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We analyse the nonlinear Kuramoto-Sivashinsky equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately…

Numerical Analysis · Mathematics 2025-10-20 T. MacKenzie , A. J. Roberts

I analyse a generalised Burger's equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately models the…

chao-dyn · Physics 2007-05-23 A. J. Roberts

Modern dynamical systems theory has previously had little to say about finite difference and finite element approximations of partial differential equations (Archilla, 1998). However, recently I have shown one way that centre manifold…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

Developments in dynamical systems theory provides new support for the discretisation of \pde{}s and other microscale systems. By systematically resolving subgrid microscale dynamics the new approach constructs asymptotically accurate,…

Numerical Analysis · Mathematics 2009-04-07 Tony MacKenzie , A. J. Roberts

The long term aim is to use modern dynamical systems theory to derive discretisations of noisy, dissipative partial differential equations. As a first step we here consider a small domain and apply stochastic centre manifold techniques to…

Dynamical Systems · Mathematics 2025-10-20 A. J. Roberts

Constructing discrete models of stochastic partial differential equations is very delicate. Stochastic centre manifold theory provides novel support for coarse grained, macroscale, spatial discretisations of nonlinear stochastic partial…

Dynamical Systems · Mathematics 2010-03-09 A. J. Roberts

I introduce an innovative methodology for deriving numerical models of systems of partial differential equations which exhibit the evolution of spatial patterns. The new approach directly produces a discretisation for the evolution of the…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

I prove that a centre manifold approach to creating finite difference models will consistently model linear dynamics as the grid spacing becomes small. Using such tools of dynamical systems theory gives new assurances about the quality of…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

We present a new topological method for the study of the dynamics of dissipative PDE's. The method is based on the concept of the self-consistent apriori bounds, which allows to justify rigorously the Galerkin projection. As a result we…

Analysis of PDEs · Mathematics 2025-10-20 P. Zgliczynski , K. Mischaikow

Coarse grained, macroscale, spatial discretisations of nonlinear nonautonomous partial differential\difference equations are given novel support by centre manifold theory. Dividing the physical domain into overlapping macroscale elements…

Dynamical Systems · Mathematics 2013-12-31 J. E. Bunder , A. J. Roberts

The problem of controlling and stabilising solutions to the Kuramoto-Sivashinsky equation is studied in this paper. We consider a generalised form of the equation in which the effects of an electric field and dispersion are included. Both…

Optimization and Control · Mathematics 2015-05-25 Susana N. Gomes , Demetrios T. Papageorgiou , Grigorios A. Pavliotis

We investigate a fully discrete finite element approximation for the stochastic Kuramoto-Sivashinsky equation, combining the standard finite element methods in spatial discretization with the implicit Euler-Maruyama scheme in time. Rigorous…

Numerical Analysis · Mathematics 2025-10-08 Hung D. Nguyen , Liet Vo

Simulations of chaotic systems can only produce high-fidelity trajectories if the initial and boundary conditions are well specified. When these conditions are unknown but measurements are available, variational state estimation can…

Dynamical Systems · Mathematics 2026-05-29 Noah B. Frank , Joshua L. Pughe-Sanford , Samuel J. Grauer

We present a novel control methodology to control the roughening processes of semilinear parabolic stochastic partial differential equations in one dimension, which we exemplify with the stochastic Kuramoto-Sivashinsky equation. The…

The problem of constructing data-based, predictive, reduced models for the Kuramoto-Sivashinsky equation is considered, under circumstances where one has observation data only for a small subset of the dynamical variables. Accurate…

Numerical Analysis · Mathematics 2016-08-11 Fei Lu , Kevin Lin , Alexandre J. Chorin

We develop a Melnikov framework for the Kuramoto Sivashinsky (KS) equation under weak deterministic and stochastic forcing. By treating KS as an infinite dimensional dynamical system, we derive a Melnikov functional that measures splitting…

Dynamical Systems · Mathematics 2026-04-16 Sumita Datta

We report numerical simulations of one-dimensional cellular solutions of the stabilized Kuramoto-Sivashinsky equation. This equation offers a range of generic behavior in pattern-forming instabilities of moving interfaces, such as a host of…

Pattern Formation and Solitons · Physics 2009-11-13 P. Brunet

The discretization approximation method commonly used to simulate the dynamics of quantum system coupled to the environment in continuum often suffers from the periodically partial recovery of initial state because of the effect of finite…

Quantum Physics · Physics 2025-05-07 H. T. Cui , Y. A. Yan , M. Qin , X. X. Yi

The continuous and discrete symmetries of the Kuramoto-Sivashinsky system restricted to a spatially periodic domain play a prominent role in shaping the invariant sets of its chaotic dynamics. The continuous spatial translation symmetry…

Chaotic Dynamics · Physics 2010-04-06 Predrag Cvitanović , Ruslan L. Davidchack , Evangelos Siminos

Constructing numerical models of noisy partial differential equations is very delicate. Our long term aim is to use modern dynamical systems theory to derive discretisations of dissipative stochastic partial differential equations. As a…

Dynamical Systems · Mathematics 2007-05-23 A. J. Roberts
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