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Several mechanisms have been proposed to explain the spontaneous generation of self-organized patterns, hypothesised to play a role in the formation of many of the magnificent patterns observed in Nature. In several cases of interest, the…

斑图形成与孤子 · 物理学 2025-10-22 Riccardo Muolo , Malbor Asllani , Duccio Fanelli , Philip K. Maini , Timoteo Carletti

Turing instability in activator-inhibitor systems provides a paradigm of nonequilibrium pattern formation; it has been extensively investigated for biological and chemical processes. Turing pattern formation should furthermore be possible…

适应与自组织系统 · 物理学 2010-05-13 Hiroya Nakao , Alexander S. Mikhailov

We extend the mechanism for noise-induced phase transitions proposed by Ibanes et al. [Phys. Rev. Lett. 87, 020601-1 (2001)] to pattern formation phenomena. In contrast with known mechanisms for pure noise-induced pattern formation, this…

统计力学 · 物理学 2009-11-07 J. Buceta , M. Ibanes , J. M. Sancho , Katja Lindenberg

We have studied sidebranching induced by fluctuations in dendritic growth. The amplitude of sidebranching induced by internal (equilibrium) concentration fluctuations in the case of solidification with solutal diffusion is computed. This…

斑图形成与孤子 · 物理学 2009-11-07 R. Gonzalez-Cinca , L. Ramirez-Piscina , J. Casademunt , A. Hernandez-Machado

A stochastic model of excitatory and inhibitory interactions which bears universality traits is introduced and studied. The endogenous component of noise, stemming from finite size corrections, drives robust inter-nodes correlations, that…

无序系统与神经网络 · 物理学 2017-08-16 Clement Zankoc , Duccio Fanelli , Francesco Ginelli , Roberto Livi

The theory of transient growth describes how linear mechanisms can cause temporary amplification of disturbances even when the linearized system is asymptotically stable as defined by its eigenvalues. This growth is traditionally quantified…

流体动力学 · 物理学 2023-02-23 Peter Frame , Aaron Towne

Many cellular patterns exhibit a reaction-diffusion component, suggesting that Turing instability may contribute to pattern formation. However, biological gene-regulatory pathways are more complex than simple Turing activator-inhibitor…

分子网络 · 定量生物学 2024-12-05 Hazlam S. Ahmad Shaberi , Aibek Kappassov , Antonio Matas-Gil , Robert G. Endres

Dynamics of a system that performs a large fluctuation to a given state is essentially deterministic: the distribution of fluctuational paths peaks sharply at a certain optimal path along which the system is most likely to move. For the…

统计力学 · 物理学 2008-03-03 M. I. Dykman , V. N. Smelyanskiy

The properties of the fluctuations large enough to induce bifurcations at open chemical systems at steady constraints are studied. The fluctuations that come from the diffusion-induced noise are considered. It is a generic for the surface…

统计力学 · 物理学 2007-05-23 Maria K. Koleva , L. A. Petrov

We demonstrate that demographic noise can induce persistent spatial pattern formation and temporal oscillations in the Levin-Segel predator-prey model for plankton-herbivore population dynamics. Although the model exhibits a Turing…

种群与进化 · 定量生物学 2015-05-13 Thomas Butler , Nigel Goldenfeld

The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is…

生物物理 · 物理学 2025-12-02 Antonio Matas-Gil , Robert G. Endres

The large scale fluctuations of the ordered state in active matter systems are usually characterised by studying the "giant number fluctuations" of particles in any finite volume, as compared to the expectations from the central limit…

软凝聚态物质 · 物理学 2018-05-25 Supravat Dey , Dibyendu Das , R. Rajesh

In this work we investigate the effect of density dependent nonlinear diffusion on pattern formation in the Brusselator system. Through linear stability analysis of the basic solution we determine the Turing and the oscillatory instability…

数学物理 · 物理学 2015-06-17 G. Gambino , M. C. Lombardo , M. Sammartino , V. Sciacca

We propose a new non-equilibrium model for spatial pattern formation on the basis of local information transfer. Unlike standard models of pattern formation it is not based on the Turing instability. Information is transmitted through the…

统计力学 · 物理学 2007-05-23 Thimo Rohlf , Stefan Bornholdt

Collective dynamics result from interactions among noisy dynamical components. Examples include heartbeats, circadian rhythms, and various pattern formations. Because of noise in each component, collective dynamics inevitably involve…

生物物理 · 物理学 2010-09-09 Naoki Masuda , Yoji Kawamura , Hiroshi Kori

The influence that intrinsic local density fluctuations can have on solutions of mean-field reaction-diffusion models is investigated numerically by means of the spatial patterns arising from two species that react and diffuse in the…

其他凝聚态物理 · 物理学 2007-05-23 D. Hochberg , M. -P. Zorzano , F. Moran

Magnetic fields in several astrophysical objects are amplified and maintained by a dynamo mechanism, which is the conversion of the turbulent kinetic energy to magnetic energy. A dynamo that amplifies magnetic fields at scales $<$ the…

星系天体物理 · 物理学 2021-09-27 Amit Seta , Christoph Federrath

Many approaches to modelling reaction-diffusion systems with anomalous transport rely on deterministic equations and ignore fluctuations arising due to finite particle numbers. Starting from an individual-based model we use a…

统计力学 · 物理学 2019-05-29 Joseph W. Baron , Tobias Galla

Introduction of optical gain to a disordered system results in enhanced fluctuations [$F_{(2)}=var(\tilde{g})/< \tilde{g} >^2$] of dimensionless conductance $\tilde{g}$, similar to the effect of Anderson localization in passive medium.…

介观与纳米尺度物理 · 物理学 2009-11-11 Alexey Yamilov , Hui Cao

Effect of noise in inducing order on various chaotically evolving systems is reviewed, with special emphasis on systems consisting of coupled chaotic elements. In many situations it is observed that the uncoupled elements when driven by…

chao-dyn · 物理学 2015-06-24 Manojit Roy , R. E. Amritkar