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First polarisation measurement of coherently photoproduced J/ψ in ultra-peripheral Pb–Pb collisions at s_NN=5.02 TeV

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2025年 865卷

作者： Acharya, S. Adamová, D. Adler, A. Aglieri Rinella, G. Agnello, M. Agrawal, N. Ahammed, Z. Ahmad, S. Ahn, S.U. Ahuja, I. Akindinov, A. Al-Turany, M. Aleksandrov, D. Alessandro, B. Alfanda, H.M. Alfaro Molina, R. Ali, B. Alici, A. Alizadehvandchali, N. Alkin, A. Alme, J. Alocco, G. Alt, T. Altsybeev, I. Alvarado, J.R. Anaam, M.N. Andrei, C. Andronic, A. Anguelov, V. Antinori, F. Antonioli, P. Apadula, N. Aphecetche, L. Appelshäuser, H. Arata, C. Arcelli, S. Aresti, M. Arnaldi, R. Arneiro, J.G.M.C.A. Arsene, I.C. Arslandok, M. Augustinus, A. Averbeck, R. Azmi, M.D. Badalà, A. Bae, J. Baek, Y.W. Bai, X. Bailhache, R. Bailung, Y. Balbino, A. Baldisseri, A. Balis, B. Banerjee, D. Banoo, Z. Barbera, R. Barile, F. Barioglio, L. Barlou, M. Barnaföldi, G.G. Barnby, L.S. Barret, V. Barreto, L. Bartels, C. Barth, K. Bartsch, E. Bastid, N. Basu, S. Batigne, G. Battistini, D. Batyunya, B. Bauri, D. Bazo Alba, J.L. Bearden, I.G. Beattie, C. Becht, P. Behera, D. Belikov, I. Bell Hechavarria, A.D.C. Bellini, F. Bellwied, R. Belokurova, S. Belyaev, V. Bencedi, G. Beole, S. Bercuci, A. Berdnikov, Y. Berdnikova, A. Bergmann, L. Besoiu, M.G. Betev, L. Bhaduri, P.P. Bhasin, A. Bhat, M.A. Bhattacharjee, B. Bianchi, L. Bianchi, N. Bielčík, J. Bielčíková, J. Biernat, J. Bigot, A.P. Bilandzic, A. Biro, G. Biswas, S. Bize, N. Blair, J.T. Blau, D. Blidaru, M.B. Bluhme, N. Blume, C. Boca, G. Bock, F. Bodova, T. Bogdanov, A. Boi, S. Bok, J. Boldizsár, L. Bombara, M. Bond, P.M. Bonomi, G. Borel, H. Borissov, A. Borquez Carcamo, A.G. Bossi, H. Botta, E. Bouziani, Y.E.M. Bratrud, L. Braun-Munzinger, P. Bregant, M. Broz, M. Bruno, G.E. Buckland, M.D. Budnikov, D. Buesching, H. Bufalino, S. Buhler, P. Buthelezi, Z. Bylinkin, A. Bysiak, S.A. Cai, M. Caines, H. Caliva, A. Calvo Villar, E. Camacho, J.M.M. Camerini, P. Canedo, F.D.M. Cantway, S.L. Carabas, M. Carballo, A.A. Carnesecchi, F. Caron, R. Carvalho, L.A.D. Castillo Castellanos, J. Catalano, F. Ceballos Sanchez, C. Chakaberia, I. Chakraborty, P. Chandra, S. Chapeland, S. Chartier, M. Chattopa A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation Yerevan Armenia AGH University of Krakow Cracow Poland Bogolyubov Institute for Theoretical Physics National Academy of Sciences of Ukraine Kiev Ukraine Bose Institute Department of Physics Centre for Astroparticle Physics and Space Science (CAPSS) Kolkata India California Polytechnic State University San Luis Obispo CA United States Central China Normal University Wuhan China Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN) Havana Cuba Centro de Investigación y de Estudios Avanzados (CINVESTAV) Mexico City and Mérida Mexico Chicago State University Chicago IL United States China Institute of Atomic Energy Beijing China Chungbuk National University Cheongju South Korea Comenius University Bratislava Faculty of Mathematics Physics and Informatics Bratislava Slovakia COMSATS University Islamabad Islamabad Pakistan Creighton University Omaha NE United States Department of Physics Aligarh Muslim University Aligarh India Department of Physics Pusan National University Pusan South Korea Department of Physics Sejong University Seoul South Korea Department of Physics University of California Berkeley CA United States Department of Physics University of Oslo Oslo Norway Department of Physics and Technology University of Bergen Bergen Norway Dipartimento di Fisica Università di Pavia Pavia Italy Dipartimento di Fisica dell'Università Sezione INFN Cagliari Italy Dipartimento di Fisica dell'Università Sezione INFN Trieste Italy Dipartimento di Fisica dell'Università Sezione INFN Turin Italy Dipartimento di Fisica e Astronomia dell'Università Sezione INFN Bologna Italy Dipartimento di Fisica e Astronomia dell'Università Sezione INFN Catania Italy Dipartimento di Fisica e Astronomia dell'Università Sezione INFN Padova Italy Dipartimento di Fisica ‘E.R. Caianiello’ dell'Università Gruppo Collegato INFN Salerno Italy Dipartimento DISAT del Politecnico

The first measurement of the polarisation of coherently photoproduced J/ψ mesons in ultra-peripheral Pb–Pb collisions, using data at sNN=5.02 TeV, is presented. The J/ψ meson is measured via its dimuon decay channe...

The first measurement of the polarisation of coherently photoproduced J/ψ mesons in ultra-peripheral Pb–Pb collisions, using data at s_NN=5.02 TeV, is presented. The J/ψ meson is measured via its dimuon decay channel in the forward rapidity interval −4.0−1 ± 5% (syst) is analysed. Hadronic activity is highly suppressed since the interaction is mediated by a photon. The polar and azimuthal angle distributions of the decay muons are measured, and the polarisation parameters λ_θ, λ_φ, λ_θφ are extracted. The analysis is carried out in the helicity frame. The results are found to be consistent with a transversely polarised J/ψ. These values are compared with previous measurements by the H1 and ZEUS experiments. The polarisation parameters of coherent J/ψ photoproduction in Pb–Pb collisions are found to be consistent with the s-channel helicity conservation hypothesis. © 2025 CERN for the benefit of the ALICE Collaboration

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Lamé Parameter Estimation from Static Displacement Field Measurements in the Framework of Nonlinear Inverse Problems

arXiv

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arXiv 2017年

作者： Hubmer, Simon Sherina, Ekaterina Neubauer, Andreas Scherzer, Otmar Johannes Kepler University Linz Doctoral Program Computational Mathematics Altenbergerstraße 69 LinzA-4040 Austria Technical University of Denmark Department of Applied Mathematics and Computer Science Asmussens Allé Kongens Lyngby 2800 Denmark Johannes Kepler University Linz Industrial Mathematics Institute Altenbergerstraße 69 LinzA-4040 Austria University of Vienna Computational Science Center Oskar Morgenstern-Platz 1 Vienna1090 Austria Johann Radon Institute Linz Altenbergerstraße 69 LinzA-4040 Austria

We consider a problem of quantitative static elastography, the estimation of the Lamé parameters from internal displacement field data. This problem is formulated as a nonlinear operator equation. To solve this equation, we investigate the Landweber iteration both analytically and numerically. The main result of this paper is the verification of a nonlinearity condition in an infinite dimensional Hilbert space context. This condition guarantees convergence of iterative regularization methods. Furthermore, numerical examples for recovery of the Lamé parameters from displacement data simulating a static elastography experiment are *** Codes 65J22, 65J15, 74G75 Copyright © 2017, The Authors. All rights reserved.

关键词： Inverse problems

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Deep Potential: A general representation of a many-body potential energy surface

arXiv

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arXiv 2017年

作者： Han, Jiequn Zhang, Linfeng Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Mathematics Princeton University PrincetonNJ08544 United States Center for Data Science Beijing International Center for Mathematical Research Peking University Beijing Institute of Big Data Research Beijing100871 China

We present a simple, yet general, end-to-end deep neural network representation of the potential energy surface for atomic and molecular systems. This methodology, which we call Deep Potential, is "first-principle" based, in the sense that no ad hoc approximations or empirical fitting functions are required. The neural network structure naturally respects the underlying symmetries of the systems. When tested on a wide variety of examples, Deep Potential is able to reproduce the original model, either empirical or quantum mechanics based, within chemical accuracy. The computational cost of this new model is not substantially larger than that of empirical force fields. In addition, the method has promising scalability properties. This brings us one step closer to being able to carry out molecular simulations with accuracy comparable to that of quantum mechanics models and computational cost comparable to that of empirical potentials. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Performance of the joint LST-1 and MAGIC observations evaluated with Crab Nebula data

arXiv

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arXiv 2023年

作者： Abe, H. Abe, K. Abe, S. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Crespo, N. Alvarez Aniello, T. Ansoldi, S. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baack, D. Babić, A. Baktash, A. Bamba, A. Larriva, A. Baquero Baroncelli, L. de Almeida, U. Barres Barrio, J.A. Batković, I. Baxter, J. González, J. Becerra Bednarek, W. Bernardini, E. Bernardos, M.I. Medrano, J. Bernete Berti, A. Besenrieder, J. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Biland, A. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bošnjak, Ž. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Busetto, G. Ordaz, A. Campoy Cardillo, M. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.S. Carretero-Castrillo, M. Cassol, F. Castro-Tirado, A.J. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cornelia, A. Cortina, J. Costantini, H. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. DelPopolo, A. Deleglise, G. Delfino, M. Mendez, C. Delgado Mengual, J. Delgado Volpe, D. della Dellaiera, M. Depaoli, D. De Angelis, A. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Dominik, R.M. Prester, D. Dominis Donini, A. Dorner, D. Doro, M. Díaz, C. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Ramazani, V. Fallah Fariña, L. Fattorini, A. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Font, L. Coromina, L. Freixas Fröse, S. Fukami, S. Fukazawa, Y. López, R.J. Garcia Garcia, E. Garczarczyk, M. López, R.J. García Gasbarra, C. Gasparrini, D. Gasparyan, S. Gaug, M. Geyer, D. Paiva, J.G. Giesbrecht Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Llorente, J. Herrera Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Tenerife La Laguna Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Grupo de Electronica Universidad Complutense de Madrid Av. Complutense s/n Madrid28040 Spain RomeI-00136 Italy INFN Sezione di Trieste Università degli studi di Udine via delle scienze 206 Udine33100 Italy Rome Italy INAF - Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone00040 Italy INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Università di Padova INFN PadovaI-35131 Italy The Barcelona Institute of Science and Technology Campus UAB Bellaterra08193 Spain Univ. Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules - IN2P3 Annecy74000 France Department of Physics TU Dortmund University Otto-Hahn-Str. 4 Dortmund44227 Germany Zagreb10000 Croatia Universität Hamburg Institut für Experimentalphysik Luruper Chaussee 149 Hamburg22761 Germany Graduate School of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Faculty of Science and Technology Universidad del Azuay Cuenca Ecuador INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Centro Brasileiro de Pesquisas Físicas Rua Xavier Sigaud 150 RJ Rio de Janeiro22290-180 Brazil INFN Sezione di Padova

Aims. LST-1, the prototype of the Large-Sized Telescope for the upcoming Cherenkov Telescope Array Observatory, is concluding its commissioning in Observatorio del Roque de los Muchachos on the island of La Palma. The proximity of LST-1 (Large-Sized Telescope 1) to the two MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes permits observations of the same gamma-ray events with both systems. Methods. We describe the joint LST-1+MAGIC analysis pipeline and use simultaneous Crab Nebula observations and Monte Carlo simulations to assess the performance of the three-telescope system. The addition of the LST-1 telescope allows the recovery of events in which one of the MAGIC images is too dim to survive analysis quality cuts. Results. Thanks to the resulting increase in the collection area and stronger background rejection, we find a significant improvement in sensitivity, allowing the detection of 30% weaker fluxes in the energy range between 200 GeV and 3 TeV. The spectrum of the Crab Nebula, reconstructed in the energy range ∼60 GeV to ∼10 TeV, is in agreement with previous measurements. Copyright © 2023, The Authors. All rights reserved.

关键词： Telescopes

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Overview of KAGRA : Data transfer and management

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Progress of Theoretical and Experimental Physics 2023年第10期2023卷

作者： Akutsu, T Ando, M Arai, K Arai, Y Araki, S Araya, A Aritomi, N Asada, H Aso, Y Bae, S Bae, Y Baiotti, L Bajpai, R Barton, M A Cannon, K Cao, Z Capocasa, E Chan, M Chen, C Chen, K Chen, Y Chiang, C-Y Chu, H Chu, Y-K Eguchi, S Enomoto, Y Flaminio, R Fujii, Y Fujikawa, Y Fukunaga, M Fukushima, M Gao, D Ge, G Ha, S Hagiwara, A Haino, S Han, W-B Hasegawa, K Hattori, K Hayakawa, H Hayama, K Himemoto, Y Hiranuma, Y Hirata, N Hirose, E Hong, Z Hsieh, B Huang, G-Z Huang, H-Y Huang, P Huang, Y-C Huang, Y Hui, D C Y Ide, S Ikenoue, B Imam, S Inayoshi, K Inoue, Y Ioka, K Ito, K Itoh, Y Izumi, K Jeon, C Jin, H-B Jung, K Jung, P Kaihotsu, K Kajita, T Kakizaki, M Kamiizumi, M Kanda, N Kang, G Kawaguchi, K Kawai, N Kawasaki, T Kim, C Kim, J Kim, J C Kim, W S Kim, Y-M Kimura, N Kita, N Kitazawa, H Kobayashi, Y Kojima, Y Kokeyama, K Komori, K Kong, A K H Kotake, K Kozakai, C Kozu, R Kumar, R Kume, J Kuo, C Kuo, H-S Kuromiya, Y Kuroyanagi, S Kusayanagi, K Kwak, K Lee, H K Lee, H W Lee, R Leonardi, M Li, K L Lin, L C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H L Liu, G C Luo, L-W Majorana, E Marchio, M Michimura, Y Mio, N Miyakawa, O Miyamoto, A Miyazaki, Y Miyo, K Miyoki, S Mori, Y Morisaki, S Moriwaki, Y Nagano, K Nagano, S Nakamura, K Nakano, H Nakano, M Nakashima, R Nakayama, Y Narikawa, T Naticchioni, L Negishi, R Quynh, L Nguyen Ni, W-T Nishizawa, A Nozaki, S Obuchi, Y Ogaki, W Oh, J J Oh, K Oh, S H Ohashi, M Ohashi, T Ohishi, N Ohkawa, M Ohta, H Okutani, Y Okutomi, K Oohara, K Ooi, C Oshino, S Otabe, S Pan, K Pang, H Parisi, A Park, J Arellano, F E Peña Pinto, I Sago, N Saito, S Saito, Y Sakai, K Sakai, Y Sakuno, Y Sasaki, Y Sato, S Sato, T Sawada, T Sekiguchi, T Sekiguchi, Y Shao, L Shibagaki, S Shimizu, R Shimoda, T Shimode, K Shinkai, H Shishido, T Shoda, A Somiya, K Son, E J Sotani, H Sugimoto, R Suresh, J Suzuki, T Tagoshi, H Takahashi, H Takahashi, R Takamori, A Takano, S Takeda, H Takeda, M Tanaka, H Tanaka, K Tanaka, T Tanioka, S Martin, E N Tapia San Telada, S Tomaru, T Tomigami, Y Tomura, T Travasso, F Trozzo, L Tsang, T Ts Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research (ICRR) KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Hirosaki University 3 Bunkyo-cho Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) 245 Daehak-ro Yuseong-gu Daejeon 34141 Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University No. 19 Xinjiekou Street Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy Nation

KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu prefecture, Japan. In this article, we describe the KAGRA data management system, i.e., recording of data, transfer from the KAGRA experiment site to computing resources, as well as data distribution to tier sites, including international sites in Taiwan and Korea. The amount of KAGRA data exceeded 1.0 PiB and increased by about 1.5 TB per day during operation in 2020. Our system has succeeded in data management, and has achieved performance that can withstand observations after 2023, that is, a transfer rate of 20 MB s-1or more and file storage of sufficient capacity for petabyte class. We also discuss the sharing of data between the global gravitational-wave detector network with other experiments, namely LIGO and Virgo. The latency, which consists of calculation of calibrated strain data and transfer time within the global network, is very important from the view of multi-messenger astronomy using gravitational waves. Real-time calbrated data delivered from the KAGRA detector site and other detectors to our computing system arrive with about 4–15 seconds of latency. These latencies are sufficiently short compared to the time taken for gravitational wave event search computations. We also established a high-latency exchange of offline calibrated data that was aggregated with a better accuracy compared with real-time data.

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STATE OF THE CLIMATE IN 2021

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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2022年第8期103卷 S1-S1页

作者： Blunden, Jessica NOAA/NESDIS National Centers for Environmental Information Asheville NC United States NOAA NESDIS National Centers for Environmental Information Silver Spring MD United States Met Office Hadley Centre Exeter United Kingdom Cooperative Institute for Satellite Earth System Studies North Carolina State University Asheville NC United States Communications and Outreach NOAA/NESDIS National Centers for Environmental Information Asheville NC United States Innovative Consulting and Management Services LLC NOAA/NESDIS National Centers for Environmental Information Asheville NC United States European Centre for Medium-Range Weather Forecasts Reading United Kingdom CMNS-Earth System Science Interdisciplinary Center University of Maryland College Park MD United States Department of Meteorology National Centre for Earth Observation University of Reading Reading United Kingdom Department of Atmospheric and Planetary Science Hampton University Hampton VA United States National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Life and Environmental Sciences Osaka Prefecture University Osaka Sakai Japan University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder CO United States Centro de Investigaciones sobre Desertificación Spanish National Research Council (CIDE CSIC-UV-Generalitat Valenciana) Climate Atmosphere and Ocean Laboratory (Climatoc-Lab) Moncada Valencia Spain Instituto de Geografía Pontificia Universidad Católica de Valparaíso Valparaíso Chile Climatic Research Unit School of Environmental Sciences University of East Anglia Norwich United Kingdom Joint Research Centre of the European Commission Ispra Italy GloH2O Almere Netherlands University of Reading Reading United Kingdom School of Engineering Newcastle University Newcastle-upon-Tyne United Kingdom Université de Paris Cité Institut de physique du globe de Paris CNRS IGN Paris

Editors note: For easy download the posted pdf of the State of the Climate in 2021 is a low-resolution file. A high-resolution copy of the report is available by clickinghere. Please be patient as it may take a few mi... 详细信息

关键词： Greenhouse gases

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Spectral bounds for independent cascade model with sensitive edges

Spectral bounds for independent cascade model with sensitive...

引用

Annual Conference on Information Sciences and Systems (CISS)

作者： Eun Jee Lee Sudeep Kamath Emmanuel Abbe Sanjeev R. Kulkarni Program in Applied and Computational Mathematics Department of Electrical Engineering Princeton University

This paper studies independent cascade models where influence propagates from seed-nodes along edges with independent probabilities. Upper-bounds for the expected number of influenced nodes were previously proposed using the spectral norm of a Hazard matrix. However, these bounds turn out loose in many cases, in particular with respect to sensitive edges such as bottlenecks, seed adjacent, and high probability edges. This paper proposes a similar bound that improves in such cases by handling sensitives edges more carefully.

关键词： Hazards Upper bound Stochastic processes Information science Merging Computational modeling Mathematical model

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A fluctuating boundary integral method for brownian suspensions

arXiv

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arXiv 2017年

作者： Bao, Yuanxun Rachh, Manas Keaveny, Eric E. Greengard, Leslie Donev, Aleksandar Courant Institute of Mathematical Sciences New York University 251 Mercer Street New YorkNY United States Applied Mathematics Program Yale University New HavenCT06511 United States Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom Center for Computational Biology Flatiron Institute New YorkNY United States

We present a fluctuating boundary integral method (FBIM) for overdamped Brownian Dynamics (BD) of two-dimensional periodic suspensions of rigid particles of complex shape immersed in a Stokes fluid. We develop a novel approach for generating Brownian displacements that arise in response to the thermal fluctuations in the fluid. Our approach relies on a first-kind boundary integral formulation of a mobility problem in which a random surface velocity is prescribed on the particle surface, with zero mean and covariance proportional to the Green’s function for Stokes flow (Stokeslet). This approach yields an algorithm that scales linearly in the number of particles for both deterministic and stochastic dynamics, handles particles of complex shape, achieves high order of accuracy, and can be generalized to three dimensions and other boundary conditions. We show that Brownian displacements generated by our method obey the discrete fluctuation-dissipation balance relation (DFDB). Based on a recently-developed Positively Split Ewald method [A. M. Fiore, F. Balboa Usabiaga, A. Donev and J. W. Swan, J. Chem. Phys., 146, 124116, 2017], near-field contributions to the Brownian displacements are efficiently approximated by iterative methods in real space, while far-field contributions are rapidly generated by fast Fourier-space methods based on fluctuating hydrodynamics. FBIM provides the key ingredient for time integration of the overdamped Langevin equations for Brownian suspensions of rigid particles. We demonstrate that FBIM obeys DFDB by performing equilibrium BD simulations of suspensions of starfish-shaped bodies using a random finite difference temporal integrator. Copyright © 2017, The Authors. All rights reserved.

关键词： Boundary integral equations

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Community detection and stochastic block models: recent developments

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2017年第1期18卷

作者： Emmanuel Abbe Program in Applied and Computational Mathematics and Department of Electrical Engineering Princeton University Princeton NJ

The stochastic block model (SBM) is a random graph model with planted clusters. It is widely employed as a canonical model to study clustering and community detection, and provides generally a fertile ground to study the statistical and computational tradeoffs that arise in network and data *** note surveys the recent developments that establish the fundamental limits for community detection in the SBM, both with respect to information-theoretic and computational thresholds, and for various recovery requirements such as exact, partial and weak recovery (a.k.a., detection). The main results discussed are the phase transitions for exact recovery at the Chernoff-Hellinger threshold, the phase transition for weak recovery at the Kesten-Stigum threshold, the optimal distortion-SNR tradeoff for partial recovery, the learning of the SBM parameters and the gap between information-theoretic and computational *** note also covers some of the algorithms developed in the quest of achieving the limits, in particular two-round algorithms via graph-splitting, semi-definite programming, linearized belief propagation, classical and nonbacktracking spectral methods. A few open problems are also discussed.

关键词： clustering community detection computational gaps network data analysis random graphs spectral algorithms stochastic block models unsupervised learning

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Author Correction: The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

npj biodiversity

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npj biodiversity 2024年第1期3卷 31页

作者： Ann M Mc Cartney Giulio Formenti Alice Mouton Diego De Panis Luísa S Marins Henrique G Leitão Genevieve Diedericks Joseph Kirangwa Marco Morselli Judit Salces-Ortiz Nuria Escudero Alessio Iannucci Chiara Natali Hannes Svardal Rosa Fernández Tim De Pooter Geert Joris Mojca Strazisar Jonathan M D Wood Katie E Herron Ole Seehausen Phillip C Watts Felix Shaw Robert P Davey Alice Minotto José M Fernández Astrid Böhne Carla Alegria Tyler Alioto Paulo C Alves Isabel R Amorim Jean-Marc Aury Niclas Backstrom Petr Baldrian Laima Baltrunaite Endre Barta Bertrand BedHom Caroline Belser Johannes Bergsten Laurie Bertrand Helena Bilandija Mahesh Binzer-Panchal Iliana Bista Mark Blaxter Paulo A V Borges Guilherme Borges Dias Mirte Bosse Tom Brown Rémy Bruggmann Elena Buena-Atienza Josephine Burgin Elena Buzan Alessia Cariani Nicolas Casadei Matteo Chiara Sergio Chozas Fedor Čiampor Angelica Crottini Corinne Cruaud Fernando Cruz Love Dalen Alessio De Biase Javier Del Campo Teo Delic Alice B Dennis Martijn F L Derks Maria Angela Diroma Mihajla Djan Simone Duprat Klara Eleftheriadi Philine G D Feulner Jean-François Flot Giobbe Forni Bruno Fosso Pascal Fournier Christine Fournier-Chambrillon Toni Gabaldon Shilpa Garg Carmela Gissi Luca Giupponi Jessica Gomez-Garrido Josefa González Miguel L Grilo Björn Grüning Thomas Guerin Nadege Guiglielmoni Marta Gut Marcel P Haesler Christoph Hahn Balint Halpern Peter W Harrison Julia Heintz Maris Hindrikson Jacob Höglund Kerstin Howe Graham M Hughes Benjamin Istace Mark J Cock Franc Janžekovič Zophonias O Jonsson Sagane Joye-Dind Janne J Koskimäki Boris Krystufek Justyna Kubacka Heiner Kuhl Szilvia Kusza Karine Labadie Meri Lähteenaro Henrik Lantz Anton Lavrinienko Lucas Leclère Ricardo Jorge Lopes Ole Madsen Ghislaine Magdelenat Giulia Magoga Tereza Manousaki Tapio Mappes Joao Pedro Marques Gemma I Martinez Redondo Florian Maumus Shane A McCarthy Hendrik-Jan Megens Jose Melo-Ferreira Sofia L Mendes Matteo Montagna Joao Moreno Mai-Britt Mosbech Mónica Moura Zuzana Musilova Eugene Myers Will J N Genomics Institute University of California Santa Cruz CA USA. anmmccar@ucsc.edu. The Vertebrate Genome Laboratory The Rockefeller University New York NY USA. Department of Biology University of Florence Sesto Fiorentino Italy. InBios-Conservation Genetics Laboratory University of Liege Liege Belgium. Leibniz Institut für Zoo und Wildtierforschung Berlin Germany. Berlin Center for Genomics in Biodiversity Research Berlin Germany. Department of Biology University of Antwerp Antwerp Belgium. Institute of Zoology University of Cologne Cologne Germany. Department of Chemistry Life Sciences and Environmental Sustainability University of Parma Parma Italy. Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra) Barcelona Spain. Naturalis Biodiversity Center Leiden The Netherlands. Neuromics Support Facility VIB Center for Molecular Neurology VIB Antwerp Belgium. Neuromics Support Facility Department of Biomedical Sciences University of Antwerp Antwerp Belgium. Tree of Life Wellcome Sanger Institute Hinxton Cambridge UK. School of Biology and Environmental Science University College Dublin Belfield Ireland. Aquatic Ecology & Evolution Institute of Ecology & Evolution University of Bern Bern Switzerland. Department of Fish Ecology & Evolution Eawag Kastanienbaum Switzerland. Department of Biological and Environmental Science University of Jyvaskyla Jyvaskyla Finland. The Earlham Institute Norwich Research Park Norwich UK. Digital Science London UK. Barcelona Supercomputing Center Spanish National Bioinformatics Institute ELIXIR Spain Getafe Spain. Leibniz Institute for the Analysis of Biodiversity Change Museum Koenig Bonn Bonn Germany. CE3C-Centre for Ecology Evolution and Environmental Changes & CHANGE-Global Change and Sustainability Institute Faculdade de Ciências Universidade de Lisboa Campo Grande Lisboa Portugal. Centro Nacional de Análisis Genómico (CNAG) Barcelona Spain. Universitat de Barcelona (UB) Barcelona Spain. CIBIO C

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