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Machine learning techniques not only offer efficient tools for modelling dynamical systems from data, but can also be employed as frontline investigative instruments for the underlying physics. Nontrivial information about the original…

Data Analysis, Statistics and Probability · Physics 2021-02-24 Francesco Borra , Marco Baldovin

Symbolic dynamics is a coarse-grained description of dynamics. By taking into account the ``geometry'' of the dynamics, it can be cast into a powerful tool for practitioners in nonlinear science. Detailed symbolic dynamics can be developed…

chao-dyn · Physics 2007-05-23 Bai-lin Hao

Energy methods for constructing time-stepping algorithms are of increased interest in application to nonlinear problems, since numerical stability can be inferred from the conservation of the system energy. Alternatively, symplectic…

Computational Physics · Physics 2020-08-24 Vasileios Chatziioannou

This paper begins with a description of methods for estimating image probability density functions that reflects the observation that such data is usually constrained to lie in restricted regions of the high-dimensional image space-not…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Peter Tu , Zhaoyuan Yang , Richard Hartley , Zhiwei Xu , Jing Zhang , Yiwei Fu , Dylan Campbell , Jaskirat Singh , Tianyu Wang

Random invariant manifolds are geometric objects useful for understanding complex dynamics under stochastic influences. Under a nonuniform hyperbolicity or a nonuniform exponential dichotomy condition, the existence of random pseudo-stable…

Dynamical Systems · Mathematics 2009-01-06 Tomas Caraballo , Jinqiao Duan , Kening Lu , Bjorn Schmalfuss

Discrete time random dynamical systems with countably many maps which admit countable Markov partitions on complete metric spaces such that the resulting Markov systems are uniform continuous and contractive are considered. A notion of a…

Probability · Mathematics 2015-06-16 Ivan Werner

We characterize the geometrical and topological aspects of a dynamical system by associating a geometric phase with a phase space trajectory. Using the example of a nonlinear driven damped oscillator, we show that this phase is resilient to…

Chaotic Dynamics · Physics 2007-05-23 Radha Balakrishnan , Indubala Satija

We prove the dynamical large deviations for a particle system in which particles may have different velocities. We assume that we have two infinite reservoirs of particles at the boundary: this is the so-called boundary driven process. The…

Probability · Mathematics 2010-06-02 Jonathan Farfan , Alexandre B. Simas , Fabio J. Valentim

A dynamical network, a graph whose nodes are dynamical systems, is usually characterized by a large dimensional space which is not always accesible due to the impossibility of measuring all the variables spanning the state space. Therefore,…

Chaotic Dynamics · Physics 2019-07-25 Irene Sendiña-Nadal , Christophe Letellier

We will show how it is possible to generate entangled states out of unentangled ones on a bipartite system by means of dynamical boundary conditions. The auxiliary system is defined by a symmetric but not self-adjoint Hamiltonian and the…

Quantum Physics · Physics 2015-01-15 A. Ibort , G. Marmo , J. M. Perez-Pardo

The newly developed "void expansion method" allows for an efficient generation of porous packings of spherical particles over a wide range of volume fractions using the discrete element method. Particles are randomly placed under addition…

Soft Condensed Matter · Physics 2009-11-09 Iwan Schenker , Frank T. Filser , Hans J. Herrmann , Ludwig J. Gauckler

Time evolution equations for dynamical systems can often be derived from generating functionals. Examples are Newton's equations of motion in classical dynamics which can be generated within the Lagrange or the Hamiltonian formalism. We…

Neurons and Cognition · Quantitative Biology 2014-04-23 Claudius Gros

Dissipativity is an essential concept of systems theory. The paper provides an extension of dissipativity, named differential dissipativity, by lifting storage functions and supply rates to the tangent bundle. Differential dissipativity is…

Systems and Control · Computer Science 2013-05-17 Fulvio Forni , Rodolphe Sepulchre

Systems of systems are highly dynamic software systems that require flexible monitoring solutions to be observed and controlled. Indeed, operators have to frequently adapt the set of collected indicators according to changing circumstances,…

Software Engineering · Computer Science 2021-01-05 Alessandro Tundo , Chiara Castelnovo , Marco Mobilio , Oliviero Riganelli , Leonardo Mariani

Stickiness is a well known phenomenon in which chaotic orbits expend an expressive amount of time in specific regions of the chaotic sea. This phenomenon becomes important when dealing with area-preserving open systems because, in this…

Chaotic Dynamics · Physics 2021-01-12 Vitor M. de Oliveira , David Ciro , Iberê L. Caldas

Learning to sample from complex unnormalized distributions is a fundamental challenge in computational physics and machine learning. While score-based and variational methods have achieved success in continuous domains, extending them to…

Machine Learning · Statistics 2026-03-11 Lei Li , Zhen Wang , Lishuo Zhang

Conditional density estimation (density regression) estimates the distribution of a response variable y conditional on covariates x. Utilizing a partition model framework, a conditional density estimation method is proposed using logistic…

Methodology · Statistics 2017-03-22 Richard D. Payne , Nilabja Guha , Yu Ding , Bani K. Mallick

Damped-driven systems are ubiquitous in engineering and science. Despite the diversity of physical processes observed in a broad range of applications, the underlying instabilities observed in practice have a universal characterization…

Adaptation and Self-Organizing Systems · Physics 2022-11-23 J. Nathan Kutz , Aminur Rahman , Megan R. Ebers , James Koch , Jason J. Bramburger

The simulation of particle physics data is a fundamental but computationally intensive ingredient for physics analysis at the Large Hadron Collider, where observational set-valued data is generated conditional on a set of incoming…

Markov partitions persisting in a neighbourhood of hyperbolic components of rational maps were constructed under the condition that closures of Fatou components are disjoint in \cite{R1}. Given such a partition, we characterize all nearby…

Dynamical Systems · Mathematics 2017-11-01 Mary Rees
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