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It is well known that instabilities of nearly integrable Hamiltonian systems occur around resonances. Dynamics near resonances of these systems is well approximated by the associated averaged system, called slow system. Each resonance is…

Dynamical Systems · Mathematics 2015-01-26 Vadim Kaloshin , Ke Zhang

We consider a nonlinear non-autonomous system with time-varying delays $$ \dot{x_i}(t)=-a_i(t)x_{i}(h_i(t))+\sum_{j=1}^mF_{ij}(t,x_j(g_{ij}(t))) $$ which has a large number of applications in the theory of artificial neural networks. Via…

Dynamical Systems · Mathematics 2013-09-10 Leonid Berezansky , Elena Braverman , Lev Idels

Theories of localised pattern formation are important to understand a broad range of natural patterns, but are less well-understood than more established mechanisms of domain-filling pattern formation. Here, we extend recent work on pattern…

Pattern Formation and Solitons · Physics 2025-07-22 Andrew L. Krause , Václav Klika , Edgardo Villar-Sepúlveda , Alan R. Champneys , Eamonn A. Gaffney

We study the correlated Haldane-Hubbard model with single-particle gain and loss, focusing on its non-Hermitian phase diagram and the ensuing non-unitary dynamic properties. The interplay of interactions and non-hermiticity results in…

Strongly Correlated Electrons · Physics 2025-05-05 Tian-Cheng Yi , Rubem Mondaini

Stochastic Gumbel graph networks are proposed to learn high-dimensional time series, where the observed dimensions are often spatially correlated. To that end, the observed randomness and spatial-correlations are captured by learning the…

Machine Learning · Computer Science 2023-07-13 Jin Guo , Ting Gao , Yufu Lan , Peng Zhang , Sikun Yang , Jinqiao Duan

This paper is a continuation of the paper \cite{JL}, which focuses on exploring the global stability of nonlinear stochastic feedback systems on the nonnegative orthant driven by multiplicative white noise and presenting a couple of…

Dynamical Systems · Mathematics 2016-12-05 Jifa Jiang , Xiang Lv

To describe the slow dynamics of a system out of equilibrium, but close to a dynamical arrest, we generalize the ideas of previous work to the case where time-translational invariance is broken. We introduce a model of the dynamics that is…

Disordered Systems and Neural Networks · Physics 2016-08-31 P. De Gregorio , F. Sciortino , P. Tartaglia , E. Zaccarelli , K. A. Dawson

The problem of linear instability of a nonlinear traveling wave in a canonical Hamiltonian system with translational symmetry subject to superharmonic perturbations is discussed. It is shown that exchange of stability occurs when energy is…

Fluid Dynamics · Physics 2019-08-09 N. Sato , M. Yamada

In this work the stability of perturbed linear time-varying systems is studied. The main features of the problem are threefold. Firstly, the time-varying dynamics is not required to be continuous but allowed to have jumps. Also the system…

Systems and Control · Electrical Eng. & Systems 2022-02-25 Shenyu Liu

We introduce a driven-dissipative Bose-Hubbard chain describing coupled lossy photonic modes, in which time-reversal symmetry is broken by a coherent drive with a uniform phase gradient. We investigate this model by means of a Gaussian…

Quantum Physics · Physics 2024-11-15 Laszlo Rassaert , Tomás Ramos , Tommaso Roscilde , Diego Porras

We propose and analyse a novel, fully discrete numerical algorithm for the approximation of the generalised Stokes system forced by transport noise -- a prototype model for non-Newtonian fluids including turbulence. Utilising the Gradient…

Numerical Analysis · Mathematics 2024-12-20 Jerome Droniou , Kim-Ngan Le , Jörn Wichmann

The purpose of this note is to extend the recent generalized version of the Grobman-Hartman theorem established by Bernardes Jr. and Messaoudi from an autonomous to the nonautonomous dynamics. More precisely, we prove that any sufficiently…

Dynamical Systems · Mathematics 2021-07-14 Lucas Backes , Davor Dragičević

In contrast to Hermitian systems, eigenstates of non-Hermitian ones are in general nonorthogonal. This feature is most pronounced at exceptional points where several eigenstates are linearly dependent. In this work we show that near this…

Quantum Physics · Physics 2016-12-23 Alexander A. Zyablovsky , Evgeny S. Andrianov , Alexander A. Pukhov

Discovering a suitable coordinate transformation for nonlinear systems enables the construction of simpler models, facilitating prediction, control, and optimization for complex nonlinear systems. To that end, Koopman operator theory offers…

Machine Learning · Computer Science 2023-08-29 Pawan Goyal , Süleyman Yıldız , Peter Benner

We study the convergence of a Zakharov system driven by a time white noise, colored in space, to a multiplicative stochastic nonlinear Schr{\"o}dinger equation, as the ion-sound speed tends to infinity. In the absence of noise, the…

Analysis of PDEs · Mathematics 2024-09-24 Grégoire Barrué , Anne de Bouard , Arnaud Debussche

For piecewise expanding one-dimensional maps without periodic turning points we prove that isolated eigenvalues of small (random) perturbations of these maps are close to isolated eigenvalues of the unperturbed system. (Here ``eigenvalue''…

chao-dyn · Physics 2009-10-30 Michael Blank , Gerhard Keller

We investigate the effects of dichotomous noise added to a classical harmonic oscillator in the form of stochastic time-dependent gain and loss states, whose durations are sampled from two distinct exponential waiting time distributions.…

Statistical Mechanics · Physics 2016-11-01 Mirko Luković , Patrick Navez , Giorgos P. Tsironis , Theo Geisel

We consider the problem of learning stabilizable systems governed by nonlinear state equation $h_{t+1}=\phi(h_t,u_t;\theta)+w_t$. Here $\theta$ is the unknown system dynamics, $h_t $ is the state, $u_t$ is the input and $w_t$ is the…

Machine Learning · Computer Science 2021-11-22 Yahya Sattar , Samet Oymak

We consider a multidimensional time-homogeneous dynamical system and add a randomly perturbed time-dependent deterministic signal to some of its components, giving rise to a high-dimensional system of stochastic differential equations,…

Probability · Mathematics 2019-08-02 Simon Holbach

The Koopman operator framework can be used to identify a data-driven model of a nonlinear system. Unfortunately, when the data is corrupted by noise, the identified model can be biased. Additionally, depending on the choice of lifting…

Systems and Control · Electrical Eng. & Systems 2024-09-02 Louis Lortie , James Richard Forbes
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