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相关论文: One-scale Model for Domain Wall Network Evolution

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It has recently been discovered that many biological systems, when represented as graphs, exhibit a scale-free topology. One such system is the set of structural relationships among protein domains. The scale-free nature of this and other…

种群与进化 · 定量生物学 2009-11-10 Eric J. Deeds , Eugene I. Shakhnovich

Recent experimental and computational studies indicate that near wall turbulent flows can be characterized by universal small scale autonomous dynamics that are modulated by large scale structures. We formulate numerical simulations of near…

流体动力学 · 物理学 2021-01-21 Sean P. Carney , Björn Engquist , Robert D. Moser

Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of…

数学物理 · 物理学 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the…

社会与信息网络 · 计算机科学 2026-04-02 Yichao Yao , Minyu Feng , Matjaž Perc , Jürgen Kurths

The concept of Schramm-Loewner evolution provides a unified description of domain boundaries of many lattice spin systems in two dimensions, possibly even including systems with quenched disorder. Here, we study domain walls in the…

统计力学 · 物理学 2015-03-17 Jacob D. Stevenson , Martin Weigel

In an increasingly connected world, the resilience of networked dynamical systems is important in the fields of ecology, economics, critical infrastructures, and organizational behaviour. Whilst we understand small-scale resilience well,…

适应与自组织系统 · 物理学 2018-08-21 Giannis Moutsinas , Weisi Guo

The abundance of models of complex networks and the current insufficient validation standards make it difficult to judge which models are strongly supported by data and which are not. We focus here on likelihood maximization methods for…

物理与社会 · 物理学 2014-03-26 Matus Medo

Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information…

无序系统与神经网络 · 物理学 2016-08-31 Albert-Laszlo Barabasi , Reka Albert , Hawoong Jeong

We revisit previously developed analytic models for defect evolution and adapt them appropriately for the study of semilocal string networks. We thus confirm the expectation (based on numerical simulations) that linear scaling evolution is…

高能物理 - 唯象学 · 物理学 2011-10-11 A. S. Nunes , A. Avgoustidis , C. J. A. P. Martins , J. Urrestilla

We study the kinetic roughening of a driven domain wall between spin-up and spin-down domains for a model with non-conserved order parameter and quenched disorder. To understand the scaling behavior of this interface we construct an…

无序系统与神经网络 · 物理学 2008-02-03 M. Jost , K. D. Usadel

A model for growing networks is introduced, having as a main ingredient that new nodes are attached to the network through one existing node and then explore the network through the links of the visited nodes. From exact calculations of two…

统计力学 · 物理学 2007-05-23 Alexei Vazquez

We use the Velocity-dependent One Scale Model for topological defect evolution to explore and classify the possible scaling solutions for string networks with time-varying tension, in cosmological and non-cosmological settings and under two…

高能物理 - 唯象学 · 物理学 2026-02-24 C. S. C. M. Coelho , A. -L. Y. Gschrey , C. J. A. P. Martins

Domain wall - type solution with oscillating thickness in a real, scalar field model is investigated with the help of a polynomial approximation. We propose a simple extension of the polynomial approximation method. In this approach we…

高能物理 - 理论 · 物理学 2007-05-23 Maciej Slusarczyk

We consider domain walls embedded in curved backgrounds as an approximation for braneworld scenarios. We give a large class of new exact solutions, exhausting the possibilities for describing one and two walls for the cases where the…

高能物理 - 理论 · 物理学 2016-08-25 Nemanja Kaloper

The structure of real-world networks is usually difficult to characterize owing to the variation of topological scales, the nondyadic complex interactions, and the fluctuations in the network. We aim to address these problems by introducing…

社会与信息网络 · 计算机科学 2019-09-25 Quoc Hoan Tran , Van Tuan Vo , Yoshihiko Hasegawa

We revisit the velocity-dependent one-scale model for topological defect evolution, and present a new alternative formulation in terms of a physical (rather than invariant) characteristic length scale. While the two approaches are…

高能物理 - 唯象学 · 物理学 2016-03-09 C. J. A. P. Martins , M. M. P. V. P. Cabral

We investigated domain wall networks as a possible candidate to explain the present accelerated expansion of the universe. We discuss various requirements that any stable lattice of frustrated walls must obey and propose a class of `ideal'…

高能物理 - 唯象学 · 物理学 2008-08-26 J. Menezes

Our main interest is the evolution of domain walls of the Higgs field in the early Universe. The aim of this paper is to understand how dynamics of Higgs domain walls could be influenced by yet unknown interactions from beyond the Standard…

高能物理 - 唯象学 · 物理学 2018-05-16 Tomasz Krajewski , Zygmunt Lalak , Marek Lewicki , Paweł Olszewski

To quantify the fundamental evolution of time-varying networks, and detect abnormal behavior, one needs a notion of temporal difference that captures significant organizational changes between two successive instants. In this work, we…

社会与信息网络 · 计算机科学 2017-08-17 Nathan D Monnig , Francois G Meyer

The process of collision of two parallel domain walls in a supersymmetric model is studied both in effective Lagrangian approximation and by numerical solving of the exact classical field problem. For small initial velocities we find that…

高能物理 - 理论 · 物理学 2017-01-04 V. A. Gani , A. E. Kudryavtsev