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This paper presents a methodology to achieve lower-dimensional Koopman quasi-linear representations of nonlinear system dynamics using Koopman generalized eigenfunctions. The proposed approach considers the analytically derived Koopman…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Simone Martini , Margareta Stefanovic , Kimon P. Valavanis

The Koopman operator has emerged as a powerful tool for the analysis of nonlinear dynamical systems as it provides coordinate transformations to globally linearize the dynamics. While recent deep learning approaches have been useful in…

Dynamical Systems · Mathematics 2020-06-23 Shaowu Pan , Karthik Duraisamy

Nonlinear differential equations are encountered as models of fluid flow, spiking neurons, and many other systems of interest in the real world. Common features of these systems are that their behaviors are difficult to describe exactly and…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Zexin Sun , Mingyu Chen , John Baillieul

Complete eigenfunctions of linearized integrable equations expanded around an arbitrary solution are obtained for the Ablowitz-Kaup-Newell-Segur (AKNS) hierarchy and the Korteweg-de Vries (KdV) hierarchy. It is shown that the linearization…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Jianke Yang

In this paper we exploit the phenomenon of two principal half eigenvalues in the context of fully nonlinear Lane-Emden type systems with possibly unbounded coefficients and weights. We show that this gives rise to the existence of two…

Analysis of PDEs · Mathematics 2021-12-24 Ederson Moreira dos Santos , Gabrielle Nornberg , Delia Schiera , Hugo Tavares

Analyzing the inner mechanisms of deep neural networks is a fundamental task in machine learning. Existing work provides limited analysis or it depends on local theories, such as fixed-point analysis. In contrast, we propose to analyze…

Machine Learning · Computer Science 2023-02-24 Ilan Naiman , Omri Azencot

Most modern reinforcement learning algorithms optimize a cumulative single-step cost along a trajectory. The optimized motions are often 'unnatural', representing, for example, behaviors with sudden accelerations that waste energy and lack…

Machine Learning · Computer Science 2024-07-03 Motoya Ohnishi , Isao Ishikawa , Kendall Lowrey , Masahiro Ikeda , Sham Kakade , Yoshinobu Kawahara

The field of dynamical systems is being transformed by the mathematical tools and algorithms emerging from modern computing and data science. First-principles derivations and asymptotic reductions are giving way to data-driven approaches…

Dynamical Systems · Mathematics 2021-11-02 Steven L. Brunton , Marko Budišić , Eurika Kaiser , J. Nathan Kutz

We consider Koopman operator theory in the context of nonlinear infinite-dimensional systems, where the operator is defined over a space of bounded continuous functionals. The properties of the Koopman semigroup are described and a…

Analysis of PDEs · Mathematics 2021-10-07 Alexandre Mauroy

On the basis of the canonical quantization procedure of a system defined on a cubic lattice, we propose a new method, in which resolutions of unity expressed in terms of eigenvectors are naturally provided, to find eigenvectors of field…

High Energy Physics - Theory · Physics 2019-12-06 Seiji Sakoda

The Koopman Operator (KO) offers a promising alternative methodology to solve ordinary differential equations analytically. The solution of the dynamical system is analyzed in terms of observables, which are expressed as a linear…

Numerical Analysis · Mathematics 2022-07-15 Simone Servadio , David Arnas , Richard Linares

We study numerically the spectrum and eigenfunctions of the quantum Neumann model, illustrating some general properties of a non trivial integrable model.

High Energy Physics - Theory · Physics 2009-11-10 Marc P. Bellon , Michel Talon

This paper presents the results of identification of vehicle dynamics using the Koopman operator. The basic idea is to transform the state space of a nonlinear system (a car in our case) to a higher-dimensional space, using so-called basis…

Optimization and Control · Mathematics 2019-03-15 Vit Cibulka , Tomas Hanis , Martin Hromcik

Koopman operator describes evolution of observables in the phase space, which could be used to extract characteristic dynamical features of a nonlinear system. Here, we show that it is possible to carry out interesting symbolic partitions…

Chaotic Dynamics · Physics 2020-07-23 Cong Zhang , Yueheng Lan

Often in applications such as rare events estimation or optimal control it is required that one calculates the principal eigen-function and eigen-value of a non-negative integral kernel. Except in the finite-dimensional case, usually…

Computation · Statistics 2016-09-28 Nick Whiteley , Nikolas Kantas

We consider the Neumann-Poincar'e (double layer potential) operator in 3D elasicity on a smooth closed surface. Its essential spectrum consists of 3 points. We find the asymptotics of sequences of eigenvalues converging to these three…

Analysis of PDEs · Mathematics 2022-12-06 Grigori Rozenblum

Path integrals are a central tool when it comes to describing quantum or thermal fluctuations of particles or fields. Their success dates back to Feynman who showed how to use them within the framework of quantum mechanics. Since then, path…

Statistical Mechanics · Physics 2022-08-31 Leticia F. Cugliandolo , Vivien Lecomte , Frédéric Van Wijland

The purpose of this work is to study spectral methods to approximate the eigenvalues of nonlocal integral operators. Indeed, even if the spatial domain is an interval, it is very challenging to obtain closed analytical expressions for the…

Numerical Analysis · Mathematics 2021-10-13 Luciano Lopez , Sabrina Francesca Pellegrino

Nonlinearity presents a significant challenge in problems involving dynamical systems, prompting the exploration of various linearization techniques, including the well-known Carleman Linearization. In this paper, we introduce the Koopman…

Dynamical Systems · Mathematics 2023-10-31 Dongwei Shi , Xiu Yang

We consider a new algorithm in light of the min-max Collatz-Wielandt formalism to compute the principal eigenvalue and the eigenvector (eigen-function) for a class of positive Perron-Frobenius-like operators. Such operators are natural…

Numerical Analysis · Mathematics 2021-11-25 Dong Li , Jianan Li