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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 method of using periodic approximations to compute the spectral decomposition of the Koop- man operator is generalized to the class of measure-preserving flows on compact metric spaces. It is shown that the spectral decomposition of the…

Dynamical Systems · Mathematics 2018-06-28 Nithin Govindarajan , Ryan Mohr , Shivkumar Chandrasekaran , Igor Mezić

I was asked to make my, by now quite old PhD thesis, available on the arxiv, for parts of it was never submitted for publication. The thesis offers a systematic study of stochastic differential equations (SDEs) on non-compact spaces. In…

Probability · Mathematics 2021-06-01 Xue-Mei Li

Linear dynamical systems are fully characterized by their eigenspectra, accessible directly from the generator of the dynamics. For nonlinear systems governed by partial differential equations, no equivalent theory exists. We introduce Lie…

Machine Learning · Computer Science 2026-04-02 Shafayeth Jamil , Rehan Kapadia

Dynamical systems provide a comprehensive way to study complex and changing behaviors across various sciences. Many modern systems are too complicated to analyze directly or we do not have access to models, driving significant interest in…

Dynamical Systems · Mathematics 2024-07-10 Matthew J. Colbrook , Igor Mezić , Alexei Stepanenko

The Koopman operator lifts nonlinear dynamical systems into a functional space of observables, where the dynamics are linear. In this paper, we provide three different Koopman representations for hybrid systems. The first is specific to…

Dynamical Systems · Mathematics 2020-06-23 Craig Bakker , Arnab Bhattacharya , Samrat Chatterjee , Casey J. Perkins , Matthew R. Oster

Forecasting physical systems over long horizons from irregularly sampled observations demands models that are stable, computationally efficient, and free of fixed-timestep assumptions. We address this with a continuous-time Koopman…

Machine Learning · Computer Science 2026-05-11 Rares Grozavescu , Pengyu Zhang , Etienne Meunier , Mark Girolami

The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces. Dynamic Mode Decomposition and Extended Dynamic Mode Decomposition are amongst the most…

Machine Learning · Computer Science 2021-03-26 Francesco Zanini , Alessandro Chiuso

We discuss a general framework of monotone skew-product semiflows under a connected group action. In a prior work, a compact connected group $G$-action has been considered on a strongly monotone skew-product semiflow. Here we relax the…

Dynamical Systems · Mathematics 2012-01-30 Feng Cao , Mats Gyllenberg , Yi Wang

In this work we establish that finite directed graphs give rise to semiflows on the power set of their nodes. We analyze the topological dynamics for semiflows on finite directed graphs by characterizing Morse decompositions, recurrence…

Dynamical Systems · Mathematics 2020-05-29 José Ayala , Wolfgang Kliemann

In this paper, we develop the Koopman operator theory for dynamical systems with symmetry. In particular, we investigate how the Koopman operator and eigenfunctions behave under the action of the symmetry group of the underlying dynamical…

Dynamical Systems · Mathematics 2020-03-11 Subhrajit Sinha , Sai P. Nandanoori , Enoch Yeung

We review recent advances regarding the long-time dynamics of space-periodic water waves, focusing on 1) bifurcation of quasi-periodic solutions, both standing and traveling; 2) long-time well-posedness results; 3) modulational instability…

Analysis of PDEs · Mathematics 2025-12-29 Massimiliano Berti

Dynamical systems that are contracting on a subspace are said to be semicontracting. Semicontraction theory is a useful tool in the study of consensus algorithms and dynamical flow systems such as Markov chains. To develop a comprehensive…

Probability · Mathematics 2022-12-22 Giulia De Pasquale , Kevin D. Smith , Francesco Bullo , Maria Elena Valcher

We consider impulsive semiflows defined on compact metric spaces and give sufficient conditions, both on the semiflows and the potentials, for the existence and uniqueness of equilibrium states. We also generalize the classical notion of…

Dynamical Systems · Mathematics 2015-11-30 Jose F. Alves , Maria Carvalho , Jaqueline Siqueira

We present a flexible data-driven method for dynamical system analysis that does not require explicit model discovery. The method is rooted in well-established techniques for approximating the Koopman operator from data and is implemented…

Dynamical Systems · Mathematics 2023-11-01 Jason J. Bramburger , Giovanni Fantuzzi

In this paper, we present a new data-driven method for learning stable models of nonlinear systems. Our model lifts the original state space to a higher-dimensional linear manifold using Koopman embeddings. Interestingly, we prove that…

Machine Learning · Computer Science 2021-10-14 Fletcher Fan , Bowen Yi , David Rye , Guodong Shi , Ian R. Manchester

Koopman operators provide a linear framework for data-driven analyses of nonlinear dynamical systems, but their infinite-dimensional nature presents major computational challenges. In this article, we offer an introductory guide to Koopman…

Numerical Analysis · Mathematics 2025-10-28 Matthew J. Colbrook , Zlatko Drmač , Andrew Horning

Continuous Normalizing Flows (CNFs) enable elegant generative modeling but remain bottlenecked by slow sampling: producing a single sample requires solving a nonlinear ODE with hundreds of function evaluations. Recent approaches such as…

Machine Learning · Computer Science 2025-10-23 Erkan Turan , Aristotelis Siozopoulos , Louis Martinez , Julien Gaubil , Emery Pierson , Maks Ovsjanikov

Spectral decomposition of the Koopman operator is attracting attention as a tool for the analysis of nonlinear dynamical systems. Dynamic mode decomposition is a popular numerical algorithm for Koopman spectral analysis; however, we often…

Machine Learning · Computer Science 2018-01-31 Naoya Takeishi , Yoshinobu Kawahara , Takehisa Yairi

It is common practice in both theoretical computer science and theoretical physics to describe the (static) logic of a system by means of a complete lattice. When formalizing the dynamics of such a system, the updates of that system…

Category Theory · Mathematics 2007-05-23 Isar Stubbe
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