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This paper formulates a new approach to the study of chaos in discrete dynamical systems based on the notions of inverse ill-posed problems, set-valued mappings, generalized and multivalued inverses, graphical convergence of a net of…

Chaotic Dynamics · Physics 2007-05-23 A. Sengupta

Chaos-based potentials are defined and implemented in the one-dimensional tight-binding model as a way of simulating disorder-controlled crystalline lattices. In this setting, disorder is handled with the aid of the chaoticity parameter.…

Disordered Systems and Neural Networks · Physics 2018-01-25 Weslley Florentino de Oliveira , Giancarlo Queiroz Pellegrino

We generate new hierarchy of many-parameter family of maps of the interval [0,1] with an invariant measure, by composition of the chaotic maps of reference [1]. Using the measure, we calculate Kolmogorov-Sinai entropy, or equivalently…

Chaotic Dynamics · Physics 2015-06-26 M. A. Jafarizadeh , S. Behnia , S. Khorram , H. Naghshara

This paper extends the deterministic Lyapunov-based stabilization framework to random hyperbolic systems of conservation laws, where uncertainties arise in boundary controls and initial data. Building on the finite volume discretization…

Numerical Analysis · Mathematics 2025-10-10 Shaoshuai Chu , Michael Herty , Alexander Kurganov

This paper presents some finite combinatorics of set systems with applications to model theory, particularly the study of dependent theories. There are two main results. First, we give a way of producing lower bounds on VC_ind-density, and…

Logic · Mathematics 2016-02-10 Hunter R. Johnson

While a previously proposed method for estimating inertial manifold dimension, based on explicitly computing angles between pairs of covariant Lyapunov vectors (CLVs), employs efficient algorithms, it remains computationally demanding due…

Chaotic Dynamics · Physics 2025-12-12 Pavel V. Kuptsov

A new scheme for numerical integration of the 1D2V relativistic Vlasov-Maxwell system is proposed. Assuming that all particles in a cell of the phase space move with the same velocity as that of the particle located at the center of the…

Plasma Physics · Physics 2010-02-18 Akihiro Suzuki , Toshikazu Shigeyama

In this work, the term ``quantum chaos'' refers to spectral correlations similar to those found in the random matrix theory. Quantum chaos can be diagnosed through the analysis of level statistics using e.g.~the spectral form factor, which…

We apply to bidimensional chaotic maps the numerical method proposed by Ginelli et al. to approximate the associated Oseledets splitting, i.e. the set of linear subspaces spanned by the so called covariant Lyapunov vectors (CLV) and…

Chaotic Dynamics · Physics 2016-12-21 Matteo Sala , Cesar Manchein , Roberto Artuso

We compute the Lyapunov spectrum and the Kolmogorov-Sinai entropy for a moving particle placed in a dilute, random array of hard disk or hard sphere scatterers - i.e. the dilute Lorentz gas model. This is carried out in two ways: First we…

chao-dyn · Physics 2009-10-30 H. van Beijeren , A. Latz , J. R. Dorfman

We present a theory for the dynamical evolution of a quantum system coupled to a complex many-body intrinsic system/environment. By modelling the intrinsic many-body system with parametric random matrices, we study the types of effective…

Nuclear Theory · Physics 2009-10-30 Aurel Bulgac , Gui DoDang , Dimitri Kusnezov

Variational quantum algorithms (VQAs) incorporate hybrid quantum-classical computation aimed at harnessing the power of noisy intermediate-scale quantum (NISQ) computers to solve challenging computational problems. In this thesis, three…

Quantum Physics · Physics 2025-02-18 Mirko Consiglio

Solving for the lowest energy eigenstate of the many-body Schrodinger equation is a cornerstone problem that hinders understanding of a variety of quantum phenomena. The difficulty arises from the exponential nature of the Hilbert space…

Chaotic systems such as the gravitational N-body problem are ubiquitous in astronomy. Machine learning (ML) is increasingly deployed to predict the evolution of such systems, e.g. with the goal of speeding up simulations. Strategies such as…

The recent years have witnessed a growing interest for covariant Lyapunov vectors (CLVs) which span local intrinsic directions in the phase space of chaotic systems. Here we review the basic results of ergodic theory, with a specific…

Chaotic Dynamics · Physics 2015-06-12 Francesco Ginelli , Hugues Chate' , Roberto Livi , Antonio Politi

Following Papadakis (2005)'s numerical exploration of the Chermnykh's problem, we here study a Chermnykh-like problem motivated by the astrophysical applications. We find that both the equilibrium points and solution curves become quite…

Astrophysics · Physics 2008-11-26 Ing-Guey Jiang , Li-Chin Yeh

Machine learning (ML) strategies are opening the door to faster computer simulations, allowing us to simulate more realistic colloidal systems. Since the interactions in colloidal systems are often highly many-body, stemming from e.g.…

Soft Condensed Matter · Physics 2026-01-09 Rinske M. Alkemade , Rastko Sknepnek , Frank Smallenburg , Laura Filion

We study Lyapunov vectors (LVs) corresponding to the largest Lyapunov exponents in systems with spatiotemporal chaos. We focus on characteristic LVs and compare the results with backward LVs obtained via successive Gram-Schmidt…

Chaotic Dynamics · Physics 2008-08-05 Diego Pazó , Ivan G. Szendro , Juan M. López , Miguel A. Rodríguez

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range…

Materials Science · Physics 2024-11-14 Emanuel A. Lazar , Jiayin Lu , Chris H. Rycroft , Deborah Schwarcz

This study is focused on the qualitative and quantitative characterization of chaotic systems with the use of symbolic description. We consider two famous systems: Lorenz and R\"ossler models with their iconic attractors, and demonstrate…

Dynamical Systems · Mathematics 2024-06-19 James Scully , Alexander Neiman , Andrey Shilnikov
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