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arXiv 2020年

作者： González-Santamaría, Iker Manteiga, M. Manchado, A. Gómez-Muñoz, M.A. Ulla, A. Dafonte, C. Department of Computer Science and Information Technologies Campus Elviña s/n Coruña15071 A Spain CITIC Centre for Information and Communications Technologies Research Universidade da Coruña Campus de Elviña s/n A Coruña15071 Spain Department of Nautical Sciences and Marine Engineering Paseo de Ronda 51 A Coruña15011 Spain Instituto de Astrofísica de Canarias La Laguna Tenerife38200 Spain Astrophysics Department Spain CSIC Spain Instituto de Astronomía Universidad Nacional Autónoma de México Apdo. Postal 877 EnsenadaB. C.22800 Mexico Applied Physics Department Campus Lagoas-Marcosende s/n Vigo36310 Spain

Context. Gaia Data Release 2 (DR2) was used to select a sample of 211 central stars of planetary neb.lae (CSPNe) with good quality astrometric measurements, that we refer to as GAPN, Golden Astrometry Planetary Neb.lae. Gaia astrometric and photometric measurements allowed us to derive accurate distances and radii, and to calculate luminosities with the addition of self-consistent literature values. Such information was used to plot the position of these stars in a Hertzsprung-Russel (HR) diagram and to study their evolutionary status in comparison with CSPNe evolutionary tracks. Aims. The extremely precise measurement of parallaxes and proper motions in Gaia DR2 has allowed us to search for wide b.nary companions in a region close to each of the central stars in the GAPN sample. We are interested in estab.ishing the presence of b.nary companions at large separations which could allow to add further information on the influence of b.narity on the formation and evolution of planetary neb.lae. We aim to study the evolutive properties of the b.nary pairs to check the consistency of spectral types and masses in order to b.tter constrain the ages and evolutionary stage of the CSPNe. Methods. We limited our search to a region around 20,000 AU of each CSPN to minimise accidental detections, and only considered stars with good parallax and proper motions data, i.e. with errors b.low 30% in DR2. We determined that the hypothetical b.nary pairs should show a statistically significant agreement for the three astrometric quantities, i.e. parallax and b.th components of proper motions. Results. We found 8 wide b.nary systems among our GAPN sample. One of them is in a triple system. We compiled the astrometric and photometric measurements of these b.nary systems and discussed them in comparison with previously pub.ished searches for b.naries in PNe. b. analysing the position in the HR diagram of the companion stars using Gaia photometry, we are ab.e to estimate their temperatures

关键词： Stars

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The CMS Statistical Analysis and Comb.nation Tool: Comb.ne

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Computing and Software for b.g science 2024年第1期8卷 1-45页

作者： Zhokin, A. Zhizhin, I. Zarub.n, A. Yuldashev, b.S. Voytishin, N. Vorotnikov, G. Vorob.ev, A. Volkov, P. Uzunian, A. Uvarov, L. Toropin, A. Tlisova, I. Teryaev, O. Terkulov, A. Tcherniaev, E. Sulimov, V. Sosnov, D. Smirnov, V. Slab.spitskii, 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. Ob.aztsov, 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. Grib.shin, A. Gorb.nov, I. Golutvin, I. Golub.v, N. Golovtcov, V. Gninenko, S. Gavrilov, V. Gavrilov, G. Dudko, L. Dub.nin, M. Druzhkin, D. Dimova, T. Dermenev, A. Chistov, R. Chekhovsky, V. Chadeeva, M. b.nichev, V. b.dkouski, D. b.rshch, V. b.os, E. b.inov, V. b.b.ev, 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 b.uyn, I. Dasu, S. b.se, T. b.ack, K. b.nerjee, S. Aravind, A. Karchin, P.E. b.attacharya, 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. Volob.uev, 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. Euseb., R. b.uhali, O. Akhter, T. Ahmad, M. Aeb., D. Spanier, S. Nib.gira, E. Lee, L. Karunarathna, N. Kanuganti, A.R. Holmes, T. Higginb.tham, 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 describ.s the Comb.ne software package used for statistical analyses b. the CMS Collab.ration. The package, originally designed to perform searches for a Higgs b.son and the comb.ned analysis of those searches, has evolved to b.come the statistical analysis tool presently used in the majority of measurements and searches performed b. the CMS Collab.ration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collab.ration, providing an outline of the most salient features and capab.lities. Readers are provided with the possib.lity to run Comb.ne and reproduce examples provided in this paper using a pub.icly availab.e 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 Comb.ne. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. © CERN, for the b.nefit of the CMS Collab.ration 2024.

关键词： CMS Comb.ne Higgs Higgs b.son Statistics

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Search for W′ b.sons decaying to a top and a b.ttom quark in leptonic final states in proton-proton collisions at s = 13 TeV

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Journal of High Energy Physics 2024年第5期2024卷 46页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. b.rgauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Liko, D. Mikulec, I. Schieck, J. Schöfb.ck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenb.rger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Van Mechelen, P. b.ls, E.S. D’hondt, J. Dansana, S. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Van Putte, S. Vannerom, D. Clerb.ux, b. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Khalilzadeh, A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden b.mden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dob.r, D. Hong, Y. Knolle, J. Lamb.echt, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Van Den b.ssche, N. Wezenb.ek, L. b.necke, A. b.uno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Menezes De Oliveira, T. Moraes, A. Reb.llo Teles, P. Soeiro, M. Aldá Júnior, W.L. Alves Gallo Pereira, M. b.rroso Ferreira Filho, M. b.andao Malb.uisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. b.rnardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. 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. Ivanov, T. Litov, L. Pavlov, b. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. b.uer, G. Hu, Z. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos, A. b.n, Y. Lev 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 Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang 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 Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

A search for W′ b.sons decaying to a top and a b.ttom quark in final states including an electron or a muon is performed with the CMS detector at the LHC. The analyzed data correspond to an integrated luminosity of 138 fb.sup>−1 of proton-proton collisions at a center-of-mass energy of 13 TeV. Good agreement with the standard model expectation is ob.erved and no evidence for the existence of the W′ b.son is found over the mass range examined. The largest ob.erved deviation from the standard model expectation is found for a W′ b.son mass (mWb.′b.) hypothesis of 3.8 TeV with a relative decay width of 1%, with a local (glob.l) significance of 2.6 (2.0) standard deviations. Upper limits on the production cross sections of W′ b.sons decaying to a top and a b.ttom quark are set. Left- and right-handed W′ b.sons with mWb.′b. b.low 3.9 and 4.3 TeV, respectively, are excluded at the 95% confidence level, under the assumption that the new particle has a narrow decay width. Limits are also set for relative decay widths up to 30%. © The Author(s) 2024.

关键词： b.yond Standard Model Hadron-Hadron Scattering Vector b.son Production

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RETRACTED ARTICLE: Energy consumption analysis of Virtual Machine migration in cloud using hyb.id swarm optimization (Ab.–b.)

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The Journal of Supercomputing 2018年第5期76卷 3374-3390页

作者： Karthikeyan, K. Sunder, R. Shankar, K. Lakshmanaprab., S. K. Vijayakumar, V. Elhoseny, Mohamed Manogaran, Gunasekaran Department of Computer Applications Anna University Regional Campus Madurai Madurai India Department of Computer Science and Engineering Sahrdaya College of Engineering and Technology Kodakara India School of Computing Kalasalingam Academy of Research and Education Krishnankoil India Department of Electronics and Instrumentation Engineering B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai India School of Computing Science and Engineering Vellore Institute of Technology Chennai India CoVIS Lab University of North Texas Denton USA University of California Davis USA

A cloud data center consumes more energy for computation and switching servers b.tween modes. Virtual Machine (VM) migration enhances the execution of cloud server farm in terms of energy proficiency, adaptation to internal failure, and accessib.lity. Cloud suppliers, b. that as it may, ought to likewise enhance for amounts like energy consumption and administrations costs and in this manner, trying to have all the Virtual Machines with the least measures of physical equipment machines conceivab.e. The part of virtualization is critical and its execution is sub.ected to VM migration and machine allotment. A greater amount of the energy is caught up in the cloud; consequently, the use of various calculations is required for sparing energy and productivity upgradation in the proposed work. In the proposed work, the Naive b.yes classifier with hyb.id optimization using Artificial b.e Colony–b.t Algorithm (Ab.–b.) was implemented to reduce the energy consumption in VM migration. The proposed method was evaluated in CloudSim and the performances were compared using performance index such as success &failure rate, and energy consumption. It is ob.erved from the implementation results that the proposed method reduces energy consumption compared to other existing methods. From the implementation outcomes of the proposed work, it was understood that the model was ab.e to achieve the minimum energy consumption and failure rate i.e., 1000–1200&nb.p;kWh, 0.2 with maximum success rate and accuracy of 1 and 97.77%.

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Measurement of the τ lepton polarization in Z b.son decays in proton-proton collisions at (Formula presented.)

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Journal of High Energy Physics 2024年第1期2024卷 101页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. b.rgauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Liko, D. Mikulec, I. Schieck, J. Schöfb.ck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenb.rger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Van Mechelen, P. b.ls, E.S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Van Putte, S. Vannerom, D. Clerb.ux, b. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Khalilzadeh, A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden b.mden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dob.r, D. Hong, Y. Knolle, J. Lamb.echt, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Van Den b.ssche, N. Wezenb.ek, L. b.necke, A. b.uno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Menezes De Oliveira, T. Moraes, A. Reb.llo Teles, P. Soeiro, M. Aldá Júnior, W.L. Alves Gallo Pereira, M. b.rroso Ferreira Filho, M. b.andao Malb.uisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. b.rnardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. 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. Ivanov, T. Litov, L. Pavlov, b. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. b.uer, G. Hu, Z. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos, A. b.n, Y. Lev 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 Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang 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 Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

The polarization of τ leptons is measured using leptonic and hadronic τ lepton decays in Z → τ+ τ− events in proton-proton collisions at (Formula presented.) recorded b. CMS at the CERN LHC with an integrated lum... 详细信息

The polarization of τ leptons is measured using leptonic and hadronic τ lepton decays in Z → τ⁺ τ⁻ events in proton-proton collisions at (Formula presented.) recorded b. CMS at the CERN LHC with an integrated luminosity of 36.3 fb.sup>−1. The measured τ⁻ lepton polarization at the Z b.son mass pole is Pb.τb.(Z) = −0.144 ± 0.006 (stat) ± 0.014 (syst) = −0.144 ± 0.015, in good agreement with the measurement of the τ lepton asymmetry parameter of Ab.τb. = 0.1439 ± 0.0043 = − Pb.τb.(Z) at LEP. The τ lepton polarization depends on the ratio of the vector to axial-vector couplings of the τ leptons in the neutral current expression, and thus on the effective weak mixing angle sin² θWeff , independently of the Z b.son production mechanism. The ob.ained value sin² θWeff = 0.2319 ± 0.0008(stat) ± 0.0018(syst) = 0.2319 ± 0.0019 is in good agreement with measurements at e⁺ e⁻ colliders. [Figure not availab.e: see fulltext.]. © 2024, The Author(s).

关键词： Hadron-Hadron Scattering Tau Physics

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Portab.e Acceleration of CMS Computing Workflows with Coprocessors as a Service

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Computing and Software for b.g science 2024年第1期8卷 1-36页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. b.rgauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P.S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfb.ck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenb.rger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Mechelen, P. Van b.ls, 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. Clerb.ux, 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. b.mden, M. Vanden Velde, C. Vander Vanlaer, P. De Coen, M. Dob.r, D. Hong, Y. Knolle, J. Lamb.echt, L. Mestdach, G. Amarilo, K. Mota Rendón, C. Samalan, A. Skovpen, K. b.ssche, N. Van Den Linden, J. van der Wezenb.ek, L. b.necke, A. b.thani, A. b.uno, 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. Reb.llo Soeiro, M. Júnior, W. L. Aldá Pereira, M. Alves Gallo Filho, M. b.rroso Ferreira Malb.uisson, H. b.andao 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 b.rnardes, 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 comb.nations 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 b. easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enab.es high coprocessor usage and enab.es the portab.lity 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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Rob.st field-level likelihood-free inference with galaxies

arXiv

引用

arXiv 2023年

作者： de Santi, Natalí S.M. Shao, Helen Villaescusa-Navarro, Francisco Ab.amo, L. Raul Teyssier, Romain Villanueva-Domingo, Pab.o Ni, Yueying Anglés-Alcázar, Daniel Genel, Shy Hernandez-Martinez, Elena Steinwandel, Ulrich P. Lovell, Christopher C. Dolag, Klaus Castro, Tiago Vogelsb.rger, Mark Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Instituto de Física Universidade de São Paulo R. do Matão 1371 São Paulo05508-900 Brazil Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Bellaterra Barcelona08193 Spain Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States McWilliams Center for Cosmology Department of Physics Carnegie Mellon University PittsburghPA15213 United States Department of Physics University of Connecticut 196 Auditorium Road U-3046 StorrsCT06269 United States Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstr. 1 München81679 Germany Institute of Cosmology and Gravitation University of Portsmouth Burnaby Road PortsmouthPO1 3FX United Kingdom Centre for Astrophysics Research School of Physics Engineering & Computer Science University of Hertfordshire HatfieldAL10 9AB United Kingdom Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching85741 Germany INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34143 Italy INFN Sezione di Trieste Via Valerio 2 TS TriesteI-34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Kavli Institute for Astrophysics and Space Research Department of Physics MIT CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Massachusetts Institute of Technology CambridgeMA02139 United States

We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant and do not impose any cut on scale. From galaxy catalogs that only contain 3D positions and radial velocities of ∼ 1, 000 galaxies in tiny (25 h−1Mpc)3 volumes our models can infer the value of Ωm with approximately 12% precision. More importantly, b. testing the models on galaxy catalogs from thousands of hydrodynamic simulations, each having a different efficiency of supernova and AGN feedb.ck, run with five different codes and sub.rid models – IllustrisTNG, SIMb., Astrid, Magneticum, SWIFT-EAGLE –, we find that our models are rob.st to changes in astrophysics, sub.rid physics, and sub.alo/galaxy finder. Furthermore, we test our models on 1,024 simulations that cover a vast region in parameter space – variations in 5 cosmological and 23 astrophysical parameters – finding that the model extrapolates really well. Our results indicate that the key to b.ilding a rob.st model is the use of b.th galaxy positions and velocities, suggesting that the network have likely learned an underlying physical relation that does not depend on galaxy formation and is valid on scales larger than ∼ 10 h−1kpc. Copyright © 2023, The Authors. All rights reserved.

关键词： Galaxies

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Cloud Platform using b.g Data and HPC technologies for Distrib.ted and Parallels Treatments

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Procedia computer science 2018年 141卷 112-118页

作者： Olivier Deb.uche Sidi Ahmed Mahmoudi Saïd Mahmoudi Pierre Manneb.ck Computer Science Unit Faculty of Engineering University of Mons 20 Place du Parc B-7000 Mons Belgium Biosystems Dynamics and Exchanges Axis Biosystem Engineering Department ULiège Gembloux Agro-Bio Tech University of Liège Passage des Déportés 2 B-5030 Gembloux Belgium

Smart agriculture is one of the most diverse research. In addition, the quantity of data to b. stored and the choice of the most efficient algorithms to process are significant elements in this field. The storage of collecting data from Internet of Things (IoT), existing on distrib.ted, local datab.ses and open data need a particular infrastructure to federate all these data to make complex treatments. The storage of this wide range of data that comes at high frequency and variab.e throughput is particularly difficult. In this paper, we propose the use of distrib.ted datab.ses and high-performance computing architecture in order to exploit multiple re-configurab.e computing and application specific processing such as CPUs, GPUs, TPUs and FPGAs efficiently. This exploitation allows an accurate training for an application to machine learning, deep learning and unsupervised modeling algorithms. The last ones are used for training supervised algorithms on images when it lab.ls a set of images and unsupervised algorithms on IoT data which are unlab.led with variab.e qualities. The processing of data is b.sed on Hadoop 3.1 MapReduce to achieve parallel processing and use containerization technologies to distrib.te treatments on Multi GPU, MIC and FPGA. This architecture allows efficient treatments of data coming from several sources with a cloud high-performance heterogeneous architecture. The proposed 4 layers infrastructure can also implement FPGA and MIC which are now natively supported b. recent version of Hadoop. Moreover, with the advent of new technologies like Intel® Movidius TM ; it is now possib.e to deploy CNN at the Fog level in the IoT network and to make inference with the cloud and therefore limit significantly the network traffic that result in reducing the move of large amounts of data to the cloud.

关键词： GPU FPGA MIC CPU TPU Cloud b.g Data parallel distrib.ted processing heterogeneous cloud architecture

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Resolved neutral outflow from a lensed dusty Star-Forming Galaxy at z=2.09

arXiv

引用

arXiv 2021年

作者： b.tler, Kirsty M. van der Werf, Paul P. Ryb.k, Matus Costa, Tiago Cox, Pierre Weiß, Axel Michalowski, Michal J. Riechers, Dominik A. Rigopoulou, Dimitra Marchetti, Lucia Eales, Stephen Valtchanov, Ivan Leiden Observatory Leiden University PO Box 9513 RA Leiden2300 Netherlands THz Sensing Group Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Netherlands Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching b. MünchenD-85748 Germany Sorbonne Université UPMC Université Paris 6 CNRS UMR 7095 Institut d'Astrophysique de Paris 98b boulevard Arago Paris75014 France Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Astronomical Observatory Institute Faculty of Physics Adam Mickiewicz University ul. Sloneczna 36 Poznan60-286 Poland Department of Astronomy Cornell University Space Sciences Building IthacaNY14853 United States Astrophysics Department of Physics University of Oxford Keble Road OxfordOX1 3RH United Kingdom Department of Astronomy University of Cape Town Private Bag X3 Rondebosch Cape Town7701 South Africa INAF Institute for Radio Astronomy Via Gobetti 101 Bologna40129 Italy School of Physics and Astronomy Cardiff University The Parade CardiffCF24 3AA United Kingdom Telespazio UK for ESA European Space Astronomy Centre Operations Department Villanueva de la CañadaE-28691 Spain

We report the detection of a massive neutral gas outflow in the z=2.09 gravitationally lensed Dusty Star-Forming Galaxy HATLASJ085358.9+015537 (G09v1.40), seen in ab.orption with the OH+(11 − 10) transition using spatially resolved (0.500 × 0.400) Atacama Large Millimeter/sub.illimeter Array (ALMA) ob.ervations. The b.ueshifted OH+ line is ob.erved simultaneously with the CO(9-8) emission line and underlying dust continuum. These data are complemented b. high angular resolution (0.1700 × 0.1300) ALMA ob.ervations of CH+(1-0) and underlying dust continuum, and Keck 2.2 µm imaging tracing the stellar emission. The neutral outflow, dust, dense molecular gas and stars all show spatial offsets from each other. The total atomic gas mass of the ob.erved outflow is 6.7 × 109M☉, > 25% as massive as the gas mass of the galaxy. We find that a conical outflow geometry b.st describ.s the OH+ kinematics and morphology and derive deprojected outflow properties as functions of possib.e inclination (0.38◦ − 64◦). The neutral gas mass outflow rate is b.tween 83 − 25400 M☉ yr−1, exceeding the star formation rate (788 ±300 M☉ yr−1) if the inclination is > 3.6◦ (mass-loading factor = 0.3-4.7). Kinetic energy and momentum fluxes span 4.4 − 290 × 109 L☉ and 0.1 − 3.7 × 1037 dyne, respectively (energy-loading factor = 0.013-16), indicating that the feedb.ck mechanisms required to drive the outflow depend on the inclination assumed. We derive a gas depletion time b.tween 29 and 1 Myr, b.t find that the neutral outflow is likely to remain b.und to the galaxy, unless the inclination is small, and may b. re-accreted if additional feedb.ck processes do not occur. © 2021, CC b..

关键词： Galaxies

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Measurement of the doub.e-differential inclusive jet cross section in proton-proton collisions at s = 5.02 TeV

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Journal of High Energy Physics 2025年第1期2025卷 1-49页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. b.rgauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Schieck, J. Schöfb.ck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenb.rger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Van Mechelen, P. b.ls, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Putte, S. Vannerom, D. Clerb.ux, b. Dansana, S. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden b.mden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dob.r, D. Knolle, J. Lamb.echt, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den b.ssche, N. Vermassen, b. Wezenb.ek, L. b.necke, A. b.uno, G. b.ry, F. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Vischia, P. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Reb.llo Teles, P. Aldá Júnior, W.L. Alves Gallo Pereira, M. b.rroso Ferreira Filho, M. b.andao Malb.uisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. b.rnardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. 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. Ivanov, T. Litov, L. Pavlov, b. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. b.uer, G. Hu, Z. Lezki, S. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, J. Zhang, H. Aga 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 Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Venezuela 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 Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

The inclusive jet cross section is measured as a function of jet transverse momentum pT and rapidity y. The measurement is performed using proton-proton collision data at s = 5.02 TeV, recorded b. the CMS experiment a... 详细信息

The inclusive jet cross section is measured as a function of jet transverse momentum pb.Tb. and rapidity y. The measurement is performed using proton-proton collision data at s = 5.02 TeV, recorded b. the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb.sup>−1. The jets are reconstructed with the anti-kb.Tb. algorithm using a distance parameter of R = 0.4, within the rapidity interval |y| < 2, and across the kinematic range 0.06 < pb.Tb.< 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturb.tive quantum chromodynamics, calculated at b.th next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturb.tive effects, and presented for a variety of parton distrib.tion functions and choices of the renormalization/factorization scales and the strong coupling αb.Sb.. © The Author(s) 2025.

关键词： Hadron-Hadron Scattering Jet Physics QCD

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