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A simple and general formalism for mode coupling by a spatial, temporal or spatiotemporal perturbation in dispersive materials is developed. This formalism can be used for studying various linear and non-linear optical interactions…

Optics · Physics 2015-06-19 Brenda Dana , Lilya Lobachinsky , Alon Bahabad

Studies of the phase diagram of the coupled sine circle map lattice have identified the presence of two distinct universality classes of spatiotemporal intermittency viz. spatiotemporal intermittency of the directed percolation class with a…

Chaotic Dynamics · Physics 2012-09-14 Zahera Jabeen , Neelima Gupte

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically…

Cell Behavior · Quantitative Biology 2016-11-23 Adriano Bonforti , Salva Duran-Nebreda , Raul Montañez , Ricard Solé

Interacting populations often create complicated spatiotemporal behavior, and understanding it is a basic problem in the dynamics of spatial systems. We study the two-species case by simulations of a host--parasitoid model. In the case of…

Populations and Evolution · Quantitative Biology 2009-01-16 Matti Peltomaki , Martin Rost , Mikko Alava

The ordinal patterns of a fixed number of consecutive values in a time series is the spatial ordering of these values. Counting how often a specific ordinal pattern occurs in a time series provides important insights into the properties of…

Statistics Theory · Mathematics 2025-02-06 Annika Betken , Giorgio Micali , Johannes Schmidt-Hieber

We establish the existence of spatially localised one-dimensional free surfaces of a ferrofluid near onset of the Rosensweig instability, assuming a general (nonlinear) magnetisation law. It is shown that the ferrohydrostatic equations can…

Analysis of PDEs · Mathematics 2018-02-26 Mark D. Groves , David J. B. Lloyd , Athanasios Stylianou

Encounter-based models of diffusion provide a probabilistic framework for analyzing the effects of a partially absorbing reactive surface, in which the probability of absorption depends upon the amount of surface-particle contact time.…

Statistical Mechanics · Physics 2023-07-05 Paul C Bressloff

A discontinuous area-preserving mapping derived from a sinusoidally-forced impacting system is studied. This system, the elastic impact oscillator, is very closely related to the accelerator models of particle physics such as the Fermi map.…

chao-dyn · Physics 2008-02-03 Harbir Lamba

We present a theoretical framework for electromagnetic scattering by particles with a permittivity that is periodically varying in time, based on a perturbative approach. Within this framework, we derive explicit expressions for the…

We study an abstracted model of neuronal activity via numerical simulation, and report spatiotemporal pattern formation and critical like dynamics. A population of pulse coupled, discretised, relaxation oscillators is simulated over…

Neurons and Cognition · Quantitative Biology 2019-04-24 Dionysios Georgiadis , Didier Sornette

Correlated fluctuations in the activity of neural populations reflect the network's dynamics and connectivity. The temporal and spatial dimensions of neural correlations are interdependent. However, prior theoretical work mainly analyzed…

Neurons and Cognition · Quantitative Biology 2022-07-19 Yan-Liang Shi , Roxana Zeraati , Anna Levina , Tatiana A. Engel

Spontaneous pattern formation from a uniform state is a widely studied nonlinear optical phenomenon that shares similarities with non-equilibrium pattern formation in other scientific domains. Here we show how a single layer of atoms in an…

Optics · Physics 2023-12-22 C. D. Parmee , J. Ruostekoski

We consider a diffusion process with coefficients that are periodic outside of an "interface region" of finite thickness. The question investigated in this article is the limiting long time/large scale behavior of such a process under…

Probability · Mathematics 2011-04-20 Martin Hairer , Charles Manson

An instantaneous time mirror (ITM) is an interesting approach to manipulate wave propagation from the time boundaries. In the time domain, the reversed wave is previously proven to be the temporal derivative of the original pattern. Here,…

Classical Physics · Physics 2020-08-19 Danming Peng , Yiyang Fan , Ruochen Liu , Xiasheng Guo , Sihui Wang

As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming more aware of the relevance of their work to help tackle…

Machine Learning · Statistics 2020-12-23 Federico Amato , Fabian Guignard , Sylvain Robert , Mikhail Kanevski

The processes in nonequilibrium dissipative media caused by coherent structure formation and lead to the complicated dynamics are of interest for nonlinear physics. Here we consider a model of the flow of interacting electronics patterns.…

chao-dyn · Physics 2008-02-03 E. S. Mchedlova , D. I. Trubetskov

Spatio-temporal forecasting is challenging attributing to the high nonlinearity in temporal dynamics as well as complex location-characterized patterns in spatial domains, especially in fields like weather forecasting. Graph convolutions…

Machine Learning · Computer Science 2021-12-14 Haitao Lin , Zhangyang Gao , Yongjie Xu , Lirong Wu , Ling Li , Stan. Z. Li

A diffusive epidemic model with an infection-dependent recovery rate is formulated in this paper. Multiple constant steady states and spatially homogeneous periodic solutions are first proven by bifurcation analysis of the reaction…

Dynamical Systems · Mathematics 2025-09-12 Wael El Khateeb , Chanaka Kottegoda , Chunhua Shan

Exotic forms of wave control have been emerging by engineering matter in space and time. In this framework, temporal photonic interfaces, i.e., abrupt changes in the electromagnetic properties of a material, have been shown to induce…

We propose an interdisciplinary framework that combines Bayesian predictive inference, a well-established tool in Machine Learning, with Formal Methods rooted in the computer science community. Bayesian predictive inference allows for…

Computation · Statistics 2025-08-21 Laura Vana , Ennio Visconti , Laura Nenzi , Annalisa Cadonna , Gregor Kastner
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