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A powerful tool for studying long-term convergence of a Markov process to its stationary distribution is a Lyapunov function. In some sense, this is a substitute for eigenfunctions. For a stochastically ordered Markov process on the…

Probability · Mathematics 2021-03-01 Andrey Sarantsev

We develop a theory of Jacobi polynomials for parabolic subgroups of finite reflection groups that specializes to the cases studied by Heckman and Opdam in which the whole group and the trivial group are considered. For the intermediate…

Representation Theory · Mathematics 2023-03-13 Maarten van Pruijssen

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace. The Koopman operator is an infinite-dimensional linear operator that evolves…

Dynamical Systems · Mathematics 2016-04-27 Steven L. Brunton , Bingni W. Brunton , Joshua L. Proctor , J. Nathan Kutz

We develop Kummer theory for algebraic function fields in finitely many transcendental variables. We consider any finitely generated Kummer extension (possibly, over a cyclotomic extension) of an algebraic function field, and describe the…

Number Theory · Mathematics 2024-07-16 Félix Baril Boudreau , Antonella Perucca

The problem of phase space transport which is of interest both theoretically and from the point of view of applications has been investigated extensively using geometric and probabilistic methods. Two of the important tools for this that…

Chaotic Dynamics · Physics 2011-07-06 Phanindra Tallapragada

An outstanding challenge in nonlinear systems theory is identification or learning of a given nonlinear system's Koopman operator directly from data or models. Advances in extended dynamic mode decomposition approaches and machine learning…

Machine Learning · Computer Science 2017-12-11 Charles A. Johnson , Enoch Yeung

This paper presents a new interpretation of the Lyapunov and Riccati equations from the perspective of positive system theory. We show it is possible to construct positive systems related to these equations, and then certain conclusions --…

Optimization and Control · Mathematics 2025-11-24 Dongjun Wu , Yankai Lin

In this paper we study polynomial maps of vector spaces and their eigenvectors and eigenvalues. The new quantity called complanart is defined. Complanarts determine complanarity of solution vectors of systems of polynomial equations.…

Mathematical Physics · Physics 2011-01-03 Andrey Vlasov

We develop a Koopman operator framework for studying the {computational properties} of dynamical systems. Specifically, we show that the resolvent of the Koopman operator provides a natural abstraction of halting, yielding a ``Koopman…

Mathematical Physics · Physics 2025-10-08 Francesco Caravelli , Jean-Charles Delvenne

This paper deals with eigenvalues and eigenvectors of bicomplex linear operators defined on bicomplex space. We investigate the properties of these operators in the context of eigenvalues and eigenvectors, along with some relevant theorems.…

Representation Theory · Mathematics 2025-03-25 Anjali Anjali , Akhil Prakash , Amita , Prabhat Kumar

Koopman operator theory offers a rigorous treatment of dynamics and has been emerging as an alternative modeling and learning-based control method across various robotics sub-domains. Due to its ability to represent nonlinear dynamics as a…

In this paper, we consider time-varying real analytic vector fields as curves on the space of real analytic vector fields. Using a suitable topology on the space of real analytic vector fields, we study and characterize different properties…

Functional Analysis · Mathematics 2016-04-11 Saber Jafarpour

Recently, Koopman operator theory has become a powerful tool for developing linear representations of non-linear dynamical systems. However, existing data-driven applications of Koopman operator theory, including both traditional and deep…

Machine Learning · Computer Science 2023-05-17 King Fai Yeh , Paris Flood , William Redman , Pietro Liò

Koopman representations aim to learn features of nonlinear dynamical systems (NLDS) which lead to linear dynamics in the latent space. Theoretically, such features can be used to simplify many problems in modeling and control of NLDS. In…

Machine Learning · Computer Science 2023-11-27 Mahan Fathi , Clement Gehring , Jonathan Pilault , David Kanaa , Pierre-Luc Bacon , Ross Goroshin

Koopman operator based models emerged as the leading methodology for machine learning of dynamical systems. But their scope is much larger. In fact they present a new take on modeling of physical systems, and even language. In this article…

Dynamical Systems · Mathematics 2023-12-19 Igor Mezić

We develop cohomological interpretations for several types of automorphic forms for Hecke triangle groups of infinite covolume. We then use these interpretations to establish explicit isomorphisms between spaces of automorphic forms,…

Number Theory · Mathematics 2021-01-05 Roelof Bruggeman , Anke Pohl

We consider polynomial differential equations and make a number of contributions to the questions of (i) complexity of deciding stability, (ii) existence of polynomial Lyapunov functions, and (iii) existence of sum of squares (sos) Lyapunov…

Optimization and Control · Mathematics 2013-09-03 Amir Ali Ahmadi , Pablo A. Parrilo

This is a brief summary of our studies of quantum field theories in a special limit in which the instantons are present, the anti-instantons are absent, and the perturbative corrections are reduced to one-loop. We analyze the corresponding…

High Energy Physics - Theory · Physics 2008-11-26 E. Frenkel , A. Losev , N. Nekrasov

This paper proposes an original methodology to compute the regions of attraction in hyperbolic and polynomial nonlinear dynamical systems using the eigenfunctions of the discrete-time approximation of the Koopman operator given by the…

Systems and Control · Electrical Eng. & Systems 2022-09-07 Camilo Garcia-Tenorio , Duvan Tellez-Castro , Eduardo Mojica-Nava , Alain Vande Wouwer

Discovery of mathematical descriptors of physical phenomena from observational and simulated data, as opposed to from the first principles, is a rapidly evolving research area. Two factors, time-dependence of the inputs and hidden…

Numerical Analysis · Mathematics 2023-10-26 Hongli Zhao , Daniel M. Tartakovsky