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This article deals with invariant manifolds for infinite dimensional random dynamical systems with different time scales. Such a random system is generated by a coupled system of fast-slow stochastic evolutionary equations. Under suitable…

Probability · Mathematics 2013-07-29 Hongbo Fu , Xianming Liu , Jinqiao Duan

We introduce a nonlinear stochastic model reduction technique for high-dimensional stochastic dynamical systems that have a low-dimensional invariant effective manifold with slow dynamics, and high-dimensional, large fast modes. Given only…

Machine Learning · Statistics 2023-10-25 Felix X. -F. Ye , Sichen Yang , Mauro Maggioni

In this paper, we introduce a fictitious dynamics for describing the only fast relaxation of a stiff ordinary differential equation (ODE) system towards a stable low-dimensional invariant manifold in the phase-space (slow invariant manifold…

Statistical Mechanics · Physics 2025-10-01 Eliodoro Chiavazzo

We construct stable manifolds for a class of degenerate evolution equations including the steady Boltzmann equation, establishing in the process exponential decay of associated kinetic shock and boundary layers to their limiting equilibrium…

Dynamical Systems · Mathematics 2016-12-21 Alin Pogan , Kevin Zumbrun

Invariant manifolds facilitate the understanding of nonlinear stochastic dynamics. When an invariant manifold is represented approximately by a graph for example, the whole stochastic dynamical system may be reduced or restricted to this…

Dynamical Systems · Mathematics 2007-05-23 Aijun Du , Jinqiao Duan

Chemical reactions modeled by ordinary differential equations are finite-dimensional dissipative dynamical systems with multiple time-scales. They are numerically hard to tackle -- especially when they enter an optimal control problem as…

Optimization and Control · Mathematics 2017-03-27 Marcus Heitel , Dirk Lebiedz

In this paper, we are concerned with studying the existence of invariant complex manifolds of two-dimensional holomorphic systems. From the geometric singular perturbation theory we know that if a slow-fast system has associated a normally…

Dynamical Systems · Mathematics 2023-04-04 Gabriel Rondón , Paulo R. da Silva , Luiz F. S. Gouveia

Koopman analysis can be used to understand the dynamics of a nonlinear dynamical system in terms a linear, but generally infinite dimensional operator. The isostable coordinate system focuses on the slowest decaying principal Koopman…

Dynamical Systems · Mathematics 2025-07-21 Dan Wilson

Many real-analytic flows, e.g. in chemical kinetics, share a multiple time scale spectral structure. The trajectories of the corresponding dynamical systems are observed to bundle near so-called slow invariant manifolds (SIMs), which are…

Dynamical Systems · Mathematics 2019-12-04 Jörn Dietrich , Dirk Lebiedz

During this last decades, several attempts to construct slow invariant manifold of the Lorenz-Krishnamurthy five-mode model of slow-fast interactions in the atmosphere have been made by various authors. Unfortunately, as in the case of many…

Dynamical Systems · Mathematics 2018-08-27 Jean-Marc Ginoux

We point out a new view on slow invariant manifolds (SIM) in dynamical systems which departs from a purely geometric covariant characterization implying coordinate independency. The fundamental idea is to treat the SIM as a well-defined…

Dynamical Systems · Mathematics 2017-04-03 Dirk Lebiedz

The theory of slow manifolds is an important tool in the study of deterministic dynamical systems, giving a practical method by which to reduce the number of relevant degrees of freedom in a model, thereby often resulting in a considerable…

Statistical Mechanics · Physics 2013-07-01 George W A Constable , Alan J McKane , Tim Rogers

Slow-fast dynamical systems have two time scales and an explicit parameter representing the ratio of these time scales. Locally invariant slow manifolds along which motion occurs on the slow time scale are a prominent feature of slow-fast…

Dynamical Systems · Mathematics 2012-09-20 John Guckenheimer , Tomas Johnson , Philipp Meerkamp

Techniques are developed for decoupling dissipative differential equations. The approach considered is based upon obtaining a sufficient gap in the time dependent linear portion of the equation that corresponds to the linear variational…

Numerical Analysis · Mathematics 2015-12-01 Yu-Min Chung , Andrew J. Steyer , Erik S. Van Vleck

This paper investigates model-order reduction methods for geometrically nonlinear structures. The parametrisation method of invariant manifolds is used and adapted to the case of mechanical systems expressed in the physical basis, so that…

Numerical Analysis · Mathematics 2021-09-22 Alessandra Vizzaccaro , Andrea Opreni , Loïc Salles , Attilio Frangi , Cyril Touzé

We develop a model reduction technique for non-smooth dynamical systems using spectral submanifolds. Specifically, we construct low-dimensional, sparse, nonlinear and non-smooth models on unions of slow and attracting spectral submanifolds…

Dynamical Systems · Mathematics 2023-12-25 Leonardo Bettini , Mattia Cenedese , George Haller

The Method of Invariant Grid (MIG) is a model reduction technique based on the concept of slow invariant manifold (SIM), which approximates the SIM by a set of nodes in the concentration space (invariant grid). In the present work, the MIG…

Statistical Mechanics · Physics 2007-12-17 E. Chiavazzo , I. V. Karlin , C. E. Frouzakis , K. B. Boulouchos

In Hamiltonian systems subjected to periodic perturbations the stable and unstable manifolds of the unstable periodic orbits provide the dynamical "skeleton" that drives the mixing process and bounds the chaotic regions of the phase space.…

Plasma Physics · Physics 2016-10-05 David Ciro Taborda , Todd Edwin Evans , Iberê Luiz Caldas

In this paper, we investigate the speed of convergence and higher-order asymptotics of solutions to the porous medium equation posed in $\mathbf{R}^N$. Applying a nonlinear change of variables, we rewrite the equation as a diffusion on a…

Analysis of PDEs · Mathematics 2015-05-26 Christian Seis

Invariance and stability are essential notions in dynamical systems study, and thus it is of great interest to learn a dynamics model with a stable invariant set. However, existing methods can only handle the stability of an equilibrium. In…

Machine Learning · Computer Science 2021-06-08 Naoya Takeishi , Yoshinobu Kawahara