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We develop a model reduction technique for non-smooth dynamical systems using spectral submanifolds. Specifically, we construct low-dimensional, sparse, nonlinear and non-smooth models on unions of slow and attracting spectral submanifolds…

Dynamical Systems · Mathematics 2023-12-25 Leonardo Bettini , Mattia Cenedese , George Haller

Every invertible, measure-preserving dynamical system induces a Koopman operator, which is a linear, unitary evolution operator acting on the $L^2$ space of observables associated with the invariant measure. Koopman eigenfunctions represent…

Dynamical Systems · Mathematics 2020-11-26 Suddhasattwa Das , Dimitrios Giannakis

The paper presents a model-independent, nonperturbative proof of operator product expansions in quantum field theory. As an input, a recently proposed phase space condition is used that allows a precise description of point field…

Mathematical Physics · Physics 2007-11-27 Henning Bostelmann

We study the gap (= "projection norm" = "graph distance") topology of the space of (not necessarily bounded) self--adjoint Fredholm operators in a separable Hilbert space by the Cayley transform and direct methods. In particular, we show…

Functional Analysis · Mathematics 2007-05-23 Bernhelm Booss-Bavnbek , Matthias Lesch , John Phillips

In this paper, we study the spectral theory for nonlocal dispersal operators with time periodic indefinite weight functions subject to Dirichlet type, Neumann type and spatial periodic type boundary conditions. We first obtain necessary and…

Dynamical Systems · Mathematics 2016-03-01 Wenxian Shen , Xiaoxia Xie

Novel quantization properties related to the state vectors and the energy spectrum of a two-dimensional system of free particles are obtained in the framework of noncommutative (NC) quantum mechanics (QM) supported by the Weyl-Wigner…

Quantum Physics · Physics 2015-08-04 Catarina Bastos , Alex E. Bernardini , Jonas F. G. Santos

This paper concerns the spectral properties of the Neumann-Poincar\'e operator on $m$-fold rotationally symmetric planar domains. An $m$-fold rotationally symmetric simply connected domain $D$ is realized as the $m$th-root transform of a…

Spectral Theory · Mathematics 2022-01-21 Yong-Gwan Ji , Hyeonbae Kang

We numerically verify and analytically prove a winding number invariant that correctly predicts the number of edge states in one-dimensional, nearest-neighbor (between unit cells), two-band models with any complex couplings and open…

Mesoscale and Nanoscale Physics · Physics 2025-05-28 Janet Zhong , Heming Wang , Alexander N Poddubny , Shanhui Fan

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

We give a characterisation of the spectral properties of linear differential operators with constant coefficients, acting on functions defined on a bounded interval, and determined by general linear boundary conditions. The boundary…

Spectral Theory · Mathematics 2013-03-22 David Andrew Smith , Beatrice Pelloni

We present a unified approach to representations of quantum mechanics on noncommutative spaces with general constant commutators of phase-space variables. We find two phases and duality relations among them in arbitrary dimensions.…

High Energy Physics - Theory · Physics 2011-08-11 Larisa Jonke , Stjepan Meljanac

We propose a neural network-based model for nonlinear dynamics in continuous time that can impose inductive biases on decay rates and/or frequencies. Inductive biases are helpful for training neural networks especially when training data…

Machine Learning · Statistics 2022-12-27 Tomoharu Iwata , Yoshinobu Kawahara

The lacking of analytic solutions of diverse partial differential equations (PDEs) gives birth to a series of computational techniques for numerical solutions. Although numerous latest advances are accomplished in developing neural…

Machine Learning · Computer Science 2024-05-07 Wei Xiong , Xiaomeng Huang , Ziyang Zhang , Ruixuan Deng , Pei Sun , Yang Tian

The Koopman framework proposes a linear representation of finite-dimensional nonlinear systems through a generally infinite-dimensional globally linear embedding. Originally, the Koopman formalism has been derived for autonomous systems. In…

Systems and Control · Electrical Eng. & Systems 2025-07-15 Lucian Cristian Iacob , Roland Tóth , Maarten Schoukens

Understanding nonlinear dynamical systems (NLDSs) is challenging in a variety of engineering and scientific fields. Dynamic mode decomposition (DMD), which is a numerical algorithm for the spectral analysis of Koopman operators, has been…

Machine Learning · Statistics 2022-05-10 Keisuke Fujii , Yoshinobu Kawahara

We consider a family of non-compact manifolds $X_\eps$ (``graph-like manifolds'') approaching a metric graph $X_0$ and establish convergence results of the related natural operators, namely the (Neumann) Laplacian $\laplacian {X_\eps}$ and…

Mathematical Physics · Physics 2009-11-11 Olaf Post

The concept of supersymmetry in a quantum mechanical system is extended, permitting the recognition of many more supersymmetric systems, including very familiar ones such as the free particle. Its spectrum is shown to be supersymmetric,…

Quantum Physics · Physics 2009-11-10 A. R. P. Rau

Resonances in the form of quasi-normal modes (QNMs) for open scattering systems can be generally identified in the far field through peaks of scattering spectra (\textit{e.g.} cross sections of scattering, extinction and absorption).…

Optics · Physics 2025-03-14 Jingwei Wang , Yuntian Chen , Wei Liu

The resonances of forced dynamical systems occur when either the amplitude of the frequency response undergoes a local maximum (amplitude resonance) or phase lag quadrature takes places (phase resonance). This study focuses on the phase…

Dynamical Systems · Mathematics 2021-08-25 Martin Volvert , Gaetan Kerschen

We exploit the key idea that nonlinear system identification is equivalent to linear identification of the socalled Koopman operator. Instead of considering nonlinear system identification in the state space, we obtain a novel linear…

Systems and Control · Computer Science 2016-08-30 Alexandre Mauroy , Jorge Goncalves