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Supercomputing Frontiers and Innovations 2017年第2期4卷 87-102页

作者： Noaje, Gabriel Davis, Alan Low, Jonathan Seng, Lim Lian, Tan Geok Orlowski, Lukasz P. Chien, Dominic Sing-Wu, Liou Wee, Tan Tin Poppe, Yves Kim Kenneth, Ban Hon Howard, Andrew Southwell, David Gunthorpe, Jason Michalewicz, Marek T. Singapore Institute for Advanced Computational Science Stony Brook University New York United States Department of Applied Mathematics and Statistics Stony Brook University New York United States Singapore Department of Biochemistry Yong Loo Lin School of Medicine National University of Singapore Singapore National University of Singapore Singapore The Australian National University Canberra Australia Obsidian Strategics Inc Edmonton Canada University of Warsaw Warsaw Poland

The global effort to build ever more powerful supercomputers is faced with the challenge of ramping up High Performance Computing systems to ExaScale capabilities and, at the same time, keeping the electrical power consumption for a system of that scale at less than 20 MW level. One possible solution, bypassing this local energy limit, is to use distributed supercomputers to alleviate intense power requirements at any single location. The other critical challenge faced by the global computer industry and international scientific collaborations is the requirement of streaming colossal amounts of time-critical data. Examples abound: i) transfer of astrophysical data collected by the Square Kilometre Array to the international partners, ii) streaming of large facilities experimental data through the Pacific Research Platform collaboration of DoE, ESnet and other partners in the US and elsewhere, iii) the Superficilities vision expressed by DoE, iv) new architecture for CERN LHC data processing pipeline focussing on more powerful processing facilities connected by higher throughput connectivity. The InfiniCortex project led by A*STAR computational Resource Centre demonstrates a worldwide InfiniBand fabric circumnavigating the globe and bringing together, as one concurrent globally distributer HPC system, several supercomputing facilities spanned across four continents (Asia, Australia, Europe and North America). Using global scale InfiniBand connections, with bandwidth utilisation approaching 98% link capacity, we have established a new architectural approach which might lead to the next generation supercomputing systems capable of solving the most complex problems through the aggregation and parallelisation of many globally distributed supercomputers into a single hive-mind of enormous scale. © The Authors 2016.

关键词： Supercomputers

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SciPy 1.0—Fundamental algorithms for scientific computing in python

arXiv

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arXiv 2019年

作者： Virtanen, Pauli Gommers, Ralf Oliphant, Travis E. Haberland, Matt Reddy, Tyler Cournapeau, David Burovski, Evgeni Peterson, Pearu Weckesser, Warren Bright, Jonathan van der Walt, Stéfan J. Brett, Matthew Wilson, Joshua Millman, K. Jarrod Mayorov, Nikolay Nelson, Andrew R.J. Jones, Eric Kern, Robert Larson, Eric Carey, C.J. Polat, Ilhan Feng, Yu Moore, Eric W. VanderPlas, Jake Laxalde, Denis Perktold, Josef Cimrman, Robert Henriksen, Ian Quintero, E.A. Harris, Charles R. Archibald, Anne M. Ribeiro, Antônio H. Pedregosa, Fabian van Mulbregt, Paul University of Jyväskylä University of Jyväskylä FI-40014 Finland Quansight LLC AustinTX United States Ultrasound Imaging Mayo Clinic RochesterMN55902 United States Electrical Engineering Brigham Young University ProvoUT84604 United States Enthought Inc. AustinTX78701 United States Anaconda Inc AustinTX78701 United States BioResource and Agricultural Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States Department of Mathematics University of California Los AngelesCA90025 United States Los Alamos National Laboratory Los AlamosNM87544 United States Independent Researcher Higher School of Economics Myasnitskaya 20 Moscow101000 Russia Independent Researcher Saue Estonia Department of Mechanics and Applied Mathematics Institute of Cybernetics Tallinn Technical University Akadeemia Rd 21 Tallinn Estonia Independent Researcher NY United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States School of Psychology University of Birmingham Edgbaston BirmighamB15 2TT United Kingdom Division of Biostatistics University of California BerkeleyCA94720 United States WayRay LLC Skolkovo Innovation Center Moscow143026 Russia Australian Nuclear Science and Technology Organisation Locked Bag 2001 Kirrawee DCNSW2232 Australia Institute for Learning and Brain Sciences University of Washington SeattleWA98195 United States College of Information and Computing Sciences University of Massachusetts Amherst AmherstMA01002 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Bruker Biospin Corp. 15 Fortune Drive BillericaMA01821 United States University of Washington SeattleWA98195 United States New Technologies - Research Centre University of West Bohemia Univerzitní 8 Plzeň306 14 Czech Republic Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX7

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments. Copyright © 2019, The Authors. All rights reserved.

关键词： Open source software

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Prospects for a survey of the Galactic plane with the Cherenkov Telescope Array

arXiv

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arXiv 2023年

作者： Abe, S. Abhir, J. Abhishek, A. Acero, F. Acharyya, A. Adam, R. Aguasca-Cabot, A. Agudo, I. Aguirre-Santaella, A. Alfaro, J. Alvarez-Crespo, N. Alves Batista, R. Amans, J.-P. Amato, E. Ambrosi, G. Ambrosino, F. Angüner, E.O. Aramo, C. Arcaro, C. Arrabito, L. Asano, K. Ascasíbar, Y. Aschersleben, J. Augusto Stuani, L. Backes, M. Balazs, C. Balbo, M. Ballet, J. Baquero Larriva, A. Barbosa Martins, V. Barres de Almeida, U. Barrio, J.A. Batković, I. Batzofin, R. Baxter, J. Becerra González, J. Beck, G. Beiske, L. Belmont, R. Benbow, W. Bernardini, E. Bernete, J. Bernlöhr, K. Berti, A. Bertucci, B. Beshley, V. Bhattacharjee, P. Bhattacharyya, S. Bi, B. Biederbeck, N. Biland, A. Bissaldi, E. Biteau, J. Blanch, O. Blazek, J. Bocchino, F. Boisson, C. Bolmont, J. Bonneau Arbeletche, L. Bonnoli, G. Bonollo, A. Bordas, P. Bosnjak, Z. Bottacini, E. Braiding, C. Bronzini, E. Brose, R. Brown, A.M. Brun, F. Brunelli, G. Bucciantini, N. Bulgarelli, A. Burelli, I. Burmistrov, L. Burton, M. Burtovoi, A. Bylund, T. Calisse, P.G. Campoy-Ordaz, A. Cantlay, B.K. Caproni, A. Capuzzo-Dolcetta, R. Caraveo, P. Caroff, S. Carosi, A. Carosi, R. Carquin, E. Carrasco, M.-S. Cascone, E. Cassol, F. Castrejon, N. Castro-Tirado, A.J. Cerasole, D. Cerruti, M. Chadwick, P.M. Chambery, P. Chaty, S. Chen, A.W. Chernyakova, M. Chiavassa, A. Chytka, L. Cifuentes, A. Coimbra Araujo, C.H. Conforti, V. Conte, F. Contreras, J.L. Cortina, J. Costa, A. Costantini, H. Cotter, G. Crestan, S. Cristofari, P. Cuevas, O. Curtis-Ginsberg, Z. Aì, A.D. Amico, G.D. Ammando, F.D. Dadina, M. Dalchenko, M. David, L. Dazzi, F. de Bony de Lavergne, M. De Caprio, V. De Frondat Laadim, F. de Gouveia Dal Pino, E.M. De Lotto, B. De Lucia, M. de Martino, D. de Menezes, R. de Naurois, M. de Ona Wilhelmi, E. de Souza, V. del Peral, L. Delgado Giler, A.G. Delgado, C. Dellaiera, M. DellaValle, M. della Volpe, D. Depaoli, D. Di Girolamo, T. Di Piano, A. Di Pierro, F. Di Tria, R. Di Venere, L. Díaz, C. Diebold, S. Dinesh, A. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan ETH Zürich Institute for Particle Physics and Astrophysics Otto-Stern-Weg 5 Zürich8093 Switzerland Sezione di Fisica Via Roma 56 Siena53100 Italy Université Paris-Saclay Université Paris Cité CEA CNRS AIM Gif-sur-YvetteCedex F-91191 France FSLAC IRL 2009 CNRS/IAC Tenerife La Laguna Spain University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 TuscaloosaAL35487-0324 United States Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Laboratoire Lagrange France Laboratoire Leprince-Ringuet CNRS IN2P3 École polytechnique Institut Polytechnique de Paris Palaiseau91120 France 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 Institute for Computational Cosmology Department of Physics Durham University South Road DurhamDH1 3LE United Kingdom Instituto de Física Teórica UAM CSIC Departamento de Física Teórica Universidad Autónoma de Madrid Campus de Cantoblanco UAM c/ Nicolás Cabrera 13-15 Madrid28049 Spain Pontificia Universidad Católica de Chile Av. Libertador Bernardo O’Higgins 340 Santiago Chile IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain LUTH GEPI and LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen Meudon92190 France INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy INFN Sezione di Perugia Università degli Studi di Perugia Via A. Pascoli Perugia06123 Italy INAF - Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone00040 Italy TÜBİTAK Research Institute for Fundamental Sciences Gebze Kocaeli41470 Turkey

Approximately one hundred sources of very-high-energy (VHE) gamma rays are known in the Milky Way, detected with a combination of targeted observations and surveys. A survey of the entire Galactic Plane in the energy range from a few tens of GeV to a few hundred TeV has been proposed as a Key Science Project for the upcoming Cherenkov Telescope Array Observatory (CTAO). This article presents the status of the studies towards the Galactic Plane Survey (GPS). We build and make publicly available a sky model that combines data from recent observations of known gamma-ray emitters with state-of-the-art physically-driven models of synthetic populations of the three main classes of established Galactic VHE sources (pulsar wind nebulae, young and interacting supernova remnants, and compact binary systems), as well as of interstellar emission from cosmic-ray interactions in the Milky Way. We also perform an optimisation of the observation strategy (pointing pattern and scheduling) based on recent estimations of the instrument performance. We use the improved sky model and observation strategy to simulate GPS data corresponding to a total observation time of 1620 hours spread over ten years. Data are then analysed using the methods and software tools under development for real data. Under our model assumptions and for the realisation considered, we show that the GPS has the potential to increase the number of known Galactic VHE emitters by almost a factor of five. This corresponds to the detection of more than two hundred pulsar wind nebulae and a few tens of supernova remnants at average integral fluxes one order of magnitude lower than in the existing sample above 1 TeV, therefore opening the possibility to perform unprecedented population studies. The GPS also has the potential to provide new VHE detections of binary systems and pulsars, to confirm the existence of a hypothetical population of gamma-ray pulsars with an additional TeV emission component, and to detect brigh

关键词： Cosmology

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Search for continuous gravitational waves from 20 accreting millisecond x-ray pulsars in O3 LIGO data

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Physical Review D 2022年第2期105卷 022002-022002页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain T. Akutsu S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer L. Cadonati G. Cagnoli C. Cahillane J. Calderón Bustillo J. D. Callaghan T. A. Callister E. Ca LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut Lumière Matière F-69622 Villeurbanne France Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Un

Results are presented of searches for continuous gravitational waves from 20 accreting millisecond x-ray pulsars with accurately measured spin frequencies and orbital parameters, using data from the third observing run of the Advanced LIGO and Advanced Virgo detectors. The search algorithm uses a hidden Markov model, where the transition probabilities allow the frequency to wander according to an unbiased random walk, while the J-statistic maximum-likelihood matched filter tracks the binary orbital phase. Three narrow subbands are searched for each target, centered on harmonics of the measured spin frequency. The search yields 16 candidates, consistent with a false alarm probability of 30% per subband and target searched. These candidates, along with one candidate from an additional target-of-opportunity search done for SAX J1808.4−3658, which was in outburst during one month of the observing run, cannot be confidently associated with a known noise source. Additional follow-up does not provide convincing evidence that any are a true astrophysical signal. When all candidates are assumed nonastrophysical, upper limits are set on the maximum wave strain detectable at 95% confidence, h095%. The strictest constraint is h095%=4.7×10−26 from IGR J17062−6143. Constraints on the detectable wave strain from each target lead to constraints on neutron star ellipticity and r-mode amplitude, the strictest of which are ε95%=3.1×10−7 and α95%=1.8×10−5 respectively. This analysis is the most comprehensive and sensitive search of continuous gravitational waves from accreting millisecond x-ray pulsars to date.

关键词： Gravitational waves Binary stars Neutron stars & pulsars

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Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation

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Physical Review Letters 2016年第22期116卷 228301-228301页

作者： Dane Taylor Saray Shai Natalie Stanley Peter J. Mucha Carolina Center for Interdisciplinary Applied Mathematics Department of Mathematics University of North Carolina Chapel Hill North Carolina 27599 USA Curriculum in Bioinformatics and Computational Biology University of North Carolina Chapel Hill North Carolina 27599 USA

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers’ adjacency matrices for which we show the detectability limit vanishes as O(L−1/2) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common—but not well understood—practice of thresholding pairwise-interaction data to obtain sparse network representations.

关键词： Community structure Multilayer & multiplex networks

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Comparison of Polarized Radiative Transfer Codes Used by the EHT Collaboration

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The Astrophysical Journal 2023年第1期950卷 35-35页

作者： Ben S. Prather Jason Dexter Monika Moscibrodzka Hung-Yi Pu Thomas Bronzwaer Jordy Davelaar Ziri Younsi Charles F. Gammie Roman Gold George N. Wong Kazunori Akiyama Antxon Alberdi Walter Alef Juan Carlos Algaba Richard Anantua Keiichi Asada Rebecca Azulay Uwe Bach Anne-Kathrin Baczko David Ball Mislav Baloković John Barrett Michi Bauböck Bradford A. Benson Dan Bintley Lindy Blackburn Raymond Blundell Katherine L. Bouman Geoffrey C. Bower Hope Boyce Michael Bremer Christiaan D. Brinkerink Roger Brissenden Silke Britzen Avery E. Broderick Dominique Broguiere Sandra Bustamante Do-Young Byun John E. Carlstrom Chiara Ceccobello Andrew Chael Chi-kwan Chan Dominic O. Chang Koushik Chatterjee Shami Chatterjee Ming-Tang Chen Yongjun Chen Xiaopeng Cheng Ilje Cho Pierre Christian Nicholas S. Conroy John E. Conway James M. Cordes Thomas M. Crawford Geoffrey B. Crew Alejandro Cruz-Osorio Yuzhu Cui Mariafelicia De Laurentis Roger Deane Jessica Dempsey Gregory Desvignes Vedant Dhruv Sheperd S. Doeleman Sean Dougal Sergio A. Dzib Ralph P. Eatough Razieh Emami Heino Falcke Joseph Farah Vincent L. Fish Ed Fomalont H. Alyson Ford Raquel Fraga-Encinas William T. Freeman Per Friberg Christian M. Fromm Antonio Fuentes Peter Galison Roberto García Olivier Gentaz Boris Georgiev Ciriaco Goddi Arturo I. Gómez-Ruiz José L. Gómez Minfeng Gu Mark Gurwell Kazuhiro Hada Daryl Haggard Kari Haworth Michael H. Hecht Ronald Hesper Dirk Heumann Luis C. Ho Paul Ho Mareki Honma Chih-Wei L. Huang Lei Huang David H. Hughes Shiro Ikeda C. M. Violette Impellizzeri Makoto Inoue Sara Issaoun David J. James Buell T. Jannuzi Michael Janssen Britton Jeter Wu Jiang Alejandra Jiménez-Rosales Michael D. Johnson Svetlana Jorstad Abhishek V. Joshi Taehyun Jung Mansour Karami Ramesh Karuppusamy Tomohisa Kawashima Garrett K. Keating Mark Kettenis Dong-Jin Kim Jae-Young Kim Jongsoo Kim Junhan Kim Motoki Kino Jun Yi Koay Prashant Kocherlakota Yutaro Kofuji Shoko Koyama Carsten Kramer Michael Kramer Thomas P. Krichbaum Cheng-Yu Kuo Noemi La Bella Tod R. Lauer Daeyoung L CCS-2 Los Alamos National Laboratory P.O. Box 1663 Los Alamos NM 87545 USA bprather@lanl.gov JILA and Department of Astrophysical and Planetary Sciences University of Colorado Boulder CO 80309 USA Department of Astrophysics/IMAPP Radboud University P.O. Box 9010 6500 GL Nijmegen The Netherlands Department of Physics National Taiwan Normal University No. 88 Sec.4 Tingzhou Road Taipei 116 Taiwan R.O.C. Center of Astronomy and Gravitation National Taiwan Normal University No. 88 Sec. 4 Tingzhou Road Taipei 116 Taiwan R.O.C. Institute of Astronomy and Astrophysics Academia Sinica 11F of Astronomy-Mathematics Building AS/NTU No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan R.O.C. Department of Astronomy and Columbia Astrophysics Laboratory Columbia University 550 W. 120th Street New York NY 10027 USA Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New York NY 10010 USA Department of Astrophysics Institute for Mathematics Astrophysics and Particle Physics (IMAPP) Radboud University P.O. Box 9010 6500 GL Nijmegen The Netherlands Mullard Space Science Laboratory University College London Holmbury St. Mary Dorking Surrey RH5 6NT UK Institut für Theoretische Physik Goethe-Universität Frankfurt Max-von-Laue-Straße 1 D-60438 Frankfurt am Main Germany Department of Physics University of Illinois 1110 West Green Street Urbana IL 61801 USA Department of Astronomy University of Illinois at Urbana-Champaign 1002 West Green Street Urbana IL 61801 USA NCSA University of Illinois 1205 W. Clark Street Urbana IL 61801 USA CP3-Origins University of Southern Denmark Campusvej 55 DK-5230 Odense M Denmark School of Natural Sciences Institute for Advanced Study 1 Einstein Drive Princeton NJ 08540 USA Princeton Gravity Initiative Princeton University Princeton NJ 08544 USA Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road Westford MA 01886 USA National Astronomical Observatory of Japan 2-21-1 Osaw

Interpretation of resolved polarized images of black holes by the Event Horizon Telescope (EHT) requires predictions of the polarized emission observable by an Earth-based instrument for a particular model of the black hole accretion system. Such predictions are generated by general relativistic radiative transfer (GRRT) codes, which integrate the equations of polarized radiative transfer in curved spacetime. A selection of ray-tracing GRRT codes used within the EHT Collaboration is evaluated for accuracy and consistency in producing a selection of test images, demonstrating that the various methods and implementations of radiative transfer calculations are highly consistent. When imaging an analytic accretion model, we find that all codes produce images similar within a pixel-wise normalized mean squared error (NMSE) of 0.012 in the worst case. When imaging a snapshot from a cell-based magnetohydrodynamic simulation, we find all test images to be similar within NMSEs of 0.02, 0.04, 0.04, and 0.12 in Stokes I, Q, U, and V, respectively. We additionally find the values of several image metrics relevant to published EHT results to be in agreement to much better precision than measurement uncertainties.

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Theory of the Lattice Boltzmann method: Derivation of macroscopic equations via the Maxwell iteration

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Physical Review E 2016年第3期93卷 033310-033310页

作者： Wen-An Yong (雍稳安) Weifeng Zhao (赵伟峰) Li-Shi Luo (罗礼诗) Zhou Pei-Yuan Center for Applied Mathematics Tsinghua University Beijing 100084 China Beijing Computational Science Research Center Beijing 100094 China Department of Mathematics & Statistics Old Dominion University Norfolk Virginia 23529 USA

We propose using the Maxwell iteration to derive the hydrodynamic equations from the lattice Boltzmann equation (LBE) with an external forcing term. The proposed methodology differs from existing approaches in several aspects. First, it need not explicitly introduce multiple-timescales or the Knudsen number, both of which are required in the Chapman–Enskog analysis. Second, it need not use the Hilbert expansion of the hydrodynamic variables, which is necessary in the asymptotic analysis of the LBE. The proposed methodology assumes the acoustic scaling (or the convective scaling) δt∼δx, thus δt is the only expansion parameter in the analysis of the LBE system, and it leads to the Navier–Stokes equations in compressible form. The forcing density derived in this work can reproduce existing forcing schemes by adjusting appropriate parameters. The proposed methodology also analyzes the numerical accuracy of the LBE. In particular, it shows the Mach number Ma should scale as O(δt1/3) to maintain the truncation errors due to Ma and δt in balance when δt→0, so that the LBE can converge to the expected hydrodynamic equations effectively and efficiently.

关键词： Lattice-Boltzmann methods

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Effect on electronic and optical properties of Frenkel and Schottky defects in HfS2 monolayer

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AIP Conference Proceedings 2018年第1期1942卷

作者： Deobrat Singh Nisha Singh Sanjeev K. Gupta Yogesh Sonvane 1Department of Applied Physics S. V. National Institute of Technology Surat 395007 India 2Department of Physics Marwadi University Rajkot 360003 India 3Department of Mathematics Marwadi University Rajkot 360003 India 4Computational Materials and Nanoscience Group Department of Physics and Electronics St. Xavier’s College Ahmedabad 380009 India

In the present work, we have investigated structural, electronic and optical properties of Frenkel and Schottky defects in monolayer HfS2 using first principles calculations. We have observed that the possible changes in the electronic, optical properties such as dielectric function and optical absorption spectrum due to the modulating of electronic band gap. The electronic band gaps are 1.26 eV for pure monolayer HfS2, 0.28 eV for Frenkel defect and 1.49 eV for Schottky defect in monolayer HfS2. Our study suggests that the growth of ultra-high-quality monolayer hafnium disulphide appears a structural defect which is an effective approach to modify electronic and optical properties for opening an alternative way for future high-performance electronic devices, optoelectronic and spintronics applications.

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Interpretable nonlinear dynamic modeling of neural trajectories 16

Interpretable nonlinear dynamic modeling of neural trajector...

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Proceedings of the 30th International Conference on Neural Information Processing Systems

作者： Yuan Zhao Memming Park Il Department of Neurobiology and Behavior Department of Applied Mathematics and Statistics Institute for Advanced Computational Science Stony Brook University NY

ISBN: (纸本)9781510838819

A central challenge in neuroscience is understanding how neural system implements computation through its dynamics. We propose a nonlinear time series model aimed at characterizing interpretable dynamics from neural trajectories. Our model assumes low-dimensional continuous dynamics in a finite volume. It incorporates a prior assumption about globally contractional dynamics to avoid overly enthusiastic extrapolation outside of the support of observed trajectories. We show that our model can recover qualitative features of the phase portrait such as attractors, slow points, and bifurcations, while also producing reliable long-term future predictions in a variety of dynamical models and in real neural data.

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Transient analysis of a resource-limited recovery policy for epidemics: A retrial queueing approach 37

Transient analysis of a resource-limited recovery policy for...

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37th IEEE Sarnoff Symposium, Sarnoff 2016

作者： Dadlani, Aresh Kumar, Muthukrishnan Senthil Kim, Kiseon Sahneh, Faryad Darabi School of EECS Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of Department of Applied Mathematics and Computational Science PSG College of Technology India School of Computer Science Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (纸本)9781509015405

Knowledge on the dynamics of standard epidemic models and their variants over complex networks has been well-established primarily in the stationary regime, with relatively little light shed on their transient behavior. In this paper, we analyze the transient characteristics of the classical susceptible-infected (SI) process with a recovery policy modeled as a state-dependent retrial queueing system in which arriving infected nodes, upon finding all the limited number of recovery units busy, join a virtual buffer and try persistently for service in order to regain susceptibility. In particular, we formulate the stochastic SI epidemic model with added retrial phenomenon as a finite continuous-time Markov chain (CTMC) and derive the Laplace transforms of the underlying transient state probability distributions and corresponding moments for a closed population of size N driven by homogeneous and heterogeneous contacts. Our numerical results reveal the strong influence of infection heterogeneity and retrial frequency on the transient behavior of the model for various performance measures. © 2016 IEEE.

关键词： Laplace transforms

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