specific decay mode of the Higgs boson, and it probes unexplored parameter space in models with axion-like particles (ALPs) and extended scalar sectors. The mass of the a particle is assumed to be in the range 0.1–33 GeV. The data are analysed in two categories: a merged category where the photons from the a decay are reconstructed in the ATLAS calorimeter as a single cluster, and a resolved category in which two separate photons are detected. The main background processes are from Standard Model Z boson production in association with photons or jets. The data are in agreement with the background predictions, and upper limits on the branching ratio of the Higgs boson decay to Za times the branching ratio a→γγ are derived at the 95% confidence level and they range from 0.08% to 2% depending on the mass of the a particle. The results are also interpreted in the context of ALP models. © 2024 The Author(s)

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Prediction of soft proton intensities in the near-Earth space using machine learning

arXiv

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arXiv 2021年

作者： Kronberg, Elena A. Hannan, Tanveer Huthmacher, Jens Münzer, Marcus Peste, Florian Zhou, Ziyang Berrendorf, Max Faerman, Evgeniy Gastaldello, Fabio Ghizzardi, Simona Escoubet, Philippe Haaland, Stein Smirnov, Artem Sivadas, Nithin Allen, Robert C. Tiengo, Andrea Ilie, Raluca Munich Theresienstr. 41 Munich80333 Germany Institute of Informatics LMU Munich Oettingenstraße 67 MunichD-80538 Germany Department of Statistics LMU Munich Ludwigstraße 33 MunichD-80539 Germany Milano via A. Corti 12 MilanoI-20133 Italy European Space Research and Technology Centre Keplerlaan 1 Noordwjik2201 AZ Netherlands Birkeland Centre for Space Science University of Bergen Allégaten 55 BergenNO-5007 Norway Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen37077 Germany German Research Centre for Geosciences Albert-Einstein-Straße 42-46 PotsdamD-14473 Germany Department of Electrical and Computer Engineering Boston University 8 Saint Mary's Street BostonMA02134 United States Johns Hopkins University Applied Physics Lab 11100 Johns Hopkins Road LaurelMD20723 United States Scuola Universitaria Superiore IUSS Pavia piazza della Vittoria 15 PaviaI-27100 Italy INFN Sezione di Pavia via A. Bassi 6 PaviaI-27100 Italy University of Illinois at Urbana-Champaign ECEB 306 N. Wright Street 5054 UrbanaIL61801 United States

The spatial distribution of energetic protons contributes towards the understanding of magnetospheric dynamics. Based upon 17 years of the Cluster/RAPID observations, we have derived machine learning-based models to predict the proton intensities at energies from 28 to 1,885 keV in the 3D terrestrial magnetosphere at radial distances between 6 and 22 RE. We used the satellite location and indices for solar, solar wind and geomagnetic activity as predictors. The results demonstrate that the neural network (multi-layer perceptron regressor) outperforms baseline models based on the k-Nearest Neighbors and historical binning on average by ∼80% and ∼33%, respectively. The average correlation between the observed and predicted data is about 56%, which is reasonable in light of the complex dynamics of fast-moving energetic protons in the magnetosphere. In addition to a quantitative analysis of the prediction results, we also investigate parameter importance in our model. The most decisive parameters for predicting proton intensities are related to the location: ZGSE direction and the radial distance. Among the activity indices, the solar wind dynamic pressure is the most important. The results have a direct practical application, for instance, for assessing the contamination particle background in the X-Ray telescopes for X-ray astronomy orbiting above the radiation belts. To foster reproducible research and to enable the community to build upon our work we publish our complete code, the data, as well as weights of trained models. Further description can be found in the GitHub project at https://***/Tanveer81/deep horizon. © 2021, CC BY-NC-ND.

关键词： Forecasting

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Comprehensive quality-aware automated semantic web service composition 30th

Comprehensive quality-aware automated semantic web service c...

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30th Australasian Joint Conference on Artificial Intelligence, AI 2017

作者： Wang, Chen Ma, Hui Chen, Aaron Hartmann, Sven School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand Department of Informatics Clausthal University of Technology Clausthal-Zellerfeld Germany

ISBN: (纸本)9783319630038

Web service composition has been a prevailing research direction in recent years. There are two major challenges faced by researchers, semantic matchmaking and Quality of Service (QoS) optimisation. Semantic matchmaking aims to discover interoperable web services that can interact with each other by their resources described semantically. QoS optimisation aims to optimise the non-functional requirements of service users, such as minimum cost and maximum reliability. To meet the requirements of service users, both semantic matchmaking quality and QoS should be considered simultaneously. Most existing works on web service composition, however, focus only on one of these two aspects. Therefore, we propose a comprehensive quality model that takes both semantic matchmaking quality and QoS into account with the aim of achieving a more desirable balance of both sides. Further, we develop a PSO-based service composition approach with explicit support for the proposed comprehensive quality model. We also conduct experiments to explore the effectiveness of our PSO-based approach and the desirable balance achieved by using our comprehensive quality model. © Springer International Publishing AG 2017.

关键词： Quality of service

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Radioactivity control strategy for the JUNO detector

arXiv

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arXiv 2021年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Babic, Andrej 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 Buscemi, Mario Busto, Jose Butorov, Ilya Cabrera, Anatael Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chang, Jinfan Chang, Yun Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Cheng, Jie Cheng, Yaping Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Di Lorenzo, Selma Conforti Corti, Daniele Cremonesi, Oliviero Corso, Flavio Dal Dalager, Olivia de la Taille, Christophe Deng, Jiawei 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 Dracos, Marcos Druillole, Frédéric Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fajt, Lukas Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fekete, Vladko Feng, Li-Cheng Feng, Qichun Ford, Richard Formozov, Andrey Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Giammarchi, Marco Giaz, Agnese Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Grewing, Christian Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guardone, Nunzio Gul, Maria Guo, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Hackspacher, Paul Hagn 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 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 in University of South China Hengyang China Wuyi University Jiangmen China Shandong University Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Jinan 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 China S

JUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV. © 2021, CC BY.

关键词： Radioactivity

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Measurement of vector boson production cross sections and their ratios using pp collisions at s=13.6 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 854卷

作者： Aad, G. Aakvaag, E. Abbott, B. Abdelhameed, S. Abeling, K. Abicht, N.J. Abidi, S.H. Aboelela, M. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Ackermann, A. Adam Bourdarios, C. Adamczyk, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Aktas, S. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Alegria, Z.L. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alsolami, Z.M.K. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amirie, K.J. Amor Dos Santos, S.P. Amos, K.R. An, S. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Arbiol Val, S.J. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Astrand, K.S.V. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Baer, T.M. Bagnaia, P. Bahmani, M. Bahner, D. Bai, K. Baines, J.T. Baines, L. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Department of Physics University of Adelaide Adelaide Australia Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France APC Université Paris Cité CNRS/IN2P3 Paris France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics University of Texas at Arlington Arlington TX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics University of Texas at Austin Austin TX United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Institut de Física d'Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain Institute of High Energy Physics Chinese Academy of Sciences Beijing China Physics Department Tsinghua University Beijing China Department of Physics Nanjing University Nanjing China School of Science Shenzhen Campus of Sun Yat-sen University China University of Chinese Academy of Science (UCAS) Beijing China Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory Berkeley CA United States University of California Berkeley CA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University

Fiducial and total W± and Z boson cross sections, their ratios and the ratio of top-antitop-quark pair and W-boson fiducial cross sections are measured in proton–proton collisions at a centre-of-mass energy of s...

Fiducial and total W^± and Z boson cross sections, their ratios and the ratio of top-antitop-quark pair and W-boson fiducial cross sections are measured in proton–proton collisions at a centre-of-mass energy of s=13.6 TeV, corresponding to an integrated luminosity of 29 fb⁻¹ of data collected in 2022 by the ATLAS experiment at the Large Hadron Collider. The measured fiducial cross-section values for W⁺→ℓ⁺ν, W⁻→ℓ⁻ν¯, and Z→ℓ⁺ℓ⁻ (ℓ=e or μ) boson productions are 4250±150 pb, 3310±120 pb, and 744±20 pb, respectively, where the uncertainty is the total uncertainty, including that arising from the luminosity of about 2.2%. The measurements are in agreement with Standard-Model predictions calculated at next-to-next-to-leading-order in α_s, next-to-next-to-leading logarithmic accuracy and next-to-leading-order electroweak accuracy. © 2024 The Author(s)

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Correlations of software code metrics: An empirical study 17

Correlations of software code metrics: An empirical study

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27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement, IWSM Mensura 2017

作者： Al Mamun, Md Abdullah Berger, Christian Hansson, Jörgen Department of Computer Science and Engineering Chalmers University of Technology University of Gothenburg Gothenburg41296 Sweden Department of Computer Science and Engineering Chalmers University of Technology Sweden University of Gothenburg Gothenburg41296 Sweden School of Informatics University of Skövde Skövde Sweden

ISBN: (纸本)9781450348539

Background: The increasing up-trend of software size brings about challenges related to release planning and maintainability. Foreseeing the growth of software metrics can assist in taking proactive decisions regarding different areas where software metrics play vital roles. For example, source code metrics are used to automatically calculate technical debt related to code quality which may indicate how maintainable a software is. Thus, predicting such metrics can give us an indication of technical debt in the future releases of software. Objective: Estimation or prediction of software metrics can be performed more meaningfully if the relationships between different domains of metrics and relationships between the metrics and different domains are well understood. To understand such relationships, this empirical study has collected 25 metrics classified into four domains from 9572 software revisions of 20 open source projects from 8 well-known companies. Results: We found software size related metrics are most correlated among themselves and with metrics from other domains. Complexity and documentation related metrics are more correlated with size metrics than themselves. Metrics in the duplications domain are observed to be more correlated to themselves on a domain-level. However, a metric to domain level relationship exploration reveals that metrics with most strong correlations are in fact connected to size metrics. The Overall correlation ranking of duplication metrics are least among all domains and metrics. Contribution: Knowledge earned from this research will help to understand inherent relationships between metrics and domains. This knowledge together with metric-level relationships will allow building better predictive models for software code metrics. © 2017 Association for Computing Machinery.

关键词： Open source software

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Search for non-resonant production of semi-visible jets using Run 2 data in ATLAS

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 848卷

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Hoffman, A.C. Abusleme Acharya, B.S. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Tamlihat, M. Ait Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Flores, C.A. Allendes Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Estevez, M. Alvarez Fernandez, A. Alvarez Cardoso, M. Alves Alviggi, M.G. Aly, M. Coutinho, Y. Amaral Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Dos Santos, S.P. Amor Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Pozo, J.A. Aparisi Aparo, M.A. Bella, L. Aperio Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assahsah, J. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Gupta, D. Bakshi Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. CPPM Aix-Marseille Université CNRS IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton NY United States Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York NY United States Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King's College London London United Kingdom LAPP Université Savoie Mont Blanc CNRS IN2P3 Annecy France AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto ON Canada Department of Physics Brandeis University Waltham MA United States School of Physics and Astronomy University of Manchester Manchester United Kingdom Department of Physics Northern Illinois University DeKalb IL United States Department of Physics Istanbul University Istanbul Turkey Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States CERN Geneva Switzerland Institut de Física d'Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Institute of Physics Azerbaijan Academy of

Semi-visible jets, with a significant contribution to the event's missing transverse momentum, can arise in strongly interacting dark sectors. This results in an event topology where one of the jets can be aligned with the direction of the missing transverse momentum. The first search for semi-visible jets produced via a t-channel mediator exchange is presented. The analysis uses proton-proton collisions with an integrated luminosity of 139 fb⁻¹ and a centre-of-mass energy of 13 TeV, collected with the ATLAS detector during the Run 2 of the LHC. No excess over Standard Model predictions is observed. Assuming a coupling strength of unity between the mediator, a Standard Model quark and a dark quark, mediator masses up to 2.7 TeV are excluded at the 95% confidence level. Upper limits on the coupling strength are also derived. © 2023 The Author(s)

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A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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Computing and Software for Big Science 2020年第1期4卷 1-20页

作者： Sirunyan, A.M. Tumasyan, A. Adam, W. Ambrogi, F. Bergauer, T. Dragicevic, M. Erö, J. Valle, A. Escalante Del Flechl, M. Frühwirth, R. Jeitler, M. Krammer, N. Krätschmer, I. Liko, D. Madlener, T. Mikulec, I. Rad, N. Schieck, J. Schöfbeck, R. Spanring, M. Spitzbart, D. Waltenberger, W. Wulz, C.-E. Zarucki, M. Drugakov, V. Mossolov, V. Gonzalez, J. Suarez Darwish, M.R. De Wolf, E.A. Croce, D. Di Janssen, X. Lelek, A. Pieters, M. Sfar, H. Rejeb Haevermaet, H. Van Mechelen, P. Van Putte, S. Van Remortel, N. Van Blekman, F. Bols, E.S. Chhibra, S.S. D’Hondt, J. De Clercq, J. Lontkovskyi, D. Lowette, S. Marchesini, I. Moortgat, S. Python, Q. Skovpen, K. Tavernier, S. Doninck, W. Van Mulders, P. Van Beghin, D. Bilin, B. Clerbaux, B. De Lentdecker, G. Delannoy, H. Dorney, B. Favart, L. Grebenyuk, A. Kalsi, A.K. Popov, A. Postiau, N. Starling, E. Thomas, L. Velde, C. Vander Vanlaer, P. Vannerom, D. Cornelis, T. Dobur, D. Khvastunov, I. Niedziela, M. Roskas, C. Tytgat, M. Verbeke, W. Vermassen, B. Vit, M. Bondu, O. Bruno, G. Caputo, C. David, P. Delaere, C. Delcourt, M. Giammanco, A. Lemaitre, V. Prisciandaro, J. Saggio, A. Marono, M. Vidal Vischia, P. Zobec, J. Alves, F.L. Alves, G.A. Silva, G. Correia Hensel, C. Moraes, A. Teles, P. Rebello Chagas, E. Belchior Batista Das Carvalho, W. Chinellato, J. Coelho, E. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. De Oliveira Martins, C. De Souza, S. Fonseca Guativa, L. M. Huertas Malbouisson, H. Martins, J. Figueiredo, D. Matos Jaime, M. Medina De Almeida, M. Melo Herrera, C. Mora Mundim, L. Nogima, H. Da Silva, W. L. Prado Rosas, L. J. Sanchez Santoro, A. Sznajder, A. Thiel, M. Manganote, E. J. Tonelli Da Silva De Araujo, F. Torres Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E.M. Lemos, D.S. Mercadante, P.G. Novaes, S.F. Padula, SandraS. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Bonchev, M. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Fang, W. Gao, X. Yuan, Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus 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 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 Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Université de Strasbourg CNRS IPH

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of s=13TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb-1. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯. © 2020, The Author(s).

关键词： b jets CMS Deep learning Higgs boson Jet energy Jet resolution

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Implementation of Non-Integer Order Filtering for the Purpose of Disparities Detection in Beta Frequencies - A Pilot Study

Implementation of Non-Integer Order Filtering for the Purpos...

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International Conference on Methods and Models in Automation and Robotics

作者： Aleksandra Kawala-Janik Magda Zolubak Waldemar Bauer Bartosz Nazimek Tomasz Sobolewski Radek Martinek Marcin Sowa Mariusz Pelc Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Krakow Poland Department of Neurosurgery University Hospital in Opole Opole Poland Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic

In this work the authors of the hereof paper describe pilot study on implementation of fractional order filtering applied for the purpose of disparities detection in Beta Frequencies. The Beta waves frequency range can be split into three sections, where the information provided by particular section enables more accurate medical diagnosis. Spectral analysis used in this study allowed appropriate isolation of the Beta waves. Implementation of non-integer order filtering in such study is innovative and provided some promising results.

关键词： Electroencephalography Spectrogram Electronic mail Frequency measurement Transfer functions Electrical engineering Stress

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A Study about Principle Component Analysis and Eigenface for Facial Extraction

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Journal of Physics: Conference Series 2019年第1期1196卷

作者： Erwin M Azriansyah N Hartuti Muhammad Fachrurrozi Bayu Adhi Tama Departement of Computer Engineering University of Sriwijaya Palembang Indonesia Departement of Informatics Engineering University of Sriwijaya Palembang Indonesia School of Management Engineering Ulsan National Institute of Science and Technology Ulsan Rep. of Korea

Facial recognition is one of the most successful applications of image analysis and understanding. This paper presents a Principal Component Analysis (PCA) and eigenface method for facial feature extraction. Several performance metrics, i.e. accuracy, precision, and recall are taken into account as a baseline of experiment. Furthermore, two public data sets, namely SOF (Speech on faces) and MIT CBCL Facerec are incorporated in the experiment. Based on our experimental result, it can be revealed that PCA has performed well in terms of accuracy, precision, and recall metrics by 0.598, 0.63, and 0.598, respectively.

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