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Transferring a physical system from an initial to a final state while minimizing energetic losses is an interdisciplinary control problem that bridges stochastic thermodynamics and optimal transport theory. Recent research typically…

Statistical Mechanics · Physics 2026-02-23 Jann van der Meer , Andreas Dechant

This paper considers the problem of designing a continuous-time dynamical system that solves a constrained nonlinear optimization problem and makes the feasible set forward invariant and asymptotically stable. The invariance of the feasible…

Optimization and Control · Mathematics 2024-08-27 Ahmed Allibhoy , Jorge Cortés

Topological constraints play a key role in the self-organizing processes that create structures in macro systems. In fact, if all possible degrees of freedom are actualized on equal footing without constraint, the state of "equipartition"…

Mathematical Physics · Physics 2017-12-15 Z. Yoshida , P. J. Morrison

Conserved dynamical systems are generally considered to be critical. We study a class of critical routing models, equivalent to random maps, which can be solved rigorously in the thermodynamic limit. The information flow is conserved for…

Adaptation and Self-Organizing Systems · Physics 2013-01-10 Dimitrije Markovic , Andre Schuelein , Claudius Gros

The backbone of nonequilibrium thermodynamics is the stability structure, where entropy is related to a Lyapunov function of thermodynamic equilibrium. Stability is the background of natural selection: unstable systems are temporary, and…

Physics and Society · Physics 2024-10-01 Peter Ván

The conceptual landscape of convection has two simple gateways: optimal function and random form. Optimal convection adjusts toward a univariate ideal called neutrality. Convection form involves elements (parcels, bubbles, drafts) whose…

Adaptation and Self-Organizing Systems · Physics 2025-04-02 Brian E. Mapes

Existence and uniqueness of global in time measure solution for the multidimensional aggregation equation is analyzed. Such a system can be written as a continuity equation with a velocity field computed through a self-consistent…

Analysis of PDEs · Mathematics 2025-05-16 José Antonio Carrillo , Francois James , Frédéric Lagoutière , Nicolas Vauchelet

Turbulent flows present rich dynamics originating from non-trivial energy fluxes across scales, non-stationary forcings and geometrical constraints. This complexity manifests in non-hyperbolic chaos, randomness, state-dependent persistence…

We introduce a novel type of random perturbation for the classical Lorenz flow in order to better model phenomena slowly varying in time such as anthropogenic forcing in climatology and prove stochastic stability for the unperturbed flow.…

Dynamical Systems · Mathematics 2020-06-09 Michele Gianfelice , Sandro Vaienti

We consider flow along a finite-length collapsible channel driven by a fixed upstream flux, where a section of one wall of a planar rigid channel is replaced by a plane-strain elastic beam subject to uniform external pressure. A modified…

Fluid Dynamics · Physics 2021-09-22 Danyang Wang , Xiaoyu Luo , Peter Stewart

We show that the full features of the dynamics towards the Feigenbaum attractor, present in all low-dimensional maps with a unimodal leading component, form a hierarchical construction with modular organization that leads to a clear-cut…

Chaotic Dynamics · Physics 2015-06-12 Alberto Robledo

The biological theory of adaptive dynamics proposes a description of the long-term evolution of a structured asexual population. It is based on the assumptions of large population, rare mutations and small mutation steps, that lead to a…

Probability · Mathematics 2007-05-23 Nicolas Champagnat , Amaury Lambert

In contexts where data samples represent a physically stable state, it is often assumed that the data points represent the local minima of an energy landscape. In control theory, it is well-known that energy can serve as an effective…

Machine Learning · Computer Science 2024-02-09 Christopher Iliffe Sprague , Arne Elofsson , Hossein Azizpour

The well-defined but intricate course of time evolution exhibited by many naturally occurring phenomena suggests some source of dynamic order sustaining it. In spite of its obviousness as a problem, it has remained absent from the…

Adaptation and Self-Organizing Systems · Physics 2021-03-02 R. Herrero , J. Farjas , F. Pi , G. Orriols

The problem of finite-dimensional asymptotics of infinite-dimensional dynamic systems is studied. A non-linear kinetic system with conservation of supports for distributions has generically finite-dimensional asymptotics. Such systems are…

Statistical Mechanics · Physics 2008-10-03 A. N. Gorban

The famous Bernoulli shift (or dyadic transformation) is perhaps the simplest deterministic dynamical system exhibiting chaotic dynamics. It is a piecewise linear time-discrete map on the unit interval with a uniform slope larger than one,…

Chaotic Dynamics · Physics 2024-04-30 Jin Yan , Moitrish Majumdar , Stefano Ruffo , Yuzuru Sato , Christian Beck , Rainer Klages

We introduce a class of stochastic advection problems amenable to analysis of turbulent transport. The statistics of the flow field are represented as a continuous time Markov process, a choice that captures the intuitive notion of…

Fluid Dynamics · Physics 2022-12-01 Andre N. Souza , Tyler Lutz , Glenn R. Flierl

Traffic waves, the spatiotemporal propagation of congestion, are a key feature of traffic flow. As Adaptive Cruise Control (ACC) systems gain widespread adoption and show promise for improving both efficiency and safety, understanding how…

Analysis of PDEs · Mathematics 2026-02-03 Zihao Li , Quyuan Lin , Fan Pu , Soyoung Ahn , Yunlong Zhang , Jiwan Jiang , Yang Zhou

Self-assembly, the process by which interacting components form well-defined and often intricate structures, is typically thought of as a spontaneous process arising from equilibrium dynamics. When a system is driven by external…

Statistical Mechanics · Physics 2021-11-12 Shriram Chennakesavalu , Grant M. Rotskoff

Macroscopic traffic flow is stochastic, but the physics-informed deep learning methods currently used in transportation literature embed deterministic PDEs and produce point-valued outputs; the stochasticity of the governing dynamics plays…

Systems and Control · Electrical Eng. & Systems 2026-03-11 Wuping Xin