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In this paper we develop a novel, discrete-time optimal control framework for mechanical systems with uncertain model parameters. We consider finite-horizon problems where the performance index depends on the statistical moments of the…

Optimization and Control · Mathematics 2017-05-17 George I. Boutselis , Yunpeng Pan , Gerardo De La Tore , Evangelos A. Theodorou

We show how a recently introduced statistics [Patil et al, Phys. Rev. Lett. 81 5878 (2001)] provides a direct relationship between dimension and predictability in spatiotemporal chaotic systems. Regions of low dimension are identified as…

Chaotic Dynamics · Physics 2007-05-23 Gerson Francisco , Paulsamy Muruganandam

The folded node is a singularity associated with loss of normal hyperbolicity in systems where mixtures of slow and fast timescales arise due to singular perturbations. Canards are special solutions that reveal a counteractive feature of…

Dynamical Systems · Mathematics 2015-06-03 Mathieu Desroches , Mike R. Jeffrey

The aim of this paper is to study the relationship between Hamiltonian dynamics and constrained variational calculus. We describe both using the notion of Lagrangian submanifolds of convenient symplectic manifolds and using the so-called…

Mathematical Physics · Physics 2015-05-30 Manuel de Leon , Fernando Jimenez , David Martin de Diego

This article reviews the role of hidden symmetries of dynamics in the study of physical systems, from the basic concepts of symmetries in phase space to the forefront of current research. Such symmetries emerge naturally in the description…

Mathematical Physics · Physics 2015-06-23 Marco Cariglia

Vortices are known to play a key role in the dynamics of the quantum trajectories defined within the framework of the de Broglie-Bohm formalism of quantum mechanics. It has been rigourously proved that the motion of a vortex in the…

Quantum Physics · Physics 2010-08-17 F. Borondo , A. Luque , J. Villanueva , D. A. Wisniacki

We construct algorithms and topological invariants that allow us to distinguish the topological type of a surface, as well as functions and vector fields for their topological equivalence. In the first part (arXiv:2501.15657), we discused…

Geometric Topology · Mathematics 2025-02-17 Alexandr Prishlyak

We use a quantitative topological characterization of complex dynamics to measure geometric structures. This approach is used to analyze the weakly turbulent state of spiral defect chaos in experiments on Rayleigh-Benard convection.…

Pattern Formation and Solitons · Physics 2009-04-28 Kapilanjan Krishan , Marcio Gameiro , Konstantin Mischaikow , Michael F. Schatz

Whether there is similarity between two physical processes in the movement of objects and the complexity of behavior is an essential problem in science. How to seek similarity through the adoption of quantitative and qualitative research…

Dynamical Systems · Mathematics 2023-01-02 Yuting Chen , Yong Li

Differentiable physics is a powerful approach to learning and control problems that involve physical objects and environments. While notable progress has been made, the capabilities of differentiable physics solvers remain limited. We…

Machine Learning · Computer Science 2020-07-07 Yi-Ling Qiao , Junbang Liang , Vladlen Koltun , Ming C. Lin

In this paper we discuss some general aspects of the so-called "geometrodynamical approach" (GDA) to Chaos and present some results obtained within this framework. In order to support the claim that the GDA isn't simply a mere…

chao-dyn · Physics 2008-02-03 Di Bari Maria , Cipriani Piero

We consider a two-dimensional model of double-diffusive convection and its time discretisation using a second-order scheme which treat the nonlinear term explicitly (backward differentiation formula with a one-leg method). Uniform bounds on…

Numerical Analysis · Mathematics 2014-02-28 Florentina Tone , Xiaoming Wang , Djoko Wirosoetisno

A chaotic dynamics generalizing the Verhulst, Ricker dynamics and containing a new parameter is introduced. It is established that with the value of this parameter approaching the fine-structure constant the chaos in the system is…

Pattern Formation and Solitons · Physics 2012-05-29 D. B. Volov

Dissipative phenomena manifest in multiple mechanical systems. In this dissertation, different geometric frameworks for modelling non-conservative dynamics are considered. The objective is to generalize several results from conservative…

Mathematical Physics · Physics 2024-09-19 Asier López-Gordón

The dynamics on a chaotic attractor can be quite heterogeneous, being much more unstable in some regions than others. Some regions of a chaotic attractor can be expanding in more dimensions than other regions. Imagine a situation where two…

Chaotic Dynamics · Physics 2018-11-14 Yoshitaka Saiki , Miguel A. F. Sanjuan , James A. Yorke

Flexible slender structures such as rods, ribbons, plates, and shells exhibit extreme nonlinear responses bending, twisting, buckling, wrinkling, and self contact, that defy conventional simulation frameworks. Discrete Differential Geometry…

We study several examples of kinetically constrained lattice models using dynamically accessible volume as an order parameter. Thereby we identify two distinct regimes exhibiting dynamical slowing, with a sharp threshold between them. These…

Statistical Mechanics · Physics 2009-11-11 Aonghus Lawlor , Paolo De Gregorio , Phil Bradley , Mauro Sellitto , Kenneth A. Dawson

We consider here a recently proposed geometrical criterion for local instability based on the geodesic deviation equation. Although such a criterion can be useful in some cases, we show here that, in general, it is neither necessary nor…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Alberto Saa

The cavity method is one of the cornerstones of the statistical physics of disordered systems such as spin glasses and other complex systems. It is able to analytically and asymptotically exactly describe the equilibrium properties of a…

Disordered Systems and Neural Networks · Physics 2023-09-11 Freya Behrens , Barbora Hudcová , Lenka Zdeborová

In this paper we explore challenges in developing a topological framework in which machine learning can be used to robustly characterize global dynamics. Specifically, we focus on learning a useful discretization of the phase space of a…