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arXiv 2022年

作者： Bauer, Christian W. Davoudi, Zohreh Balantekin, A. Baha Bhattacharya, Tanmoy Carena, Marcela de Jong, Wibe A. Draper, Patrick El-Khadra, Aida Gemelke, Nate Hanada, Masanori Kharzeev, Dmitri Lamm, Henry Li, Ying-Ying Liu, Junyu Lukin, Mikhail Meurice, Yannick Monroe, Christopher Nachman, Benjamin Pagano, Guido Preskill, John Rinaldi, Enrico Roggero, Alessandro Santiago, David I. Savage, Martin J. Siddiqi, Irfan Siopsis, George Van Zanten, David Wiebe, Nathan Yamauchi, Yukari Yeter-Aydeniz, Kübra Zorzetti, Silvia Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Physics Maryland Center for Fundamental Physics University of Maryland College ParkMD20742 United States Department of Physics University of Wisconsin MadisonWI53706 United States T-2 Los Alamos National Laboratory Los AlamosNM87545 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Enrico Fermi Institute University of Chicago ChicagoIL60637 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Department of Physics University of Chicago ChicagoIL60637 United States Department of Physics Illinois Center for the Advanced Study of the Universe and Illinois Quantum Information Science and Technology Center University of Illinois UrbanaIL61801 United States QuEra Computing Inc BostonMA02135 United States Department of Mathematics University of Surrey Guildford Surrey GU2 7XH United Kingdom Center for Nuclear Theory Department of Physics and Astronomy Stony Brook University NY11794-3800 United States Department of Physics Brookhaven National Laboratory UptonNY11973 United States Pritzker School of Molecular Engineering Chicago Quantum Exchange Kadanoff Center for Theoretical Physics University of Chicago IL60637 United States QBraid Co. Harper Court 5235 ChicagoIL60615 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Physics and Astronomy University of Iowa Iowa CityIA52242 United States Duke Quantum Center Duke University DurhamNC27701 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Physics Duke University DurhamNC27708 United States IonQ Inc. College ParkMD20740 United States Physics and Astronomy Department Rice University HoustonTX77005 United States Institute for Quantum Information and Matter Californi

It is for the first time that quantum simulation for High Energy Physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in Quantum Information Sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This community whitepaper is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond. © 2022, CC BY.

关键词： High energy physics

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Numerical Study of Mixed Convection Heat Transfer in Methanol based Micropolar Nanofluid about a Horizontal Circular Cylinder

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Journal of Physics: Conference Series 2019年第1期1366卷

作者： M Z Swalmeh H T Alkasasbeh A Hussanan M Mamat Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (Kampus Gong Badak) 21300 Kuala Terengganu Terengganu Malaysia Faculty of Arts and Sciences Aqaba University of Technology Aqaba-Jordan Department of Mathematics Faculty of Science Ajloun National University P.O. Box 43 Ajloun 26810 Jordan Division of Computational Mathematics and Engineering Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Vietnam Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Vietnam

In this article, the mixed convection boundary layer flow about a horizontal circular cylinder with a micropolar nanofluid, which is maintained at a constant surface heat flux, has been investigated. Three types of nanoparticles with distinct conductivities, namely, graphene oxide, copper and copper oxide are considered and suspended in methanol based micropolar nanofluid. The governing equations are transformed into nonlinear PDEs by applying the similarity transformations and then solved numerically by an implicit finite difference scheme known as Keller-box method. The results for the local wall temperature, local skin friction coefficient, temperature, velocity and angular velocity are plotted and discussed for different parameters such as nanoparticles volume fraction and mixed convection parameter in view of thermo-physical properties of nanoparticles and base fluid. Moreover, numerical results for the local wall temperature and local skin friction coefficient are obtained. It is found that copper (Cu) suspended methanol based micropolar nanofluid have higher velocity than the copper oxide (CuO) or graphene oxide (GO) methanol based micropolar nanofluid. Comparison have been made with published results on Newtonian fluid under special cases and obtained in close agreement.

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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

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Physical Review X 2023年第4期13卷 041039-041039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 P. Ajith S. Akcay 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 M. Arogeti 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 C. P. L. Berry 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. Brandt 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 G. S. Cabourn Davies L. Cadonati G. Cagn 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 and 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 International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India University College Dublin Dublin 4 Ireland 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 L

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

关键词： Gravitational waves

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Claire: A distributed-memory solver for constrained large deformation diffeomorphic image registration

arXiv

引用

arXiv 2018年

作者： Mang, Andreas Gholami, Amir Davatzikos, Christos Biros, George Department of Mathematics University of Houston HoustonTX77204-5008 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720-1770 United States Center for Biomedical Image Computing and Analytics Department of Radiology University of Pennsylvania PhiladephiaPA19104-2643 United States Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX78712-1229 United States

68U10, 49J20, 35Q93, 65K10, 65F08, 76D55We introduce CLAIRE, a distributed-memory algorithm and software for solving constrained large deformation diffeomorphic image registration problems in three dimensions. We invert for a stationary velocity field that parameterizes the deformation map. Our solver is based on a globalized, preconditioned, inexact reduced space Gauss-Newton-Krylov scheme. We exploit state-of-the-art techniques in scientific computing to develop an effective solver that scales to thousand of distributed memory nodes on high-end clusters. Our improved, parallel implementation features parameter-, scale-, and grid-continuation schemes to speedup the computations and reduce the likelihood to get trapped in local minima. We also implement an improved preconditioner for the reduced space Hessian to speedup the convergence. We test registration performance on synthetic and real data. We demonstrate registration accuracy on 16 neuroimaging datasets. We compare the performance of our scheme against different flavors of the DEMONS algorithm for diffeomorphic image registration. We study convergence of our preconditioner and our overall algorithm. We report scalability results on state-of-the-art supercomputing platforms. We demonstrate that we can solve registration problems for clinically relevant data sizes in two to four minutes on a standard compute node with 20 cores, attaining excellent data fidelity. With the present work we achieve a speedup of (on average) 5× with a peak performance of up to 17× compared to our former work. Copyright © 2018, The Authors. All rights reserved.

关键词： Neuroimaging

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Joint base station clustering and beamforming for non-orthogonal multicast and unicast transmission with backhaul constraints

arXiv

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arXiv 2017年

作者： Chen, Erkai Tao, Meixia Liu, Ya-Feng Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

The demand for providing multicast services in cellular networks is continuously and fastly increasing. In this work, we propose a non-orthogonal transmission framework based on layered-division multiplexing (LDM) to support multicast and unicast services concurrently in cooperative multi-cell cellular networks with limited backhaul capacity. We adopt a two-layer LDM structure where the first layer is intended for multicast services, the second layer is for unicast services, and the two layers are superposed with different beamformers. Each user decodes the multicast message first, subtracts it, and then decodes its dedicated unicast message. We formulate a joint multicast and unicast beamforming problem with adaptive base station clustering that aims to maximize the weighted sum of the multicast rate and the unicast rate under per-BS power and backhaul constraints. To solve the problem, we first develop a branch-and-bound algorithm to find its global optimum. We then reformulate the problem as a sparse beamforming problem and propose a low-complexity algorithm based on convex-concave procedure. Simulation results demonstrate the significant superiority of the proposed LDM-based non-orthogonal scheme over orthogonal schemes in terms of the achievable multicast-unicast rate region. Copyright © 2017, The Authors. All rights reserved.

关键词： Beamforming

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Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

arXiv

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arXiv 2023年

作者： Alexeev, Yuri Amsler, Maximilian Barroca, Marco Antonio Bassini, Sanzio Battelle, Torey Camps, Daan Casanova, David Choi, Young Jai Chong, Frederic T. Chung, Charles Codella, Christopher Córcoles, Antonio D. Cruise, James Di Meglio, Alberto Duran, Ivan Eckl, Thomas Economou, Sophia Eidenbenz, Stephan Elmegreen, Bruce Fare, Clyde Faro, Ismael Fernández, Cristina Sanz Ferreira, Rodrigo Neumann Barros Fuji, Keisuke Fuller, Bryce Gagliardi, Laura Galli, Giulia Glick, Jennifer R. Gobbi, Isacco Gokhale, Pranav de la Puente Gonzalez, Salvador Greiner, Johannes Gropp, Bill Grossi, Michele Gull, Emanuel Healy, Burns Hermes, Matthew R. Huang, Benchen Humble, Travis S. Ito, Nobuyasu Izmaylov, Artur F. Javadi-Abhari, Ali Jennewein, Douglas Jha, Shantenu Jiang, Liang Jones, Barbara de Jong, Wibe Albert Jurcevic, Petar Kirby, William Kister, Stefan Kitagawa, Masahiro Klassen, Joel Klymko, Katherine Koh, Kwangwon Kondo, Masaaki Kürkçüoglu, Doga Murat Kurowski, Krzysztof Laino, Teodoro Landfield, Ryan Leininger, Matt Leyton-Ortega, Vicente Li, Ang Lin, Meifeng Liu, Junyu Lorente, Nicolas Luckow, Andre Martiel, Simon Martin-Fernandez, Francisco Martonosi, Margaret Marvinney, Claire Medina, Arcesio Castaneda Merten, Dirk Mezzacapo, Antonio Michielsen, Kristel Mitra, Abhishek Mittal, Tushar Moon, Kyungsun Moore, Joel Mostame, Sarah Motta, Mario Na, Young-Hye Nam, Yunseong Narang, Prineha Ohnishi, Yu-Ya Ottaviani, Daniele Otten, Matthew Pakin, Scott Pascuzzi, Vincent R. Pednault, Edwin Piontek, Tomasz Pitera, Jed Rall, Patrick Ravi, Gokul Subramanian Robertson, Niall Rossi, Matteo A.C. Rydlichowski, Piotr Ryu, Hoon Samsonidze, Georgy Sato, Mitsuhisa Saurabh, Nishant Sharma, Vidushi Sharma, Kunal Shin, Soyoung Slessman, George Steiner, Mathias Sitdikov, Iskandar Suh, In-Saeng Switzer, Eric D. Tang, Wei Thompson, Joel Todo, Synge Tran, Minh C. Trenev, Dimitar Trott, Christian Tseng, Huan-Hsin Tubman, Norm M. Tureci, Esin Valiñas, David García Vallecorsa, Sofia Wever, Christopher Wojciechowski, Konrad Wu, Xiaodi Yoo, Shinjae Yoshioka, Argonne National Laboratory LemontIL60439 United States Corporate Sector Research and Advance Engineering Robert Bosch GmbH Robert-Bosch-Campus 1 RenningenD-71272 Germany IBM Research RJ Rio de Janeiro20031-170 Brazil Centro Brasileiro de Pesquisas Físicas RJ Rio de Janeiro22290-180 Brazil CINECA via Magnanelli 6/3 BO Casalecchio di Reno40033 Italy Arizona State University TempeAZ United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA United States Euskadi Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Physics Yonsei University Seoul03722 Korea Republic of University of Chicago ChicagoIL United States IBM Quantum IBM T.J. Watson Research Center Yorktown Heights NY10598 United States Cambridge Consultants part of Capgemini Invent Cambridge United Kingdom Geneva1211 Switzerland Virginia Tech BlacksburgVA24061 United States Los Alamos National Laboratory Los AlamosNM87545 United States Osaka University Osaka560-8531 Japan Department of Chemistry Chicago Center for Theoretical Chemistry University of Chicago ChicagoIL United States Fraunhofer ITWM Rheinland-Pfalz Kaiserslautern67663 Germany Infleqtion ChicagoIL60622 United States University of Illinois Urbana-Champaign United States University of Michigan Ann ArborMI48109 United States Research Office Oak Ridge National Laboratory One Bethel Valley Road Oak RidgeTN37831 United States Hyogo Kobe650-0047 Japan Chemical Physics Theory Group Department of Chemistry University of Toronto TorontoONM5S 3H6 Canada Department of Physical and Environmental Sciences University of Toronto Scarborough TorontoONM1C 1A4 Canada Brookhaven National Laboratory UptonNY United States Rutgers University New BrunswickNJ United States IBM Quantum Almaden Research Center San JoseCA95120 United States Applied Mathematics and Computational Research Division

computational models are an essential tool for the design, characterization, and discovery of novel materials. computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions. Copyright © 2023, The Authors. All rights reserved.

关键词： Characterization (materials science)

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High order fast algorithm for the Caputo fractional derivative

arXiv

引用

arXiv 2017年

作者： Wang, Kun Huang, Jizu College of Mathematics and Statistics Chongqing University Chongqing401331 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

In the paper, we present a high order fast algorithm with almost optimum memory for the Caputo fractional derivative, which can be expressed as a convolution of u′(t) with the kernel (tn- t)-α. In the fast algorithm, the interval [0, tn-1] is split into nonuniform subintervals. The number of the subintervals is in the order of log n at the n-th time step. The fractional kernel function is approximated by a polynomial function of K-th degree with a uniform absolute error on each subinterval. We save K+1 integrals on each subinterval, which can be written as a convolution of u′(t) with a polynomial base function. As compared with the direct method, the proposed fast algorithm reduces the storage requirement and computational cost from O(n) to O((K + 1) log n) at the n-th time step. We prove that the convergence rate of the fast algorithm is the same as the direct method even a high order direct method is considered. The convergence rate and efficiency of the fast algorithm are illustrated via several numerical examples. Copyright © 2017, The Authors. All rights reserved.

关键词： Polynomial approximation

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Conductivity in the square lattice Hubbard model at high temperatures: importance of vertex corrections

arXiv

引用

arXiv 2018年

作者： Vučičević, J. Kokalj, J. Žitko, R. Wentzell, N. Tanasković, D. Mravlje, J. Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia University of Ljubljana Faculty of Civil and Geodetic Engineering Jamova 2 Ljubljana Slovenia Jozef Stefan Institute Jamova 39 LjubljanaSI-1000 Slovenia University of Ljubljana Faculty of Mathematics and Physics Jadranska 19 Ljubljana Slovenia Center for Computational Quantum Physics Simons Foundation Flatiron Institute New YorkNY10010 United States

Recent experiments on cold atoms in optical lattices allow for a quantitative comparison of the measurements to the conductivity calculations in the square lattice Hubbard model. However, the available calculations do not give consistent results and the question of the exact solution for the conductivity in the Hubbard model remained open. In this letter we employ several complementary state-of-the-art numerical methods to disentangle various contributions to conductivity, and identify the best available result to be compared to experiment. We find that at relevant (high) temperatures, the self-energy is practically local, yet the vertex corrections remain rather important, contrary to expectations. The finite-size effects are small even at the lattice size 4 × 4 and the corresponding Lanczos diagonalization result is therefore close to the exact result in the thermodynamic limit. Copyright © 2018, The Authors. All rights reserved.

关键词： Crystal lattices

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Convergence Analysis of an Unconditionally Energy Stable Linear Crank-Nicolson Scheme for the Cahn-Hilliard Equation

arXiv

引用

arXiv 2017年

作者： Wang, Lin Yu, Haijun School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 Ncmis and Lsec Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190

Efficient and unconditionally stable high order time marching schemes are very important but not easy to construct for nonlinear phase dynamics. In this paper, we propose and analysis an efficient stabilized linear Crank-Nicolson scheme for the Cahn-Hilliard equation with provable unconditional stability. In this scheme the nonlinear bulk force are treated explicitly with two second-order linear stabilization terms. The semi-discretized equation is a linear elliptic system with constant coefficients, thus robust and efficient solution procedures are guaranteed. Rigorous error analysis show that, when the time step-size is small enough, the scheme is second order accurate in time with a prefactor controlled by some lower degree polynomial of 1/". Here " is the interface thickness parameter. Numerical results are presented to verify the accuracy and efficiency of the *** Codes 65M12, 65M15, 65P40 Copyright © 2017, The Authors. All rights reserved.

关键词： Phase interfaces

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Sharp-interface limits of a phase-field model with a generalized Navier slip boundary condition for moving contact lines

arXiv

引用

arXiv 2017年

作者： Xu, Xianmin Di, Yana Yu, Haijun School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 Ncmis and Lsec Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190

The sharp-interface limits of a phase-field model with a generalized Navier slip boundary condition for moving contact line problem are studied by asymptotic analysis and numerical simulations. The effects of the mobility number as well as a phenomenological relaxation parameter in the boundary condition are considered. In asymptotic analysis, we focus on the case that the mobility number is the same order of the Cahn number and derive the sharp-interface limits for several setups of the boundary relaxation parameter. It is shown that the sharp interface limit of the phase field model is the standard two-phase incompressible Navier-Stokes equations coupled with several different slip boundary conditions. Numerical results are consistent with the analysis results and also illustrate the different convergence rates of the sharp-interface limits for different scalings of the two parameters. Copyright © 2017, The Authors. All rights reserved.

关键词： Asymptotic analysis

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