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AtlFast3: The Next Generation of Fast Simulation in ATLAS

Computing and Software for Big Science 2022年第1期6卷 1-54页

作者： Aad, G. Abbott, B. Abbott, D.C. Abud, A. Abed Abeling, K. Abhayasinghe, D.K. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Hoffman, A. C. Abusleme Acharya, B.S. Achkar, B. Adam, L. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Addepalli, S.V. Adelman, J. Adiguzel, A. Adorni, S. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ai, X. Aielli, G. Aizenberg, I. Akatsuka, S. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Khoury, K. Al Alberghi, G.L. Albert, J. Albicocco, P. Verzini, M. J. Alconada Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, B. Ali, S. Aliev, M. Alimonti, G. Allaire, C. Allbrooke, B.M.M. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Camelia, E. Alunno Estevez, M. Alvarez Alviggi, M.G. Coutinho, Y. Amaral Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Santos, S. P. Amor Dos Amoroso, S. Amos, K.R. Amrouche, C.S. Ananiev, V. Anastopoulos, C. Andari, N. 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. Antrim, D.J.A. Anulli, F. Aoki, M. Pozo, J. A. Aparisi Aparo, M.A. Bella, L. Aperio Aranzabal, N. Ferraz, V. Araujo Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Armbruster, A.J. Armstrong, A. Arnaez, O. Arnold, H. Tame, Z. P. Arrubarrena Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Asimakopoulou, E.M. Asquith, L. Assahsah, J. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Austrup, V.A. Avner, G. Avolio, G. Ayoub, M.K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahrasemani, H. Bailey, A.J. Bailey, V.R. Baines, J.T. Bakalis, C. Baker, O.K. Bakker, P.J. Bakos, E. Gupta, D. Bakshi Balaji, S. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Bal 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 Univ. Savoie Mont Blanc CNRS/IN2P3 Annecy 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 Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey 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 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 and University of California Berkeley CA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Facultad de Ciencias y Cen

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes. © 2022, Springer Nature Switzerland AG.

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Cover Picture: Laser-scribed Graphene Electrodes as an Electrochemical Immunosensing Platform for Cancer Biomarker ‘eIF3d’ (Electroanalysis 4/2021)

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Electroanalysis 2021年第4期33卷

作者： Simge Balaban Tutku Beduk Ceren Durmus Eda Aydindogan Khaled Nabil Salama Suna Timur Department of Biochemistry Faculty of Science Ege University 35100 Bornova Izmir Turkey Sensors Lab Advanced Membranes and Porous Materials Center Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) 23955-6900 Thuwal Saudi Arabia Central Research Testing and Analysis Laboratory Research and Application Center Ege University 35100 Bornova Izmir Turkey

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Road surface friction prediction using long short-term memory neural network based on historical data

arXiv

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arXiv 2019年

作者： Pu, Ziyuan Wang, Shuo Liu, Chenglong Cui, Zhiyong Wang, Yinhai Smart Transportation Application and Research Laboratory Department of Civil and Environmental Engineering University of Washington 101 More Hall SeattleWA United States School of Computer Science and Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street NanjingJiangsu China Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University 4800 Cao’an Road Shanghai China Smart Transportation Application and Research Laboratory Department of Civil and Environmental Engineering University of Washington 101 More Hall SeattleWA United States Department of Civil and Environmental Engineering University of Washington 121F More Hall SeattleWA United States

Road surface friction significantly impacts traffic safety and mobility. A precise road surface friction prediction model can help to alleviate the influence of inclement road condition on traffic safety, Level of Service, traffic mobility, fuel efficiency, and sustained economic productivity. Most related previous studies are laboratory-based methods which are difficult for practical implementation. Moreover, in other data-driven methods, the demonstrated time-series features of road surface condition have not been considered. This study employed a Long-Short Term Memory (LSTM) neural network to develop a data-driven road surface friction prediction model based on historical data. The proposed prediction model outperformed the other baseline models in terms of the lowest value of predictive performance measurements. The influence of the number of time-lags and the predicting time interval on predictive accuracy was analyzed. In addition, the influence of adding road surface water thickness, road surface temperature and air temperature on predictive accuracy also were investigated. The findings of this study can support the road maintenance strategy development and decision making, thus mitigating the impact of inclement road condition on traffic mobility and safety. Future work includes a modified LSTM-based prediction model development by accommodating flexible time interval between time-lags. Copyright © 2019, The Authors. All rights reserved.

关键词： Long short-term memory

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Search for high-mass resonances in final states with a τ-lepton and missing transverse momentum with the ATLAS detector

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Physical Review D 2024年第11期109卷 112008-112008页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi H. Abramowicz H. Abreu Y. Abulaiti A. C. Abusleme Hoffman B. S. Acharya B. Achkar L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek S. V. Addepalli J. Adelman A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra A. Ahmad F. Ahmadov W. S. Ahmed X. Ai G. Aielli I. Aizenberg S. Akatsuka M. Akbiyik T. P. A. Åkesson A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali S. Ali M. Aliev G. Alimonti C. Allaire B. M. M. Allbrooke P. P. Allport A. Aloisio F. Alonso C. Alpigiani E. Alunno Camelia M. Alvarez Estevez M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche C. Anastopoulos N. Andari T. Andeen J. K. Anders S. Y. Andrean A. Andreazza S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella N. Aranzabal V. Araujo Ferraz C. Arcangeletti A. T. H. Arce E. Arena J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame G. Artoni H. Asada K. Asai S. Asai N. A. Asbah E. M. Asimakopoulou L. Asquith K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani P. A. Atmasiddha K. Augsten S. Auricchio V. A. Austrup G. Avner G. Avolio M. K. Ayoub G. Azuelos D. Babal H. Bachacou K. Bachas A. Bachiu F. Backman A. Badea P. Bagnaia H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines C. Bakalis O. K. Baker P. J. Bakker E. Bakos D. Bakshi Gupta S. Balaji R. Balasubramanian E. M. Baldin P. Balek E. Ballabene F. Balli W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay S. Bansal L. Barak E. L. Barberio D. Barberis M. Barbero G. Barbour K. N. Barends T. Bar CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States of America Department of Physics University of Massachusetts Amherst MA United States of America CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Physics Department Brookhaven National Laboratory Upton NY United States of America 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 High Energy Physics Division Argonne National Laboratory Argonne IL United States of America Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Institut für Physik Universität Mainz Mainz Germany 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 of America Department of Physics Northern Illinois University DeKalb IL United States of America Department of Physics Bogazici University Istanbul Türkiye Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland 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 of America IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France 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

A search for high-mass resonances decaying into a τ-lepton and a neutrino using proton-proton collisions at a center-of-mass energy of s=13 TeV is presented. The full run 2 data sample corresponding to an integrated luminosity of 139 fb−1 recorded by the ATLAS experiment in the years 2015–2018 is analyzed. The τ-lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the τ-lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the W′→τν production cross section. Heavy W′ vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model W boson. For nonuniversal couplings, W′ bosons are excluded for masses less than 3.5–5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the τ-lepton and missing transverse momentum.

关键词： Extensions of gauge sector Particle production Gauge bosons Hypothetical particles Neutrinos Tau leptons Hadron colliders

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Combination of Measurements of the Top Quark Mass from Data Collected by the ATLAS and CMS Experiments at s=7 and 8 TeV

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Physical Review Letters 2024年第26期132卷 261902-261902页

作者： A. Hayrapetyan A. Tumasyan W. Adam J. W. Andrejkovic T. Bergauer S. Chatterjee K. Damanakis M. Dragicevic P. S. Hussain M. Jeitler N. Krammer A. Li D. Liko I. Mikulec J. Schieck R. Schöfbeck D. Schwarz M. Sonawane S. Templ W. Waltenberger C.-E. Wulz M. R. Darwish T. Janssen P. Van Mechelen E. S. Bols J. D’Hondt S. Dansana A. De Moor M. Delcourt H. El Faham S. Lowette I. Makarenko D. Müller A. R. Sahasransu S. Tavernier M. Tytgat S. Van Putte D. Vannerom B. Clerbaux G. De Lentdecker L. Favart D. Hohov J. Jaramillo A. Khalilzadeh K. Lee M. Mahdavikhorrami A. Malara S. Paredes L. Pétré N. Postiau L. Thomas M. Vanden Bemden C. Vander Velde P. Vanlaer M. De Coen D. Dobur Y. Hong J. Knolle L. Lambrecht G. Mestdach C. Rendón A. Samalan K. Skovpen N. Van Den Bossche J. van der Linden L. Wezenbeek A. Benecke G. Bruno C. Caputo C. Delaere I. S. Donertas A. Giammanco K. Jaffel Sa. Jain V. Lemaitre J. Lidrych P. Mastrapasqua K. Mondal T. T. Tran S. Wertz G. A. Alves E. Coelho C. Hensel T. Menezes De Oliveira A. Moraes P. Rebello Teles M. Soeiro W. L. Aldá Júnior M. Alves Gallo Pereira M. Barroso Ferreira Filho H. Brandao Malbouisson W. Carvalho J. Chinellato E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza R. Gomes De Souza J. Martins C. Mora Herrera K. Mota Amarilo L. Mundim H. Nogima A. Santoro A. Sznajder M. Thiel A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores P. G. Mercadante S. F. Novaes B. Orzari Sandra S. Padula A. Aleksandrov G. Antchev R. Hadjiiska P. Iaydjiev M. Misheva M. Shopova G. Sultanov A. Dimitrov L. Litov B. Pavlov P. Petkov A. Petrov E. Shumka S. Keshri S. Thakur T. Cheng Q. Guo T. Javaid L. Yuan Z. Hu J. Liu K. Yi G. M. Chen H. S. Chen M. Chen F. Iemmi C. H. Jiang A. Kapoor H. Liao Z.-A. Liu R. Sharma J. N. Song J. Tao C. Wang J. Wang Z. Wang H. Zhang A. Agapitos Y. Ban A. Levin C. Li Q. Li Y. Mao S. J. Qian X. Sun D. Wang H. Yang L. Zhang C. Zhou Z. You N. Lu G. Bauer X. Gao D. Leggat H. Okawa Y. Zhang Z. Lin C. Lu M. Xiao C. Avila D. A. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Indian Institute of Technology Madras Madras India APC Université Paris Cité CNRS/IN2P3 Paris France Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Korea University Seoul Korea 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 IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France 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 Department of Physics Oxford University Oxford United Kingdom School of Physics and Astronomy Shanghai Jiao Tong University Key Laboratory for Particle Astrophysics and Cosmology (MOE) SKLPPC Shanghai China Department of Physics Chinese University of Hong Kong Shatin N.T. Hong Kong China Department of Physics University of Michigan Ann Arbor Michigan USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei China Department of Physics Nanjing University Nanjing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhe

A combination of fifteen top quark mass measurements performed by the ATLAS and CMS experiments at the LHC is presented. The datasets used correspond to an integrated luminosity of up to 5 and 20 fb−1 of proton-proton collisions at center-of-mass energies of 7 and 8 TeV, respectively. The combination includes measurements in top quark pair events that exploit both the semileptonic and hadronic decays of the top quark, and a measurement using events enriched in single top quark production via the electroweak t channel. The combination accounts for the correlations between measurements and achieves an improvement in the total uncertainty of 31% relative to the most precise input measurement. The result is mt=172.52±0.14(stat)±0.30(syst) GeV, with a total uncertainty of 0.33 GeV.

关键词： Top quark Hadron colliders

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Evidence of Minijet Emission in a Large Emission Zone from a Magnetically Dominated Gamma-Ray Burst Jet

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Astrophysical Journal 2025年第2期985卷 239-239页

作者： Yi, S.-X. Wang, C.-W. Shao, X. Moradi, R. Gao, H. Zhang, B. Xiong, S.-L. Zhang, S.-N. Tan, W.-J. Liu, J.-C. Xue, W.-C. Zhang, Y.-Q. Zheng, C. Wang, Y. Zhang, P. An, Z.-H. Cai, C. Feng, P.-Y. Gong, K. Guo, D.-Y. Huang, Y. Li, B. Li, X.-B. Li, X.-Q. Liu, X.-J. Liu, Y.-Q. Ma, X. Peng, W.-X. Qiao, R. Song, L.-M. Wang, J. Wang, P. Wang, Y. Wen, X.-Y. Xiao, S. Xu, Y.-B. Yang, S. Yi, Q.-B. Zhang, D.-L. Zhang, F. Zhang, H.-M. Zhang, J.-P. Zhang, Z. Zhao, X.-Y. Zhao, Y. Zheng, S.-J. Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 100049 China Department of Astronomy Beijing Normal University Beijing 100875 China Nevada Center for Astrophysics University of Nevada Las Vegas 89154 NV United States Department of Physics and Astronomy University of Nevada Las Vegas 89154 NV United States ICRANet Piazza della Repubblica 10 Pescara I-65122 Italy ICRA Dipartamento di Fisica Sapienza Università di Roma Piazzale Aldo Moro 5 Rome I-00185 Italy INAF Osservatorio Astronomico d’Abruzzo Via M. Maggini snc Teramo I-64100 Italy College of Electronic and Information Engineering Tongji University Shanghai 201804 China College of Physics Hebei Key Laboratory of Photophysics Research and Application Hebei Normal University Hebei Shijiazhuang 050024 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang 550001 China School of Physics and Optoelectronics Xiangtan University Yuhu District Xiangtan Hunan 411105 China School of Computer and Information Dezhou University Dezhou 253023 China

The second brightest gamma-ray burst (GRB) in history, GRB 230307A, provides an ideal laboratory to study the mechanism of GRB prompt emission thanks to its extraordinarily high photon statistics and its single-episode activity. Here we demonstrate that the rapidly variable components of its prompt emission compose an overall broad single pulse-like profile. Although these individual rapid components are aligned in time across all energy bands, this overall profile conspires to show a well-defined energy-dependent behavior that is typically seen in single GRB pulses. Such a feature demonstrates that the prompt emission of this burst is from many individual emitting units that are casually linked in a emission site at a large distance from the central engine. Such a scenario is in natural consistency with the internal-collision-induced magnetic reconnection and turbulence framework, which invokes many minijets due to local magnetic reconnection that constantly appear and disappear in a global magnetically dominated jet. © 2025. The Author(s). Published by the American Astronomical Society.

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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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Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

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Computing and Software for Big Science 2024年第1期8卷 1-36页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P.S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Mechelen, P. Van Bols, E.S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Faham, H. El Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Onsem, G. P. Van Putte, S. Van Vannerom, D. Clerbaux, B. Das, A.K. De Lentdecker, G. Favart, L. Gianneios, P. Hohov, D. Jaramillo, J. Khalilzadeh, A. Khan, F.A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Thomas, L. Bemden, M. Vanden Velde, C. Vander Vanlaer, P. De Coen, M. Dobur, D. Hong, Y. Knolle, J. Lambrecht, L. Mestdach, G. Amarilo, K. Mota Rendón, C. Samalan, A. Skovpen, K. Bossche, N. Van Den Linden, J. van der Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sh. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. De Oliveira, T. Menezes Moraes, A. Teles, P. Rebello Soeiro, M. Júnior, W. L. Aldá Pereira, M. Alves Gallo Filho, M. Barroso Ferreira Malbouisson, H. Brandao Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. De Souza, S. Fonseca De Souza, R. Gomes Martins, J. Herrera, C. Mora Mundim, L. Nogima, H. Pinheiro, J.P. Santoro, A. Sznajder, A. Thiel, M. Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liu, J. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos 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 Sun Yat-sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang 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 Faculty of Science University of Split 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 Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysic

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors. © The Author(s) 2024.

关键词： CMS Machine learning Offline and computing

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Measurement of the inclusive tt¯ production cross section in the lepton+jets channel in pp collisions at s=7 TeV with the ATLAS detector using support vector machines

引用

Physical Review D 2023年第3期108卷 032014-032014页

作者： M. Aaboud G. Aad B. Abbott D. C. Abbott D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya S. Adachi L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra F. Ahmadov G. Aielli S. Akatsuka T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa D. Alexandre T. Alexopoulos M. Alhroob B. Ali G. Alimonti J. Alison S. P. Alkire C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. I. Alstaty M. Alvarez Estevez B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen C. F. Anders J. K. Anders A. Andreazza V. Andrei C. R. Anelli S. Angelidakis I. Angelozzi A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo L. Aperio Bella G. Arabidze J. P. Araque V. Araujo Ferraz R. Araujo Pereira A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster L. J. Armitage A. Armstrong O. Arnaez H. Arnold G. Artoni S. Artz S. Asai N. A. Asbah E. M. Asimakopoulou L. Asquith K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten G. Avolio R. Avramidou M. K. Ayoub A. M. Azoulay G. Azuelos A. E. Baas M. J. Baca H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines M. Bajic C. Bakalis O. K. Baker P. J. Bakker D. Bakshi Gupta S. Balaji E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero T. Barillari M-S. Barisits J. Barkeloo T. Barklow R. Barnea S. L. LPMR Faculté des Sciences Université Mohamed Premier Oujda Morocco CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom 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 High Energy Physics Division Argonne National Laboratory Argonne Illinois USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Türkiye Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Physics Radboud University/Nikhef Nijmegen Netherlands Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Departamento de Física Teórica y del Cosmos Universidad de Granada

A measurement of the top quark pair-production cross section in the lepton+jets decay channel is presented. It is based on 4.6 fb−1 of s=7 TeV pp collision data collected during 2011 by the ATLAS experiment at the CERN Large Hadron Collider. A three-class, multidimensional event classifier based on support vector machines is used to differentiate tt¯ events from backgrounds. The tt¯ production cross section is found to be σtt¯=168.5±0.7(stat) −5.9+6.2(syst) −3.2+3.4(lumi) pb. The result is consistent with the Standard Model prediction based on QCD calculations at next-to-next-to-leading order.

关键词： Particle production Top quark Hadron colliders

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EKT: Exercise-aware knowledge tracing for student performance prediction

arXiv

引用

arXiv 2019年

作者： Liu, Qi Huang, Zhenya Yin, Yu Chen, Enhong Xiong, Hui Su, Yu Hu, Guoping Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Techonology University of Science and Technology of China Management Science and Information Systems Department Rutgers Business School State University of New Jersey Rutgers United States Iflytek Research Iflytek Co. Ltd Hefei Anhui000000 China

For offering proactive services (e.g., personalized exercise recommendation) to the students in computer supported intelligent education, one of the fundamental tasks is predicting student performance (e.g., scores) on future exercises, where it is necessary to track the change of each student's knowledge acquisition during her exercising activities. Unfortunately, to the best of our knowledge, existing approaches can only exploit the exercising records of students, and the problem of extracting rich information existed in the materials (e.g., knowledge concepts, exercise content) of exercises to achieve both more precise prediction of student performance and more interpretable analysis of knowledge acquisition remains underexplored. To this end, in this paper, we present a holistic study of student performance prediction. To directly achieve the primary goal of performance prediction, we first propose a general Exercise-Enhanced Recurrent Neural Network (EERNN) framework by exploring both student's exercising records and the text content of corresponding exercises. In EERNN, we simply summarize each student's state into an integrated vector and trace it with a recurrent neural network, where we design a bidirectional LSTM to learn the encoding of each exercise from its content. For making final predictions, we design two implementations on the basis of EERNN with different prediction strategies, i.e., EERNNM with Markov property and EERNNA with Attention mechanism. Then, to explicitly track student's knowledge acquisition on multiple knowledge concepts, we extend EERNN to an explainable Exercise-aware Knowledge Tracing (EKT) framework by incorporating the knowledge concept information, where the student's integrated state vector is now extended to a knowledge state matrix. In EKT, we further develop a memory network for quantifying how much each exercise can affect the mastery of students on multiple knowledge concepts during the exercising process. Finally, we con

关键词： Forecasting

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