检索结果-内蒙古大学图书馆

Sp(2N) Yang-Mills theories on the lattice: Scale setting and topology

Physical Review D 2022年第9期106卷 094503-094503页

作者： Ed Bennett Deog Ki Hong Jong-Wan Lee C.-J. David Lin Biagio Lucini Maurizio Piai Davide Vadacchino Swansea Academy of Advanced Computing Swansea University Fabian Way SA1 8EN Swansea Wales United Kingdom Department of Physics Pusan National University Busan 46241 Republic of Korea Institute for Extreme Physics Pusan National University Busan 46241 Republic of Korea Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu 30010 Taiwan Center for High Energy Physics Chung-Yuan Christian University Chung-Li 32023 Taiwan Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu 30010 Taiwan Physics Division National Centre for Theoretical Sciences Taipei 10617 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Fabian Way SA1 8EN Swansea Wales United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park SA2 8PP Swansea Wales United Kingdom School of Mathematics and Hamilton Mathematics Institute Trinity College Dublin 2 Ireland Centre for Mathematical Sciences University of Plymouth PL4 8AA Plymouth United Kingdom

We study Yang-Mills lattice theories with Sp(Nc) gauge group, with Nc=2N, for N=1,…,4. We show that if we divide the renormalized couplings appearing in the Wilson flow by the quadratic Casimir C2(F) of the Sp(Nc) group, then the resulting quantities display a good agreement among all values of Nc considered, over a finite interval in flow time. We use this scaled version of the Wilson flow as a scale-setting procedure, compute the topological susceptibility of the Sp(Nc) theories, and extrapolate the results to the continuum limit for each Nc.

关键词： Large-N expansion in field theory Lattice field theory Nonperturbative effects in field theory Quantum field theory Strong interaction Topology

来源：评论

学校读者我要写书评

暂无评论

On the mixing between flavor singlets in lattice gauge theories coupled to matter fields in multiple representations

arXiv

引用

arXiv 2024年

作者： Bennett, Ed Forzano, Niccolò Hong, Deog Ki Hsiao, Ho Lee, Jong-Wan Lin, C.-J. David Lucini, Biagio Piai, Maurizio Vadacchino, Davide Zierler, Fabian Swansea Academy of Advanced Computing Swansea University Bay Campus Fabian Way Wales SwanseaSA1 8EN United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park Wales SwanseaSA2 8PP United Kingdom Department of Physics Pusan National University Busan46241 Korea Republic of Extreme Physics Institute Pusan National University Busan46241 Korea Republic of Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Daejeon34126 Korea Republic of Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Centre for High Energy Physics Chung-Yuan Christian University Chung-Li32023 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Bay Campus Fabian Way Wales SwanseaSA1 8EN United Kingdom Centre for Mathematical Sciences University of Plymouth PlymouthPL4 8AA United Kingdom

We provide the first extensive, numerical study of the non-trivial problem of mixing between flavor-singlet composite states emerging in strongly coupled lattice field theories with matter field content consisting of fermions transforming in different representations of the gauge group. The theory of interest is the minimal candidate for a composite Higgs model that also accommodates a mechanism for top partial compositeness: the Sp(4) gauge theory coupled to two (Dirac) fermions transforming as the fundamental and three as the two-index antisymmetric representation of the gauge group, respectively. We apply an admixture of APE and Wuppertal smearings, as well as the generalized eigenvalue problem approach, to two-point functions involving flavor-singlet mesons, for ensembles having time extent longer than the space extent. We demonstrate that, in the region of lattice parameter space accessible to this study, both masses and mixing angles can be measured effectively, despite the presence of (numerically noisy) contributions from disconnected diagrams. © 2024, CC BY.

关键词： Fermions

来源：评论

学校读者我要写书评

暂无评论

Perspectives on adaptive dynamical systems

arXiv

引用

arXiv 2023年

作者： Sawicki, Jakub Berner, Rico Loos, Sarah A.M. Anvari, Mehrnaz Bader, Rolf Barfuss, Wolfram Botta, Nicola Brede, Nuria Franović, Igor Gauthier, Daniel J. Goldt, Sebastian Hajizadeh, Aida Hövel, Philipp Karin, Omer Lorenz-Spreen, Philipp Miehl, Christoph Mölter, Jan Olmi, Simona Schöll, Eckehard Seif, Alireza Tass, Peter A. Volpe, Giovanni Yanchuk, Serhiy Kurths, Jürgen Potsdam Institute for Climate Impact Research Telegrafenberg Potsdam14473 Germany Fachhochschule Nordwestschweiz FHNW Leonhardsstrasse 6 Basel4009 Switzerland Department of Physics Humboldt-Universität zu Berlin Newtonstraße 15 Berlin12489 Germany DAMTP University of Cambridge Wilberforce Road CambridgeCB3 0WA United Kingdom Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt-Augustin53757 Germany Institute of Systematic Musicology University of Hamburg Germany Transdisciplinary Research Area: Sustainable Futures University of Bonn Bonn53113 Germany University of Bonn Bonn53113 Germany Department of Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden Department of Computer Science University of Potsdam An der Bahn 2 Potsdam14476 Germany Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia The Ohio State University Department of Physics and Electrical and Computer Engineering 191 West Woodruff Ave ColumbusOH43210 United States ResCon Technologies LLC 1275 Kinnear Rd. Suite 239 ColumbusOH43212 United States Trieste Italy Research Group Comparative Neuroscience Leibniz Institute for Neurobiology Magdeburg Germany Theoretical Physics Saarland University Saarbrücken66123 Germany Center for Biophysics Saarland University Saarbrücken66123 Germany Department of Mathematics Imperial College London United Kingdom Center for Adaptive Rationality Max Planck Institute for Human Development Lentzeallee 94 Berlin14195 Germany Max Planck Institute for Brain Research Max-von-Laue-Straße 4 Frankfurt am Main60438 Germany Technical University of Munich School of Life Sciences Alte Akademie 8 Freising85354 Germany Department of Mathematics School of Computation Information and Technology Technical University of Munich Boltzmannstraße 3 Garching bei München8574

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges, and give perspectives on future research directions, looking to inspire interdisciplinary approaches. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

A coupling strategy for a 3D-1D model of the cardiovascular system to study the effects of pulse wave propagation on cardiac function

arXiv

引用

arXiv 2021年

作者： Caforio, Federica Augustin, Christoph M. Alastruey, Jordi Gsell, Matthias A.F. Plank, Gernot Institute of Mathematics and Scientific Computing NAWI Graz University of Graz Graz Austria Gottfried Schatz Research Center Division of Biophysics Medical University of Graz Graz Austria Department of Biomedical Engineering Division of Imaging Sciences and Biomedical Engineering King’s College London King’s Health Partners St. Thomas’ Hospital LondonSE1 7EH United Kingdom World-Class Research Center "Digital Biodesign and Personalized Healthcare" Sechenov University Moscow Russia

The impact of increased stiffness and pulsatile load on the circulation and their influence on heart performance have been documented not only for cardiovascular events but also for ventricular dysfunctions. For this reason, computer models of cardiac electromechanics (EM) have to integrate effects of the circulatory system on heart function to be relevant for clinical applications. Currently it is not feasible to consider three-dimensional (3D) models of the entire circulation. Instead, simplified representations of the circulation are used, ensuring a satisfactory trade-off between accuracy and computational cost. In this work, we propose a novel and stable strategy to couple a 3D EM model of the heart to a one-dimensional (1D) model of blood flow in the arterial system. A personalised coupled 3D-1D model of LV and arterial system is built and used in a numerical benchmark to demonstrate robustness and accuracy of our scheme over a range of time steps. Validation of the coupled model is performed by investigating the coupled system’s physiological response to variations in the arterial system affecting pulse wave propagation, comprising aortic stiffening, aortic stenosis or bifurcations causing wave reflections. Our results show that the coupled 3D-1D model is robust, stable and correctly replicates known physiology. In comparison with standard coupled 3D-0D models, additional computational costs are negligible, thus facilitating the use of our coupled 3D-1D model as a key methodology in studies where wave propagation effects are under investigation. © 2021, CC BY-NC-ND.

关键词： Heart

来源：评论

学校读者我要写书评

暂无评论

Modeling subgrid-scale force and divergence of heat flux of compressible isotropic turbulence by artificial neural network

引用

Physical Review Fluids 2019年第10期4卷 104605-104605页

作者： Chenyue Xie Ke Li Chao Ma Jianchun Wang Shenzhen Key Laboratory of Complex Aerospace Flows Center for Complex Flows and Soft Matter Research Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen 518055 People's Republic of China Institute of Computational Mathematics and Scientific Engineering Computing Chinese Academy of Sciences Beijing 100190 People's Republic of China The Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

In this paper, the subgrid-scale (SGS) force and the divergence of SGS heat flux of compressible isotropic turbulence are modeled directly by an artificial neural network (ANN), which serves as a data-driven SGS modeling tool for large-eddy simulations (LESs). The unclosed SGS force and divergence of SGS heat flux are modeled based on the local stencil geometry with Galilean invariance. The input features include the first-order and second-order derivatives of filtered velocity and temperature, filtered density, and its first-order derivative. It is shown that the proposed ANN-F7 model shows an advantage over the gradient model in the a priori test. Specifically, the ANN-F7 model gives larger correlation coefficients and smaller relative errors than the gradient model. In an a posteriori analysis, the ANN-F7 model performs better than the dynamic Smagorinsky model (DSM) and dynamic mixed model (DMM) in the prediction of the statistical properties of flow fields at the Taylor microscale Reynolds number Reλ ranging from 180 to 250. The DSM and DMM models lead to the typical tilted spectral distribution of velocity, where low wave numbers are too energy rich, while those near the cutoff are damped too strongly. In contrast, it is shown that the velocity spectrum predicted by the ANN-F7 model almost overlaps with the filtered direct numerical simulation data. Besides, the ANN-F7 model reconstructs the probability density functions of SGS force and divergence of SGS heat flux much better than the DSM and DMM models. An artificial neural network with reasonable physical input features can deepen our understanding of turbulence modeling.

关键词： Compressible flows Turbulence Artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

DRIFT-PRESERVING NUMERICAL INTEGRATORS FOR STOCHASTIC HAMILTONIAN SYSTEMS

arXiv

引用

arXiv 2019年

作者： Chen, Chuchu Cohen, David D'Ambrosio, Raffaele Lang, Annika 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 Department of Mathematics and Mathematical Statistics Umeå University Umeå90187 Sweden Department of Engineering and Computer Science and Mathematics University of L'Aquila AQ L'Aquila Italy Department of Mathematical Sciences Chalmers University of Technology University of Gothenburg Göteborg41296 Sweden

The paper deals with numerical discretizations of separable nonlinear Hamiltonian systems with additive noise. For such problems, the expected value of the total energy, along the exact solution, drifts linearly with time. We present and analyze a time integrator having the same property for all times. Furthermore, strong and weak convergence of the numerical scheme along with efficient multilevel Monte Carlo estimators are studied. Finally, extensive numerical experiments illustrate the performance of the proposed numerical *** Codes 65C20. 65C30. 60H10. 60H35 Copyright © 2019, The Authors. All rights reserved.

关键词： Additive noise

来源：评论

学校读者我要写书评

暂无评论

${\sf DeepNC}$DeepNC: Deep Generative Network Completion

引用

IEEE Transactions on Pattern Analysis and Machine Intelligence 2020年第4期44卷 1837-1852页

作者： Cong Tran Won-Yong Shin Andreas Spitz Michael Gertz Department of Computer Science and Engineering Dankook University Yongin Republic of Korea Machine Intelligence & Data Science Laboratory Yonsei University Seoul Republic of Korea School of Mathematics and Computing (Computational Science and Engineering) Yonsei University Seoul Republic of Korea School of Computer and Communication Sciences École Polytechnique Fédérale de Lausanne Lausanne Switzerland Institute of Computer Science Heidelberg University Heidelberg Germany

Most network data are collected from partially observable networks with both missing nodes and missing edges, for example, due to limited resources and privacy settings specified by users on social media. Thus, it stands to reason that inferring the missing parts of the networks by performing network completion should precede downstream applications. However, despite this need, the recovery of missing nodes and edges in such incomplete networks is an insufficiently explored problem due to the modeling difficulty, which is much more challenging than link prediction that only infers missing edges. In this paper, we present DeepNC, a novel method for inferring the missing parts of a network based on a deep generative model of graphs. Specifically, our method first learns a likelihood over edges via an autoregressive generative model, and then identifies the graph that maximizes the learned likelihood conditioned on the observable graph topology. Moreover, we propose a computationally efficient ${\sf DeepNC}$ algorithm that consecutively finds individual nodes that maximize the probability in each node generation step, as well as an enhanced version using the expectation-maximization algorithm. The runtime complexities of both algorithms are shown to be almost linear in the number of nodes in the network. We empirically demonstrate the superiority of DeepNC over state-of-the-art network completion approaches.

关键词： Matrix decomposition Prediction algorithms Deep learning Pattern analysis Social networking (online) Predictive models

来源：评论

学校读者我要写书评

暂无评论

Meson spectroscopy in the Sp(4) gauge theory with three antisymmetric fermions

引用

Physical Review D 2025年第7期111卷 074511-074511页

作者： Ed Bennett Deog Ki Hong Ho Hsiao Jong-Wan Lee C.-J. David Lin Biagio Lucini Maurizio Piai Davide Vadacchino Swansea Academy of Advanced Computing Swansea University (Bay Campus) Fabian Way SA1 8EN Swansea Wales United Kingdom Department of Physics Pusan National University Busan 46241 Korea Extreme Physics Institute Pusan National University Busan 46241 Korea Center for Computational Sciences University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki 305-8577 Japan Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu 30010 Taiwan Particle Theory and Cosmology Group Center for Theoretical Physics of the Universe Institute for Basic Science (IBS) Daejeon 34126 Korea Centre for High Energy Physics Chung-Yuan Christian University Chung-Li 32023 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University (Bay Campus) Fabian Way SA1 8EN Swansea Wales United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park SA2 8PP Swansea Wales United Kingdom Centre for Mathematical Sciences University of Plymouth Plymouth PL4 8AA United Kingdom

We report the results of an extensive numerical study of the Sp(4) lattice gauge theory coupled to fermion matter content consisting of three (Dirac) flavors, transforming in the two-index antisymmetric representation of the gauge group. In the presence of (degenerate) fermion masses, the theory has an enhanced global SU(6) symmetry, broken explicitly and spontaneously to its SO(6) subgroup. This symmetry breaking pattern makes the theory interesting for applications in the context of composite Higgs models, as well as for the implementation of top partial compositeness. Alternatively, it can also provide a dynamical realization of the strongly interacting massive particle paradigm for the origin of dark matter. We adopt the standard plaquette gauge action, along with the Wilson-Dirac formulation for the fermions, and apply the (rational) hybrid Monte Carlo algorithm in our ensemble generation process. We monitor the autocorrelation and topology of the ensembles. We explore the bare parameter space, and identify the weak and strong coupling regimes, which are separated by a line of first-order bulk phase transitions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On the complexity of an augmented lagrangian method for nonconvex optimization

arXiv

引用

arXiv 2019年

作者： Grapiglia, Geovani N. Yuan, Ya-Xiang Departamento de Matemática Universidade Federal do Paraná Centro Politécnico Cx. postal 19.081 Paraná Curitiba81531-980 Brazil State Key Laboratory of Scientific/Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Zhong Guan Cun Donglu 55 Beijing100190 China

In this paper we study the worst-case complexity of an inexact Augmented Lagrangian method for nonconvex constrained problems. Assuming that the penalty parameters are bounded, we prove a complexity bound of O(| log(ǫ)|) outer iterations for the referred algorithm to generate an ǫ-approximate KKT point, for ǫ ∈ (0, 1). When the penalty parameters are unbounded, we prove an outer iteration complexity bound of O (ǫ−2/(α−1)), where α > 1 controls the rate of increase of the penalty parameters. For linearly constrained problems, these bounds yield to evaluation complexity bounds of O(| log(ǫ)|2ǫ−2) and O ( ǫ− ( 2(2+ α−1 α) +2 )), respectively, when appropriate first-order methods (p = 1) are used to approximately solve the unconstrained subproblems at each iteration. In the case of problems having only linear equality constraints, the latter bounds are improved to O(| log(ǫ)|2ǫ−(p+1)/p) and O ( ǫ− ( α−4 1 + p+1 p )), respectively, when appropriate p-order methods (p ≥ 2) are used as inner solvers. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

A Full Multigrid Method for Distributed Control Problems Constrained by Stokes Equations

引用

高等学校计算数学学报（英文版） 2017年第3期10卷 639-655页

作者： M.M.Butt Y.Yuan Institute of Computational Mathematics and Scientific/Engineering Computing Chinese Academy of Sciences Beijing 100080 China Institute of Computational Mathematics and Scientific/Engineering Computing Chinese Academy of SciencesBeijing 100080China and Higher Education Department Government of the PunjabLahore 54000Pakistan

A full multigrid method with coarsening by a factor-of-three to distributed control problems constrained by Stokes equations is *** optimal control problem with cost functional of velocity and/or pressure tracking-type is considered with Dirichlet boundary *** optimality system that results from a Lagrange multiplier framework,form a linear system connecting the state,adjoint,and control *** investigate multigrid methods with finite difference discretization on staggered grids.A coarsening by a factor-of-three is used on staggered grids that results nested hierarchy of staggered grids and simplified the inter-grid transfer operators.A distributive-Gauss-Seidel smoothing scheme is employed to update the stateand adjoint-variables and a gradient update step is used to update the control *** experiments are presented to demonstrate the effectiveness and efficiency of the proposed multigrid framework to tracking-type optimal control problems.

关键词： PDE-constrained optimization stokes equations multigrid staggered grids finite difference

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：