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Understanding the macroscopic behavior of dynamical systems is an important tool to unravel transport mechanisms in complex flows. A decomposition of the state space into coherent sets is a popular way to reveal this essential macroscopic…

Dynamical Systems · Mathematics 2020-04-30 Gary Froyland , Péter Koltai , Martin Stahn

Coherent sets are time-dependent regions in the physical space of nonautonomous flows that exhibit little mixing with their neighborhoods, robustly under small random perturbations of the flow. They thus characterize the global long-term…

Dynamical Systems · Mathematics 2024-03-29 Robin Chemnitz , Maximilian Engel , Péter Koltai

We study the transport properties of nonautonomous chaotic dynamical systems over a finite time duration. We are particularly interested in those regions that remain coherent and relatively non-dispersive over finite periods of time,…

Dynamical Systems · Mathematics 2015-05-19 Gary Froyland , Naratip Santitissadeekorn , Adam Monahan

Many stochastic differential equations in various applications like coupled neuronal oscillators are driven by time-periodic forces. In this paper, we extend several data-driven computational tools from autonomous Fokker-Planck equation to…

Numerical Analysis · Mathematics 2025-11-26 Yao Li , Jiatong Sun

We develop methods for detecting and predicting the evolution of coherent spatiotemporal patterns in incompressible time-dependent fluid flows driven by ergodic dynamical systems. Our approach is based on representations of the generators…

Dynamical Systems · Mathematics 2020-11-26 Dimitrios Giannakis , Suddhasattwa Das

A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo and Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stochastic…

Machine Learning · Computer Science 2025-10-10 Michael S. Albergo , Nicholas M. Boffi , Eric Vanden-Eijnden

We apply the method of flow equations to describe quantum systems subject to a time-periodic drive with a time-dependent envelope. The driven Hamiltonian is expressed in terms of its constituent Fourier harmonics with amplitudes that may…

Quantum Physics · Physics 2022-01-12 Viktor Novičenko , Giedrius Žlabys , Egidijus Anisimovas

We study enhancement of diffusive mixing by fast incompressible time-periodic flows. The class of relaxation-enhancing flows that are especially efficient in speeding up mixing has been introduced in [2]. The relaxation-enhancing property…

Analysis of PDEs · Mathematics 2007-07-02 Alexander Kiselev , Roman Shterenberg , Andrej Zlatos

The long-term distributions of trajectories of a flow are described by invariant densities, i.e. fixed points of an associated transfer operator. In addition, global slowly mixing structures, such as almost-invariant sets, which partition…

Numerical Analysis · Mathematics 2015-03-17 Gary Froyland , Oliver Junge , Péter Koltai

We present a theoretical method to generate a highly accurate {\em time-independent} Hamiltonian governing the finite-time behavior of a time-periodic system. The method exploits infinitesimal unitary transformation steps, from which…

Statistical Mechanics · Physics 2019-05-30 Michael Vogl , Pontus Laurell , Aaron D. Barr , Gregory A. Fiete

We study the large-time behavior of a class of periodically driven macroscopic systems. We find, for a certain range of the parameters of either the system or the driving fields, the time-averaged asymptotic behavior effectively is that of…

Statistical Mechanics · Physics 2009-11-10 Sreedhar B. Dutta

Using stochastic thermodynamics, the properties of interacting linear chains subject to periodic drivings are investigated. The systems are described by Fokker-Planck-Kramers equation and exact (explicit) solutions are obtained for periodic…

Statistical Mechanics · Physics 2020-02-05 Bruno A. N. Akasaki , M. J. de Oliveira , Carlos E. Fiore

We study the time-averaged flow in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but the graph remains finite, the large-deviation rate…

Statistical Mechanics · Physics 2020-12-02 Davide Gabrielli , D. R. Michiel Renger

We establish the theoretical framework for adjoint-based phase reduction analysis for incompressible periodic flows. Through this adjoint-based method, we obtain spatiotemporal phase sensitivity fields through a single pair of forward and…

Fluid Dynamics · Physics 2022-10-11 Yoji Kawamura , Vedasri Godavarthi , Kunihiko Taira

We demonstrate that the counting statistics of currents in periodically driven ergodic stochastic systems can show sharp changes of some of its properties in response to continuous changes of the driving protocol. To describe this effect,…

Statistical Mechanics · Physics 2015-05-18 V. Y. Chernyak , N. A. Sinitsyn

Strongly nonlinear flows, which commonly arise in geophysical and engineering turbulence, are characterized by persistent and intermittent energy transfer between various spatial and temporal scales. These systems are difficult to model and…

Dynamical Systems · Mathematics 2022-01-25 Hassan Arbabi , Themistoklis Sapsis

A partially hinged, partially free rectangular plate is considered, with the aim to address the possible unstable end behaviors of a suspension bridge subject to wind. This leads to a nonlinear plate evolution equation with a nonlocal…

Analysis of PDEs · Mathematics 2020-07-06 Denis Bonheure , Filippo Gazzola , Irena Lasiecka , Justin T. Webster

Time-dependently driven stochastic systems form a vast and manifold class of non-equilibrium systems used to model important applications on small length scales such as bit erasure protocols or microscopic heat engines. One property that…

Statistical Mechanics · Physics 2022-04-07 Julius Degünther , Timur Koyuk , Udo Seifert

We study the dynamical properties of a broad class of high-dimensional random dynamical systems exhibiting chaotic as well as fixed point and periodic attractors. We consider cases in which attractors can co-exists in some regions of the…

Disordered Systems and Neural Networks · Physics 2026-03-02 Samantha J. Fournier , Pierfrancesco Urbani

A phase proper orthogonal decomposition (Phase POD) method is demonstrated, utilizing phase averaging for the decomposition of spatio-temporal behaviour of statistically non-stationary turbulent flows in an optimized manner. The proposed…

Fluid Dynamics · Physics 2024-03-01 Yisheng Zhang , Azur Hodzic , Fabien Evrard , Berend Van Wachem , Clara M. Velte
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