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Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at (Formula presented.) TeV with the ATLAS detector

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Journal of High Energy Physics 2024年第4期2024卷 26页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramont Department of Physics University of Adelaide Department of Physics University of Alberta Department of Physics Ankara University Division of Physics TOBB University of Economics and Technology LAPP Université Savoie Mont Blanc CNRS/IN2P3 APC Université Paris Cité CNRS/IN2P3 High Energy Physics Division Argonne National Laboratory Department of Physics University of Arizona Department of Physics University of Texas at Arlington Physics Department National and Kapodistrian University of Athens Physics Department National Technical University of Athens Department of Physics University of Texas at Austin Institute of Physics Azerbaijan Academy of Sciences Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Institute of High Energy Physics Chinese Academy of Sciences Physics Department Tsinghua University Department of Physics Nanjing University School of Science Shenzhen Campus of Sun Yat-sen University University of Chinese Academy of Science (UCAS) Institute of Physics University of Belgrade Department for Physics and Technology University of Bergen Physics Division Lawrence Berkeley National Laboratory University of California Institut für Physik Humboldt Universität zu Berlin Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern School of Physics and Astronomy University of Birmingham Department of Physics Bogazici University Department of Physics Engineering Gaziantep University Department of Physics Istanbul University Facultad de Ciencias y Centro de Investigaciónes Universidad Antonio Nariño Departamento de Física Universidad Nacional de Colombia Dipartimento di Fisica e Astronomia A. Righi Università di Bologna INFN Sezione di Bologna Physikalisches Institut Universität Bonn Department of Physics Boston University Department of Physics Brandeis University Transilvania University of Brasov Horia Hulubei National Institute of Physics and Nuclear Engineering Department of Physics Alexandru

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W^±W^±jj) using 139 fb⁻¹ of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W^±W^±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H^±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H^±± mass near 450 GeV, with a global significance of 2.5 standard deviations. © The Author(s) 2024.

关键词： Hadron-Hadron Scattering Vector Boson Production

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Observation of the Rare Decay of the η Meson to Four Muons

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Physical Review Letters 2023年第9期131卷 091903-091903页

作者： A. Hayrapetyan A. Tumasyan W. Adam J. W. Andrejkovic T. Bergauer S. Chatterjee K. Damanakis M. Dragicevic A. Escalante Del Valle P. S. Hussain M. Jeitler N. Krammer 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 A. Morton 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 J. Knolle L. Lambrecht G. Mestdach C. Rendón A. Samalan K. Skovpen N. Van Den Bossche 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 J. Martins C. Mora Herrera K. Mota Amarilo L. Mundim H. Nogima A. Santoro S. M. Silva Do Amaral 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 T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov E. Shumka S. Keshri S. Thakur T. Cheng Q. Guo T. Javaid M. Mittal L. Yuan G. Bauer Z. Hu K. Yi G. M. Chen H. S. Chen M. Chen F. Iemmi C. H. Jiang A. Kapoor H. Liao Z.-A. Liu F. Monti R. Sharma J. N. Song J. Tao J. Wang H. Zhang A. Agapitos Y. Ban A. Levin C. Li Q. Li X. Lyu Y. Mao S. J. Qian X. Sun D. Wang H. Yang C. Zhou Z. You N. Lu 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 Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussels 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 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 Massachusetts Institute of Technology Cambridge Massachusetts USA 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 Rice University Houston Texas USA 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 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 Phy

A search for the rare η→μ+μ−μ+μ− double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integrated luminosity of 101 fb−1. A signal having a statistical significance well in excess of 5 standard deviations is observed. Using the η→μ+μ− decay as normalization, the branching fraction B(η→μ+μ−μ+μ−)=[5.0±0.8(stat)±0.7(syst)±0.7(B2μ)]×10−9 is measured, where the last term is the uncertainty in the normalization channel branching fraction. This work achieves an improved precision of over 5 orders of magnitude compared to previous results, leading to the first measurement of this branching fraction, which is found to agree with theoretical predictions.

关键词： Mesons Hadron colliders Particle decays

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Smart radio environments

arXiv

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arXiv 2021年

作者： Gradoni, Gabriele Renzo, Marco Di Díaz-Rubio, Ana Tretyakov, Sergei A. Caloz, Christophe Gradoni, Gabriele Peng, Zhen Alu, Andrea Lerosey, Geoffroy Fink, Mathias Galdi, Vincenzo Cui, Tie Jun Frazier, Benjamin W. Anlage, Steven M. Salucci, Marco Massa, Andrea Cheng, Qiang Wang, Jinghe Jin, Shi Dardari, Davide Decarli, Nicoló Yurduseven, Okan Matthaiou, Michail Kenney, Mitchell Gordon, George Georgiou, Orestis Nguyen, Cam Ly Martini, Enrica Maci, Stefano Wakatsuchi, Hiroki Phang, Sendy School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Laboratoire des Signaux et Systémes CNRS CentraleSupélec Université Paris-Saclay Gif-sur-Yvette Paris France Department of of Electronics and Nanoengineering Aalto University Espoo Finland META Research Group KU Leuven Belgium School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham University Park NG72RD United Kingdom Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign IL United States Advanced Science Research Center City University of New York United States Greenerwave 6 rue Jean Calvin Paris75005 France Institut Langevin 1 rue Jussieu Paris75005 France Fields & Waves Lab Department of Engineering University of Sannio Benevento Italy State Key Laboratory of Millimeter Waves Southeast University Nanjing China Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Department of Electrical and Computer Engineering Department of Physics Quantum Materials Center University of Maryland College ParkMD20742 United States Trento Italy Chengdu China Beijing China Institute of Electromagnetic Space State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing China University of Bologna Bologna Italy Bologna Italy Centre for Wireless Innovation Institute of Electronics Communications and Information Technology Queen’s University Belfast Belfast United Kingdom Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Wireless System Laboratory Corporate Research & Development Center Toshiba Corporation Kawasaki Japan Department of Information Engineering an

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Meta-surface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G. © 2021, CC BY.

关键词： Electromagnetic wave propagation

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Nonresonant central exclusive production of charged-hadron pairs in proton-proton collisions at s=13 TeV

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Physical Review D 2024年第11期109卷 112013-112013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 G. P. Van Onsem S. Van Putte D. Vannerom B. Clerbaux A. K. Das G. De Lentdecker L. Favart P. Gianneios 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 K. Mota Amarilo C. Rendón A. Samalan K. Skovpen N. Van Den Bossche J. van der Linden L. Wezenbeek A. Benecke A. Bethani 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 L. Mundim H. Nogima J. P. Pinheiro 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 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 Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Indian Institute of Technology Madras Madras India 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 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 California Institute of Technology Pasadena California USA University of Florida Gainesville Florida USA Massachusetts Institute of Technology Cambridge Massachusetts USA 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 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

The central exclusive production of charged-hadron pairs in pp collisions at a center-of-mass energy of 13 TeV is examined, based on data collected in a special high-β* run of the LHC. The nonresonant continuum processes are studied with the invariant mass of the centrally produced two-pion system in the resonance-free region, mπ+π−<0.7 or mπ+π−>1.8 GeV. Differential cross sections as functions of the azimuthal angle between the surviving protons, squared exchanged four-momenta, and mπ+π− are measured in a wide region of scattered proton transverse momenta, between 0.2 and 0.8 GeV, and for pion rapidities |y|<2. A rich structure of interactions related to double-pomeron exchange is observed. A parabolic minimum in the distribution of the two-proton azimuthal angle is observed for the first time. It can be interpreted as an effect of additional pomeron exchanges between the protons from the interference between the bare and the rescattered amplitudes. After model tuning, various physical quantities are determined that are related to the pomeron cross section, proton-pomeron and meson-pomeron form factors, pomeron trajectory and intercept, and coefficients of diffractive eigenstates of the proton.

关键词： Particle interactions Hadrons Hadron colliders

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pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy

arXiv

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arXiv 2024年

作者： Iyer, Kartheik G. Yunus, Mikaeel O’Neill, Charles Ye, Christine Hyk, Alina McCormick, Kiera Ciucă, Ioana Wu, John F. Accomazzi, Alberto Astarita, Simone Chakrabarty, Rishabh Cranney, Jesse Field, Anjalie Ghosal, Tirthankar Ginolfi, Michele Huertas-Company, Marc Jablońska, Maja Kruk, Sandor Liu, Huiling Marchidan, Gabriel Mistry, Rohit Naiman, J.P. Peek, J.E.G. Polimera, Mugdha Rodríguez Méndez, Sergio J. Schawinski, Kevin Sharma, Sanjib Smith, Michael J. Ting, Yuan-Sen Walmsley, Mike Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Department of Physics and Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States School of Computing TheAustralian National University 108 North Rd ActonACT2601 Australia Stanford University 450 Jane Stanford Way StanfordCA94305 United States School of Electrical Engineering and Computer Science Oregon State University 1500 SW Jefferson Way CorvallisOR97331 United States Department of Engineering Loyola University Maryland 4501 North Charles Street BaltimoreMD21210 United States Research School of Astronomy & Astrophysics Australian National University Cotter Rd. WestonACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Camino Bajo del Castillo s/n Villanueva de la Cañada Madrid28692 Spain Paris France Astralis-AITC - Stromlo RSAA Australian National University Cotter Road WestonACT2600 Australia Department of Computer Science Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Dipartimento di Fisica e Astronomia Universita di Firenze Via G. Sansone 1 Sesto Fiorentino Firenze50019 Italy INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 FirenzeI-50125 Italy Instituto de Astrofisica de Canarias C. Via Lactea 1 Tenerife La LagunaE-38205 Spain Universidad de la Laguna dept. Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Cite LERMA - Observatoire de Paris PSL Paris France SCIPP University of

The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with key-words. Utilizing state-of-the-art large language models (LLMs) and a corpus of 350,000 peer-reviewed papers from the Astrophysics Data System (ADS), pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use key-words or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool’s versatility through case studies, showcasing its application in various research scenarios. The system’s performance is evaluated using custom benchmarks, including single-paper and multi-paper tasks. Beyond literature review, pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g. in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying AI to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature. © 2024, CC BY.

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BenthicNet: A global compilation of seafloor images for deep learning applications

arXiv

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arXiv 2024年

作者： Lowe, Scott C. Misiuk, Benjamin Xu, Isaac Abdulazizov, Shakhboz Baroi, Amit R. Bastos, Alex C. Best, Merlin Ferrini, Vicki Friedman, Ariell Hart, Deborah Hoegh-Guldberg, Ove Ierodiaconou, Daniel Mackin-McLaughlin, Julia Markey, Kathryn Menandro, Pedro S. Monk, Jacquomo Nemani, Shreya O’Brien, John Oh, Elizabeth Reshitnyk, Luba Y. Robert, Katleen Roelfsema, Chris M. Sameoto, Jessica A. Schimel, Alexandre C.G. Thomson, Jordan A. Wilson, Brittany R. Wong, Melisa C. Brown, Craig J. Trappenberg, Thomas Vector Institute TorontoON Canada Memorial University of Newfoundland Department of Geography St. John’sNL Canada Memorial University of Newfoundland Department of Earth Sciences St. John’sNL Canada Dalhousie University Faculty of Computer Science HalifaxNS Canada Dalhousie University School for Resource and Environmental Studies HalifaxNS Canada Dalhousie University DeepSense HalifaxNS Canada Universidade Federal do Espírito Santo Departamento de Oceanografia e Ecologia Vitória Brazil Fisheries and Oceans Canada Marine Spatial Ecology and Analysis Section Institute of Ocean Sciences SidneyBC Canada Columbia University Lamont-Doherty Earth Observatory PalisadesNY United States University of Sydney Australian Centre for Field Robotics SydneyNSW Australia Greybits Engineering SydneyNSW Australia National Oceanic and Atmospheric Administration Northeast Fisheries Science Center Woods HoleMA United States University of Queensland School of the Environment BrisbaneQLD Australia Deakin University School of Life and Environmental Sciences WarrnamboolVIC Australia Oxy Occidental College Vantuna Research Group Los AngelesCA United States University of Tasmania Institute for Marine and Antarctic Studies HobartTAS Australia Fisheries and Marine Institute of Memorial University of Newfoundland School of Ocean Technology St. John’sNL Canada Fisheries and Oceans Canada Bedford Institute of Oceanography DartmouthNS Canada Hakai Institute Heriot Bay BC Canada Trondheim Norway Ecology Action Centre HalifaxNS Canada Dalhousie University Department of Oceanography HalifaxNS Canada

Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery has outpaced our capacity to analyze it, hindering mobilization of this crucial environmental information. Machine learning approaches provide opportunities to increase the efficiency with which seafloor imagery is analyzed, yet large and consistent datasets to support development of such approaches are scarce. Here we present BenthicNet: a global compilation of seafloor imagery designed to support the training and evaluation of large-scale image recognition models. An initial set of over 11.4 million images was collected and curated to represent a diversity of seafloor environments using a representative subset of 1.3 million images. These are accompanied by 3.1 million annotations translated to the CATAMI scheme, which span 190 000 of the images. A large deep learning model was trained on this compilation and preliminary results suggest it has utility for automating large and small-scale image analysis tasks. The compilation and model are made openly available for reuse at doi:10.20383/103.0614. © 2024, CC BY.

关键词： Underwater imaging

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A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers

arXiv

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arXiv 2025年

作者： Wang, Meng Lin, Tian Hou, Qingshan Lin, Aidi Wang, Jingcheng Peng, Qingsheng Nguyen, Truong X. Fang, Danqi Zou, Ke Xu, Ting Xue, Cancan Quek, Ten Cheer Yu, Qinkai Liu, Minxin Zhou, Hui Xiao, Zixuan He, Guiqin Liang, Huiyu Shi, Tingkun Chen, Man Liu, Linna Peng, Yuanyuan Wang, Lianyu Hu, Qiuming Chen, Junhong Zhang, Zhenhua Chen, Cheng Zhao, Yitian Liu, Dianbo Wu, Jianhua Chen, Xinjian Zhang, Changqing Nguyen, Triet Thanh Meng, Yanda Zheng, Yalin Tham, Yih Chung Cheung, Carol Y. Fu, Huazhu Chen, Haoyu Cheng, Ching-Yu Centre for Innovation and Precision Eye Health Yong Loo Lin School of Medicine National University of Singapore Singapore119228 Singapore Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore119228 Singapore Joint Shantou International Eye Center Shantou University The Chinese University of Hong Kong Guangdong Shantou515041 China Shantou University Medical College Guangdong Shantou515041 China School of Computer Science and Engineering Northeastern University Liaoning Shenyang110819 China Big Vision Medical Technology Ltd. Suzhou215011 China Singapore Eye Research Institute Singapore National Eye Centre Singapore169856 Singapore Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong 999077 Hong Kong Binh Dinh Eye Hospital Viet Nam Department of Computer Science University of Exeter ExeterEX4 4RN United Kingdom University of Science and Technology Hospital Guangdong Shenzhen518000 China Shenzhen Qianhai Shekou Free Trade Zone Hospital Guangdong Shenzhen518000 China Department of Ophthalmology Meizhou People’s Hospital Meizhou Academy of Medical Sciences Guangdong Meizhou514000 China Department of Ophthalmology Yeungnam University College of Medicine Daegu42417 Korea Republic of Aier Eye Hospital of Wuhan University Hubei Wuhan430000 China School of Biomedical Engineering Anhui Medical University Anhui Hefei230032 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211100 China Guangxi Jingliang Eye Hospital Guangxi Nanning530021 China Puning People’s Hospital Guangdong Jieyang522000 China Shandong Qingdao266042 China Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Ningbo315201 China School of Electronics and Information Engineering Soochow University

Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, but current models typically require retraining when deployed across different clinical centers, limiting their widespread adoption. We introduce GlobeReady, a clinician-friendly AI platform that enables ocular disease diagnosis without retraining/fine-tuning or technical expertise. GlobeReady achieves high accuracy across imaging modalities: 93.9–98.5% for an 11-category fundus photo dataset and 87.2–92.7% for a 15-category OCT dataset. Through training-free local feature augmentation, it addresses domain shifts across centers and populations, reaching an average accuracy of 88.9% across five centers in China, 86.3% in Vietnam, and 90.2% in the UK. The built-in confidence-quantifiable diagnostic approach further boosted accuracy to 94.9–99.4% (fundus) and 88.2–96.2% (OCT), while identifying out-of-distribution cases at 86.3% (49 CFP categories) and 90.6% (13 OCT categories). Clinicians from multiple countries rated GlobeReady highly (average 4.6 out of 5) for its usability and clinical relevance. These results demonstrate GlobeReady’s robust, scalable diagnostic capability and potential to support ophthalmic care without technical barriers. © 2025, CC0.

关键词： Ophthalmology

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The Transdiagnostic Connectome Project: an open dataset for studying brain-behavior relationships in psychiatry

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Scientific data 2025年第1期12卷 923页

作者： Sidhant Chopra Carrisa V Cocuzza Connor Lawhead Jocelyn A Ricard Loïc Labache Lauren M Patrick Poornima Kumar Arielle Rubenstein Julia Moses Lia Chen Crystal Blankenbaker Bryce Gillis Laura T Germine Ilan Harpaz-Rotem B T Thomas Yeo Justin T Baker Avram J Holmes Department of Psychology Yale University New Haven CT USA. Department of Psychiatry Brain Health Institute Rutgers University Piscataway NJ USA. Orygen Parkville Melbourne Australia. Center for Youth Mental Health University of Melbourne Melbourne Australia. Department of Psychology Stony Brook University Stony Brook NY USA. Stanford Neurosciences Interdepartmental Program Stanford University School of Medicine Stanford CA USA. Department of Psychology University of Pennsylvania Philadelphia PA USA. Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Psychiatry Harvard Medical School Boston USA. Centre for Depression Anxiety and Stress Research McLean Hospital Boston USA. Department of Psychology Cornell University Ithaca NY USA. Institute for Technology in Psychiatry McLean Hospital Boston USA. Department of Psychiatry Yale University New Haven USA. Wu Tsai Institute Yale University New Haven USA. Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore. Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore. N.1 Institute for Health National University of Singapore Singapore Singapore. Department of Medicine Healthy Longevity Translational Research Programme Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM) Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore. Integrative Sciences and Engineering Programme (ISEP) National University of Singapore Singapore Singapore. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown USA. Department of Psychiatry Brain Health Institute Rutgers University Piscataway NJ USA. avram.holmes@rutgers.edu.

An important aim in psychiatry is to establish valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset to accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.

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Revealing the Dynamic Magneto-ionic Environments of Repeating Fast Radio Burst Sources through Multi-year Polarimetric Monitoring with CHIME/FRB

arXiv

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arXiv 2023年

作者： McKinven, R. Gaensler, B.M. Michilli, D. Masui, K. Kaspi, V.M. Su, J. Bhardwaj, M. Cassanelli, T. Chawla, P. Dong, F. Fonseca, E. Leung, C. Li, D.Z. Ng, C. Patel, C. Pearlman, A.B. Petroff, E. Pleunis, Z. Rafiei-Ravandi, M. Rahman, M. Sand, K.R. Shin, K. Stairs, I.H. Tendulkar, S. Department of Physics McGill University 3600 rue University MontréalQCH3A 2T8 Canada McGill Space Institute McGill University 3550 rue University MontréalQCH3A 2A7 Canada Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States MIT Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Dept. of Physics and Astronomy 6224 Agricultural Road VancouverBCV6T 1Z1 Canada Lane Department of Computer Science and Electrical Engineering 1220 Evansdale Drive PO Box 6109 MorgantownWV26506 United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States Department of Physics and Astronomy West Virginia University P.O. Box 6315 MorgantownWV26506 United States Cahill Center for Astronomy and Astrophysics California Institute of Technology 1216 E California Boulevard PasadenaCA91125 United States Sidrat Research PO Box 73527 RPO Wychwood TorontoONM6C 4A7 Canada Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India National Centre for Radio Astrophysics Post Bag 3 Ganeshkhind Pune411007 India

Fast radio bursts (FRBs) display a confounding variety of burst properties and host galaxy associations. Repeating FRBs offer insight into the FRB population by enabling spectral, temporal and polarimetric properties to be tracked over time. Here, we report on the polarized observations of 12 repeating sources using multi-year monitoring with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) over 400-800 MHz. We observe significant RM variations from many sources in our sample, including RM changes of several hundred rad m−2 over month timescales from FRBs 20181119A, 20190303A and 20190417A, and more modest RM variability (∆RM . few tens rad m−2) from FRBs 20181030A, 20190208A, 20190213B and 20190117A over equivalent timescales. Several repeaters display a frequency dependent degree of linear polarization that is consistent with depolarization via scattering. Combining our measurements of RM variations with equivalent constraints on DM variability, we estimate the average line-of-sight magnetic field strength in the local environment of each repeater. In general, repeating FRBs display RM variations that are more prevalent/extreme than those seen from radio pulsars in the Milky Way and the Magellanic Clouds, suggesting repeating FRBs and pulsars occupy distinct magneto-ionic environments. © 2023, CC BY.

关键词： Polarimeters

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Ray-Based Characterization of the AMPLE Model from 0.85 to 5 GHz

arXiv

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arXiv 2025年

作者： Zhou, Lingyou Dong, Xin Qiu, Kehai Yu, Gang Zhang, Jie Zhang, Jiliang School of Electrical and Electronic Engineering The University of Sheffield SheffieldS10 2TN United Kingdom Ranplan Wireless Network Design Ltd. CambridgeCB23 3UY United Kingdom Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom College of Engineering Design and Physical Sciences Brunel University of London UxbridgeUB8 3PH United Kingdom 5G/6G Innovation Centre University of Surrey SurreyGU2 7XH United Kingdom State Key Laboratory of Synthetical Automation for Process Industries The College of Information Science and Engineering Northeastern University Shenyang110819 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China

In this paper, we characterize the adaptive multiple path loss exponent (AMPLE) radio propagation model under urban macrocell (UMa) and urban microcell (UMi) scenarios from 0.85-5 GHz using Ranplan Professional. We first enhance the original AMPLE model by introducing an additional frequency coefficient to support path loss prediction across multiple carrier frequencies. By using measurement-validated Ranplan Professional simulator, we simulate four cities and validate the simulations for further path loss model characterization. Specifically, we extract the close-in (CI) model parameters from the simulations and compare them with parameters extracted from measurements in other works. Under the ray-based model characterization, we compare the AMPLE model with the 3rd Generation Partnership Project (3GPP) path loss model, the CI model, the alpha-beta-gamma (ABG) model, and those with simulation calibrations. In addition to standard performance metrics, we introduce the prediction-measurement difference error (PMDE) to assess overall prediction alignment with measurement, and mean simulation time per data point to evaluate model complexity. The results show that the AMPLE model outperforms existing models while maintaining similar model complexity. Copyright © 2025, The Authors. All rights reserved.

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