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In this paper we study the appearance of bifurcations of limit cycles in an epidemic model with two types of aware individuals. All the transition rates are constant except for the alerting decay rate of the most aware individuals and the…

Populations and Evolution · Quantitative Biology 2023-05-03 David Juher , David Rojas , Joan Saldaña

We study fluctuations of the Wigner time delay for open (scattering) systems which exhibit mixed dynamics in the classical limit. It is shown that in the semiclassical limit the time delay fluctuations have a distribution that differs…

Chaotic Dynamics · Physics 2010-03-09 J. P. Keating , A. M. Ozorio de Almeida , S. D. Prado , M. Sieber , R. Vallejos

In this paper, we derive general theorems for controlling (vector-valued) first order ordinary differential equations such that its solutions stop at a finite time $T>0$ and apply them to relaxation and dissipative oscillation processes. We…

Analysis of PDEs · Mathematics 2019-03-18 Richard Kowar

Fractional diffusion equations are widely used to describe anomalous diffusion processes where the characteristic displacement scales as a power of time. For processes lacking such scaling the corresponding description may be given by…

Statistical Mechanics · Physics 2007-05-23 I. M. Sokolov , A. V. Chechkin , J. Klafter

A generic saddle-node bifurcation is proposed to modelize fast transitions of finite amplitude arising in geophysical (and perhaps other) contexts, when they result from the intrinsic dynamics of the system. The fast transition is…

Chaotic Dynamics · Physics 2012-09-10 Yves Pomeau , Martine Le Berre

In this paper we study supercritical super-OU processes with general branching mechanisms satisfying a second moment condition. We establish central limit theorems for the super-OU processes. In the small and crtical branching rate cases,…

Probability · Mathematics 2013-02-07 Yan-Xia Ren , Renming Song , Rui Zhang

Delayed processes are ubiquitous in biological systems and are often characterized by delay differential equations (DDEs) and their extension to include stochastic effects. DDEs do not explicitly incorporate intermediate states associated…

Quantitative Methods · Quantitative Biology 2016-09-28 Jingchen Feng , Stuart Sevier , Bin Huang , Dongya Jia , Herbert Levine

Functional limit theorems are presented for the rescaled occupation time fluctuations process of a critical finite variance branching particle system in $R^d$ with symmetric a-stable motion starting off from either a standard Poisson random…

Probability · Mathematics 2009-11-04 Piotr Milos

This article introduces, and reviews recent work using, a simple optimisation technique for analysing the nonlinear stability of a state in a dynamical system. The technique can be used to identify the most efficient way to disturb a system…

Fluid Dynamics · Physics 2014-08-18 R. R. Kerswell , C. C. T. Pringle , A. P. Willis

Current fluctuations in boundary-driven diffusive systems are, in many cases, studied using hydrodynamic theories. Their predictions are then expected to be valid for currents which scale inversely with the system size. To study this…

Statistical Mechanics · Physics 2016-05-26 Yongjoo Baek , Yariv Kafri , Vivien Lecomte

We propose a new class of parameterizations for spatio-temporal point processes which leverage Neural ODEs as a computational method and enable flexible, high-fidelity models of discrete events that are localized in continuous time and…

Machine Learning · Computer Science 2021-03-19 Ricky T. Q. Chen , Brandon Amos , Maximilian Nickel

In this review, an outline of the so called Freidlin-Wentzell theory and its recent extensions is given. Broadly, this theory studies the exponential rate at which the probabilities of rare events related to random perturbation of ODE…

Probability · Mathematics 2014-06-24 Sergio A. Almada Monter

The limiting slow dynamics of slow-fast, piecewise-linear, continuous systems of ODEs occurs on critical manifolds that are piecewise-linear. At points of non-differentiability, such manifolds are not normally hyperbolic and so the…

Dynamical Systems · Mathematics 2018-01-16 David J. W. Simpson

Diffusion, a fundamental internal mechanism emerging in many physical processes, describes the interaction among different objects. In many learning tasks with limited training samples, the diffusion connects the labeled and unlabeled data…

Machine Learning · Computer Science 2023-05-02 Tangjun Wang , Zehao Dou , Chenglong Bao , Zuoqiang Shi

In recent years the theory of border collision bifurcations has been developed for piecewise smooth maps that are continuous across the border, and has been successfully applied to explain nonsmooth bifurcation phenomena in physical…

Chaotic Dynamics · Physics 2011-10-13 Biswambhar Rakshit , Manjul Apratim , Parag Jain , Soumitro Banerjee

Critical transitions occur in a wide variety of applications including mathematical biology, climate change, human physiology and economics. Therefore it is highly desirable to find early-warning signs. We show that it is possible to…

Dynamical Systems · Mathematics 2015-03-17 Christian Kuehn

For many physical systems the transition from a stationary solution to sustained small amplitude oscillations corresponds to a Hopf bifurcation. For systems involving impacts, thresholds, switches, or other abrupt events, however, this…

Dynamical Systems · Mathematics 2019-05-07 David J. W. Simpson

Some ODE models treat ecological disturbance as a continuous process, even disturbances such as fire that occur almost instantaneously on the timescale of system recovery. Alternatively, flow-kick models resolve disturbances as discrete…

Dynamical Systems · Mathematics 2024-12-09 Katherine Meyer , Horace Fusco , Collin Smith , Alanna Hoyer-Leitzel

In this paper we investigate the long time behavior of a family of diffusion processes with H\"older continuous diffusion terms on a compact set, these process arise naturally in random approximations of an ODE. We will prove that these…

Probability · Mathematics 2014-11-04 Bastien Marmet

This paper explores the efficacy of diffusion-based generative models as neural operators for partial differential equations (PDEs). Neural operators are neural networks that learn a mapping from the parameter space to the solution space of…

Machine Learning · Computer Science 2024-12-17 Katsiaryna Haitsiukevich , Onur Poyraz , Pekka Marttinen , Alexander Ilin