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Measurement of the tt¯ cross section and its ratio to the Z production cross section 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 848卷

作者： Aad, G. Abbott, B. Abbott, D.C. Abdinov, O. Abud, A. Abed Abeling, K. Abhayasinghe, D.K. Abidi, s.H. AbouZeid, O.s. Abraham, N.L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.s. Achkar, B. Adachi, s. Adam, L. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Adelman, J. Adersberger, M. Adiguzel, A. Adorni, s. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Aggarwal, A. Agheorghiesei, C. Aguilar-saavedra, J.A. Ahmadov, F. Ahmed, W.s. Ai, X. Aielli, G. Akatsuka, s. Åkesson, T.P.A. Akilli, E. Akimov, A.V. Al Khoury, K. Alberghi, G.L. Albert, J. Verzini, M. J. Alconada Alderweireldt, s. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexandre, D. Alexopoulos, T. Alfonsi, A. Alhroob, M. Ali, B. Alimonti, G. Alison, J. Alkire, s.P. Allaire, C. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Estevez, M. Alvarez Piqueras, D. Álvarez Alviggi, M.G. Coutinho, Y. Amaral Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Dos santos, s. P. Amor Amoroso, s. Amrouche, C.s. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, C.F. Anders, J.K. Andreazza, A. Andrei, V. Anelli, C.R. Angelidakis, s. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Pozo, J. A. Aparisi Bella, L. Aperio Arabidze, G. Araque, J.P. Ferraz, V. Araujo Pereira, R. Araujo Arcangeletti, C. Arce, A.T.H. Arduh, F.A. Arguin, J.-F. Argyropoulos, s. Arling, J.-H. Armbruster, A.J. Armitage, L.J. Armstrong, A. Arnaez, O. Arnold, H. Artamonov, A. Artoni, G. Artz, s. Asai, s. Asbah, N. Asimakopoulou, E.M. Asquith, L. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Atmani, H. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M.K. Azoulay, A.M. Azuelos, G. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A.J. Bailey, V.R. Baines, J.T. Bajic, M. Bakalis, C. Baker, O.K. Bakker, P.J. Gupta, D. Bakshi Balaji, s. Baldin, E.M. Balek, P. Balli, F. Balunas, W.K. Balz, J. Banas, E. Bandyopadhyay CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States Department of Physics University of Massachusetts Amherst MA United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany 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 IL United States CERN Geneva Switzerland INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King's College London London United Kingdom International Center for Elementary Particle Physics Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany IJCLab Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb IL United States Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Istanbul University Dept. of Physics Istanbul Turkey Bruno Kessler Foundation Trento Italy Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laborato

The inclusive top-quark-pair production cross section σtt¯ and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at s=13.6 TeV, using 29 fb−1 of data collected in ...

The inclusive top-quark-pair production cross section σtt¯sub> and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at s=13.6 TeV, using 29 fb−1sup> of data collected in 2022 with the ATLAs experiment at the Large Hadron Collider. Using events with an opposite-charge electron-muon pair and b-tagged jets, and assuming standard Model decays, the top-quark-pair production cross section is measured to be σtt¯sub>=850±3(stat.)±18(syst.)±20(lumi.) pb. The ratio of the tt¯ and the Z-boson production cross sections is also measured, where the Z-boson contribution is determined for inclusive e+sup>e−sup> and μ+sup>μ−sup> events in a fiducial phase space. The relative uncertainty on the ratio is reduced compared to the tt¯ cross section, thanks to the cancellation of several systematic uncertainties. The result for the ratio, Rtt¯/Zsub>=1.145±0.003(stat.)±0.021(syst.)±0.002(lumi.) is consistent with the standard Model prediction using the PDF4LHC21 PDF set. © 2023 The Author(s)

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Investigating the blazar TXs 0506+056 through sharp multi-wavelength eyes during 2017-2019

arXiv

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arXiv 2022年

作者： Acciari, V.A. Aniello, T. Ansoldi, s. Antonelli, L.A. Arbet Engels, A. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Berti, A. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Bošnjak, Ž. Busetto, G. Carosi, R. Ceribella, G. Cerruti, M. Chai, Y. Chilingarian, A. Cikota, s. Colombo, E. Contreras, J.L. Cortina, J. Covino, s. D'Amico, G. D'Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Fallah Ramazani, V. Fariña, L. Fattorini, A. Font, L. Fruck, C. Fukami, s. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, s. Gaug, M. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hoang, J. Hrupec, D. Hütten, M. Inada, T. Iotov, R. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Jouvin, L. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, s. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, s. Machado de Oliveira Fraga, B. Maggio, C. Majumdar, P. Makariev, M. Mallamaci, M. Maneva, G. Manganaro, M. Mannheim, K. Mariotti, M. Martínez, M. Mas Aguilar, A. Mazin, D. Menchiari, s. Mender, s. Mićanović, s. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Moralejo, A. Morcuende, D. Moreno, V. Moretti, E. Nakamori, T. Nava, L. Neustroev, V. Nievas Rosillo, M. Nigro, C. Nilsson, K. Nishijima, K. Noda, K. Nozaki, s. Ohtani, Y. Oka, T. Otero-santos, J. Paiano, s. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. Pavletić, L. Peñil, P. Persic, M. Pihet, M. Prada Moroni, P.G. Prandini, E. Priyadarshi, C. Puljak, I. Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Rome Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Bellaterra BarcelonaE-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil Università di Padova INFN PadovaI-35131 Italy University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland ZeuthenD-15738 Germany ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy Bellaterra BarcelonaE-08193 Spain INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Department of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku TurkuFI-20014 Finland Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Japanese MAGIC Group: Physics Program Graduate School of Advanced Science and Engineering Hiroshi

The blazar TXs 0506+056 got into the spotlight of the astrophysical community in september 2017, when a high-energy neutrino detected by IceCube (IceCube-170922A) was associated at the 3 σ level to a γ-ray flare from this source. This multi-messenger photon-neutrino association remains, as per today, the most significant one ever observed. TXs 0506+056 was a poorly studied object before the IceCube-170922A event. To better characterize its broad-band emission, we organized a multi-wavelength campaign lasting 16 months (November 2017 to February 2019), covering the radio-band (Metsähovi, OVRO), the optical/UV (AsAs-sN, KVA, REM, swift/UVOT), the X-rays (swift/XRT, NusTAR), the high-energy γ rays (Fermi/LAT) and the very-high-energy (VHE) γ rays (MAGIC). In γ rays, the behaviour of the source was significantly different from the 2017 one: MAGIC observations show the presence of flaring activity during December 2018, while the source only shows an excess at the 4 σ level during the rest of the campaign (74 hours of accumulated exposure);Fermi/LAT observations show several short (days-to-week timescale) flares, different from the long-term brightening of 2017. No significant flares are detected at lower energies. The radio light curve shows an increasing flux trend, not seen in other wavelengths. We model the multi-wavelength spectral energy distributions in a lepto-hadronic scenario, in which the hadronic emission emerges as Bethe-Heitler and pion-decay cascade in the X-rays and VHE γ rays. According to the model presented here, the December 2018 γ-ray flare was connected to a neutrino emission that was too brief and not bright enough to be detected by current neutrino instruments. © 2022, CC BY.

关键词： Gamma rays

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Origin of temperature and field dependence of magnetic skyrmion size in ultrathin nanodots

arXiv

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arXiv 2017年

作者： Tomasello, R. Guslienko, K.Y. Ricci, M. Giordano, A. Barker, J. Carpentieri, M. Chubykalo-Fesenko, O. Finocchio, G. Dept. Engineering Polo Scientifico Didattico di Terni University of Perugia Terni50100 Italy Depto. Física de Materiales Universidad Del País Vasco UPV/EHU San Sebastián20018 Spain IKERBASQUE Basque Foundation for Science Bilbao48013 Spain Dept. Computer Science Modeling Electronics and System Science University of Calabria RendeI-87036 Italy Dept. Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina Messina98166 Italy Institute for Materials Research Tohoku University Sendai980-8577 Japan Dept. Electrical and Information Engineering Politecnico di Bari Bari70125 Italy Instituto de Ciencia de Materiales de Madrid CSIC Cantoblanco Madrid28049 Spain

Understanding the physical properties of magnetic skyrmions is important for fundamental research with the aim to develop new spintronic device paradigms where both logic and memory can be integrated at the same level. Here, we show a universal model based on the micromagnetic formalism that can be used to study skyrmion stability as a function of magnetic field and temperature. We consider ultrathin, circular ferromagnetic magnetic dots. Our results show that magnetic skyrmions with a small radius-compared to the dot radius-are always metastable, while large radius skyrmions form a stable ground state. The change of energy profile determines the weak (strong) size dependence of the metastable (stable) skyrmion as a function of temperature and/or field. These results can open a path toward the design of optimal materials for skyrmion based devices. Copyright © 2017, The Authors. All rights reserved.

关键词： Magnetism

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Erratum to: search for squarks and gluinos in final states with one isolated lepton, jets, and missing transverse momentum at s = 13 TeV with the ATLAs detector

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The European Physical Journal C 2021年第10期81卷 1-15页

作者： Aad, G. Abbott, B. Abbott, D. C. Abed Abud, A. Abeling, K. Abhayasinghe, D. K. Abidi, s. H. AbouZeid, O. s. Abraham, N. L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. s. Achkar, B. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Adelman, J. Adiguzel, A. Adorni, s. Adye, T. Affolder, A. A. Afik, Y. Agapopoulou, C. Agaras, M. N. Aggarwal, A. Agheorghiesei, C. Aguilar-saavedra, J. A. Ahmad, A. Ahmadov, F. Ahmed, W. s. Ai, X. Aielli, G. Akatsuka, s. Akbiyik, M. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Al Khoury, K. Alberghi, G. L. Albert, J. Alconada Verzini, M. J. 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. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Alunno Camelia, E. Alvarez Estevez, M. Alviggi, M. G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos santos, s. P. Amoroso, s. Amrouche, C. s. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, J. K. Andrean, s. Y. Andreazza, A. Andrei, V. Anelli, C. R. 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. Aparisi Pozo, J. A. Aparo, M. A. Aperio Bella, L. Aranzabal, N. Araujo Ferraz, V. Araujo Pereira, R. Arcangeletti, C. Arce, A.T. H. Arguin, J.-F. Argyropoulos, s. Arling, J.-H. Armbruster, A. J. Armstrong, A. Arnaez, O. Arnold, H. Arrubarrena Tame, Z. P. Artoni, G. Asada, H. Asai, K. Asai, s. Asawatavonvanich, T. Asbah, N. 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. Austrup, V. A. Avolio, G. Ayoub, M. K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A. J. Bailey, V. R. Baines, J. T. Bakalis, C. Baker, O. K. Bakker, P. J. Bakos, E. Bakshi Gupta, D. Balaji, s. Balasubramanian, R. Baldin, E. M. Balek, P. Balli, F. Balunas CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA Department of Physics University of Massachusetts Amherst USA CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham UK Department of Physics University of Toronto Toronto Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton UK 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 USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Department of Physics Northern Illinois University DeKalb USA Department of Physics Bogazici University Istanbul Turkey Dept. of Physics Istanbul University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Geneva Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot UK Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz USA IJCLab CNRS/IN2P3 Université Paris-Saclay Orsay France LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Physics Radboud University/Nikhef Nijmegen The Netherlands Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física E

A correction to this paper has been published: 10.1140/epjc/s10052-021-09344-w

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Long-term multi-wavelength study of 1Es 0647+250

arXiv

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arXiv 2022年

作者： Acciari, MAGIC Collaboration V.A. Aniello, T. Ansoldi, s. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Berti, A. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Carosi, R. Carretero-Castrillo, M. Ceribella, G. Chai, Y. Chilingarian, A. Cikota, s. Colombo, E. Contreras, J.L. Cortina, J. Covino, s. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Fallah Ramazani, V. Fariña, L. Fattorini, A. Font, L. Fruck, C. Fukami, s. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, s. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Inada, T. Iotov, R. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, s. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, s. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Manganaro, M. Mangano, s. Mannheim, K. Mariotti, M. Martínez, M. Mas Aguilar, A. Mazin, D. Menchiari, s. Mender, s. Mićanović, s. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Moreno, V. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Nievas Rosillo, M. Nigro, C. Nilsson, K. Nishijima, K. Njoh Ekoume, T. Noda, K. Nozaki, s. Ohtani, Y. Oka, T. Otero-santos, J. Paiano, s. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. Pavletić, L. Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna La LagunaE-38200 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain ZeuthenD-15738 Germany ETH Zürich ZürichCH-8093 Switzerland Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Department of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany University of Geneva Chemin d’Ecogia 16 VersoixCH-1290 Switzerland Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku TurkuFI-20014 Finland Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Japanese MAGIC Grou

Context. The BL Lac object 1Es 0647+250 is one of the few distant γ-ray emitting blazars detected at very high energies (VHEs;&100 GeV) during a non-flaring state. It was detected with the MAGIC telescopes during a period of low activity in the years 2009-2011 as well as during three flaring activities in the years 2014, 2019, and 2020, with the highest VHE flux in the last epoch. An extensive multi-instrument data set was collected as part of several coordinated observing campaigns over these years. Aims. We aim to characterise the long-term multi-band flux variability of 1Es 0647+250, as well as its broadband spectral energy distribution (sED) during four distinct activity states selected in four different epochs, in order to constrain the physical parameters of the blazar emission region under certain assumptions. Methods. We evaluated the variability and correlation of the emission in the different energy bands with the fractional variability and the Z-transformed discrete correlation function, as well as its spectral evolution in X-rays and γ rays. Owing to the controversy in the redshift measurements of 1Es 0647+250 reported in the literature, we also estimated its distance in an indirect manner through a comparison of the GeV and TeV spectra from simultaneous observations with Fermi-LAT and MAGIC during the strongest flaring activity detected to date. Moreover, we interpret the sEDs from the four distinct activity states within the framework of one-component and two-component leptonic models, proposing specific scenarios that are able to reproduce the available multi-instrument data. Results. We find significant long-term variability, especially in X-rays and VHE γ rays. Furthermore, significant (3-4σ) correlations were found between the radio, optical, and high-energy (HE) γ-ray fluxes, with the radio emission delayed by about ∼400 days with respect to the optical and γ-ray bands. The spectral analysis reveals a harder-when-brighter trend during the non-flar

关键词： Gamma rays

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Relevance’s of using E-learning systems & technology in INDIA: Tutoring practice

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International Journal of u- and e- service, science and Technology 2016年第8期9卷 111-132页

作者： VeeraManickam, M.R.M. Mohanapriya, M. Bhattacharyya, Debnath Karpagam University Dept. of CSE Coimbatore India Department of Computer Science and Engineering Vignan’s Institute of Information Technology Visakhapatnam530049 India

Traditional classroom teaching and learning processes are not in full-fledged utilizing latest new technology for teaching learning system at various college levels which in high demand. This article describe valuable concept to get awareness to the principal governing educational sector in India to the vital need of shifting from traditional system to an e-learning practice system using Data centers deployments and latest technology. In advance it focuses on significance necessity of infrastructure which is high demand to use in educational institute to improve effectiveness and value of teaching and learning process through e-learning. Major issues are in Indian Educational sector is e-learning system decentralized model and proposed model provides solution for centralized system features and illustrate its importance of Cloud Datacenter model-Dac and its significances. © 2016 sERsC.

关键词： E-learning

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A comparative study of K-Means, DBsCAN and OPTICs

A comparative study of K-Means, DBSCAN and OPTICS

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International Conference on computer Communication and Informatics (ICCCI)

作者： Hari Krishna Kanagala V.V. Jaya Rama Krishnaiah Department of MCA Vignan's Lara Institute of Technology & Sci. Vadlamudi India Dept. of Computer Science & Engineering ASN Women's Engineering College Tenali India

ISBN: (纸本)9781467366816

In view of today's information available, recent progress in data mining research has lead to the development of various efficient methods for mining interesting patterns in large databases. It plays a vital role in knowledge discovery process by analyzing the huge data from various sources and summarizing it into useful information. It is helpful for analyzing the volumes of data in different domains like Marketing, Health, science and Technology. Cluster analysis is widely used approach to notice the trends in the volumes of data. In this paper, we evaluated the performance of the different clustering approaches like as K-Means, DBsCAN, and OPTICs in terms of accuracy, outlier's formation, and cluster size prediction.

关键词： Optics Clustering algorithms computers Informatics Data mining Partitioning algorithms shape

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Optimal CMB lensing reconstruction and parameter estimation with sPTpol data

arXiv

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arXiv 2020年

作者： Millea, Marius Daley, C.M. Chou, T.-L. Anderes, E. Ade, P.A.R. Anderson, A.J. Austermann, J.E. Avva, J.s. Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bleem, L.E. Carlstrom, J.E. Chang, C.L. Chaubal, P. Chiang, H.C. Citron, R. Corbett Moran, C. Crawford, T.M. Crites, A.T. de Haan, T. Dobbs, M.A. Everett, W. Gallicchio, J. George, E.M. Goeckner-Wald, N. Guns, s. Gupta, N. Halverson, N.W. Henning, J.W. Hilton, G.C. Holder, G.P. Holzapfel, W.L. Hrubes, J.D. Huang, N. Hubmayr, J. Irwin, K.D. Knox, L. Lee, A.T. Li, D. Lowitz, A. McMahon, J.J. Meyer, s.s. Mocanu, L.M. Montgomery, J. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Omori, Y. Padin, s. Patil, s. Pryke, C. Reichardt, C.L. Ruhl, J.E. saliwanchik, B.R. schaffer, K.K. sievers, C. smecher, G. stark, A.A. Thorne, B. Tucker, C. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Wu, W.L.K. Yefremenko, V. Department of Physics University of California BerkeleyCA94720 United States Astronomy Department University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Statistics University of California One Shields Avenue DavisCA95616 United States Cardiff University CardiffCF10 3XQ United Kingdom Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics McGill University 3600 Rue University MontrealQCH3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Jet Propulsion Laboratory PasadenaCA91109 United States Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Department of Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Canadian Institute for Advanced Research CIFAR Program in Gravity Extreme Universe TorontoONM5G 1Z8 Canada Department of Astrophysical and Pla

We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg2 of polarization observations from the sPTpol receiver on the south Pole Telescope. These data reach noise levels as low as 5.8 µK-arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly sub-optimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be Aφ = 0.949 ±0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist "bias hardening," and reducing the systematic uncertainty on Aφ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain Aφ along with AL, the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with sPT-3G, simons Observatory, and CMB-s4, where improvements relative to the QE can reach 1.5 times tighter constraints on Aφ and 7 times lower effective lensing reconstruction noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Cosmology

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATs challenge

arXiv

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arXiv 2018年

作者： Bakas, spyridon Reyes, Mauricio Jakab, Andras Bauer, stefan Rempfler, Markus Crimi, Alessandro shinohara, Russell Takeshi Berger, Christoph Ha, sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, sotirios Brown, James Cabezas, Mariano Cao, shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius s. Chandra, siddhartha Chang, Yi-Ju Chang, shiyu Chang, Ken Chazalon, Joseph Chen, shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, sandra Grosges, T. Guan, Yuanfang Guo, sheng Gupta, sudeep Han, Woo-sup Han, Il song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor segmentation (BraTs) challenge, i.e., 2012-2018. specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIsT/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTs dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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simulation and modeling of response of buried pipes using FDTD and RsM

Simulation and modeling of response of buried pipes using FD...

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Proceedings of the International Conference on Ground Penetrating Radar, GPR

作者： A. V. Hebsur E. P. Rao N. Muniappan G. Venkatachalam Dept. of Civil Engg. Vignan's Foundation for Science Technology and Research University Guntur AP India Dept. of Civil Engg. IIT Bombay Mumbai Maharastra India Dept. of Civil Engg. V. V. College of Engineering Tisaiyanvilai Mukesh Patel School of Technology Management and Engineering NMIMS (Deemed-to-be University) Mumbai

ISBN: (纸本)9781509051823

Interpretation of B-scans gathered using a GPR is often difficult. The difficulty can be resolved to a large extent if responses of common objects under different scenarios are known. Finite difference time domain (FDTD) simulation is widely used to understand the response of buried objects to GPR under diverse object-ground scenarios. However, relating these responses to discern inherent patterns and trends has not been attempted by many. One useful tool for establishing relations between the responses under diverse conditions is the response surface method (RsM). The study presented here uses RsM along with FDTD simulation of response from buried pipes, modeled as circular air voids in a semi-infinite medium. The GPR response of a pipe is a function of object, host medium, and antenna characteristics. The response of GPR is treated as a RsM 4-parameter 3-level problem requiring 81 simulations; which are obtained from the FDTD method based on the GPRMax v2.0 simulator. The GPR responses considered here are the amplitude at the crown of each hyperbola and axes of each hyperbola (`a' and `b'). The computed amplitudes and hyperbola axes are expressed as functions of influencing parameters. Trend lines are drawn to illustrate the dependence of amplitudes on the parameters varied. The relationships for the axes of the hyperbolas are useful to estimate the size and dept. of a pipe. The FDTD simulation combined with RsM helps to understand the response for any scenario falling within the chosen range without further computation-intensive simulations.

关键词： Decision support systems Analysis of variance Indexes

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