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Related papers: Dynamics of Influence on Hierarchical Structures

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Dendrites with developed sidebranches are numerically studied with a coupled map lattice model. The competitive dynamics among sidebranches determines the shape of the envelope. The envelope has a parabolic shape near the tip of the…

Pattern Formation and Solitons · Physics 2009-11-10 H. Sakaguchi , M. Ohtaki

A numerical simulation using the chaotic Dynamics of intermittency at a finite size Z(3) spin system in a 3D lattice reveals: (a) the existence of a second order phase transition with a zone hysteresis characterized from resonances…

Chaotic Dynamics · Physics 2026-03-11 Yiannis F. Contoyiannis

Understanding what and how causal dynamical mechanisms generate collective phenomena is a central challenge in complexity science. Recent studies have focused on identifying the mechanisms underlying the synergistic interdependencies that…

Physics and Society · Physics 2026-04-14 Enrico Caprioglio , Luc Berthouze

We study expanding circle maps interacting in a heterogeneous random network. Heterogeneity means that some nodes in the network are massively connected, while the remaining nodes are only poorly connected. We provide a probabilistic…

Dynamical Systems · Mathematics 2013-08-27 Tiago Pereira , Sebastian van Strien , Jeroen S. W. Lamb

Spin ensembles play a pivotal role in various quantum applications such as metrology and simulating many-body physics. Recent research has proposed utilizing spin cat states to encode logical quantum information, with logical lifetimes…

Quantum Physics · Physics 2025-04-10 Wai-Keong Mok , Leong-Chuan Kwek , Steven Touzard

Social hierarchy is central to decision-making in the coordinated movement of many swarming species. Here we propose a hierarchical swarm model in the spirit of the Vicsek model of self-propelled particles. We show that, as the hierarchy…

Biological Physics · Physics 2020-10-28 Tingting Xue , Xu Li , Peter Grassberger , Li Chen

Many phenomena in real world social networks are interpreted as spread of influence between activated and non-activated network elements. These phenomena are formulated by combinatorial graphs, where vertices represent the elements and…

Discrete Mathematics · Computer Science 2024-03-01 Siavash Askari , Manouchehr Zaker

This article starts by introducing a new theoretical framework to model spatial systems which is obtained from the framework of interacting particle systems by replacing the traditional graphical structure that defines the network of…

Probability · Mathematics 2015-06-12 Nicolas Lanchier , Jared Neufer

We use lattice Boltzmann simulations to study the effect of shear on the phase ordering of a two-dimensional binary fluid. The shear is imposed by generalising the lattice Boltzmann algorithm to include Lees-Edwards boundary conditions. We…

Soft Condensed Matter · Physics 2009-10-31 A. J. Wagner , J. M. Yeomans

Recently, some studies started to unveil the wealthy of interactions that occur between groups of nodes when looking at the small scale of interactions taking place in complex networks. Such findings claim for a new systematic methodology…

Physics and Society · Physics 2016-07-26 Cesar H. Comin , João B. Bunoro , Matheus P. Viana , Luciano da F. Costa

Frustration refers to the inability to satisfy competing interactions simultaneously, often leading to a large number of degenerate ground states. This can suppress ordering tendencies, sometimes resulting in a spin liquid phase. An…

Strongly Correlated Electrons · Physics 2014-07-30 Stefan Buhrandt , Lars Fritz

The magnetic properties of a system of coexisting localized spins and conduction electrons are investigated within an extended version of the one dimensional Kondo lattice model in which effects stemming from the electron-lattice and…

Strongly Correlated Electrons · Physics 2009-11-10 M. Gulacsi , A. Bussmann-Holder , A. R. Bishop

Entangled spin squeezed states generated via dipolar interactions in lattice models provide unique opportunities for quantum enhanced sensing and are now within reach of current experiments. A critical question in this context is which…

Quantum Physics · Physics 2024-02-27 David Wellnitz , Mikhail Mamaev , Thomas Bilitewski , Ana Maria Rey

Recent studies of networks representing complex systems from the brain to social graphs have revealed their higher-order architecture, which can be described by aggregates of simplexes (triangles, tetrahedrons, and higher cliques). Current…

Soft Condensed Matter · Physics 2026-03-11 Bosiljka Tadic , Neelima Gupte

Phase transitions in one-dimensional lattice systems are well established and have been extensively studied within both Hermitian and non-Hermitian frameworks. In this work, we extend this understanding to a more general setting by…

Disordered Systems and Neural Networks · Physics 2025-11-25 S Rahul , A Harshitha

Spin lattice models play central role in the studies of quantum magnetism and non-equilibrium dynamics of spin excitations -- magnons. We show that a spin lattice with strong nearest-neighbor interactions and tunable long-range hopping of…

Atomic Physics · Physics 2018-04-25 Fabian Letscher , David Petrosyan

A language dynamics model on a square lattice, which is an extension of the one popularized by Abrams and Strogatz [1], is analyzed using ODE bifurcation theory. For this model we are interested in the existence and spectral stability of…

Pattern Formation and Solitons · Physics 2021-02-16 T. Kapitula , P. G. Kevrekidis

A key issue in complex systems regards the relationship between topology and dynamics. In this work, we use a recently introduced network property known as steering coefficient as a means to approach this issue with respect to different…

Physics and Society · Physics 2017-11-27 Paulo J. P. de Souza , Cesar H. Comin , Luciano da F. Costa

We study the dynamical low temperature behaviour of the Ising spin glass on the Bethe lattice. Starting from Glauber dynamics we propose a cavity like Ansatz that allows for the treatment of the slow (low temperature) part of dynamics.…

Disordered Systems and Neural Networks · Physics 2009-11-13 Martin Kiemes , Heinz Horner

We present a systematic and reliable methodology, termed hierarchical mean-field theory (HMFT), to study and predict the behavior of strongly coupled many-particle systems. HMFT is a simple approximation, based upon group theoretical…

Strongly Correlated Electrons · Physics 2007-05-23 Gerardo Ortiz , Cristian D. Batista