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The scaling invariance for chaotic orbits near a transition from unlimited to limited diffusion in a dissipative standard mapping is explained via the analytical solution of the diffusion equation. It gives the probability of observing a…

Chaotic Dynamics · Physics 2020-12-02 Edson D. Leonel , Celia Mayumi Kuwana , Makoto Yoshida , Juliano Antonio de Oliveira

We explore the properties of discrete-time stochastic processes with a bounded state space, whose deterministic limit is given by a map of the unit interval. We find that, in the mesoscopic description of the system, the large jumps between…

Statistical Mechanics · Physics 2016-11-22 César Parra-Rojas , Joseph D. Challenger , Duccio Fanelli , Alan J. McKane

We consider the effect of noise on the dynamics generated by volume-preserving maps on a d-dimensional torus. The quantity we use to measure the irreversibility of the dynamics is the dissipation time. We focus on the asymptotic behaviour…

Dynamical Systems · Mathematics 2009-11-10 A. Fannjiang , S. Nonnenmacher , L. Wolowski

A continuous map $f$ from a compact interval $I$ into itself is densely (resp. generically) chaotic if the set of points $(x,y)$ such that $\limsup_{n\to+\infty}|f^n(x)-f^n(y)|>0$ and $\liminf_{n\to+\infty} |f^n(x)-f^n(y)|=0$ is dense…

Dynamical Systems · Mathematics 2019-01-09 Sylvie Ruette

We study linear statistics of a class of determinantal processes which interpolate between Poisson and GUE/Ginibre statistics in dimension 1 or 2. These processes are obtained by performing an independent Bernoulli percolation on the…

Probability · Mathematics 2019-07-23 Gaultier Lambert

We study the mixing time of a random walk on the torus, alternated with a Lebesgue measure preserving Bernoulli map. Without the Bernoulli map, the mixing time of the random walk alone is $O(1/\epsilon^2)$, where $\epsilon$ is the step…

Probability · Mathematics 2023-03-28 Gautam Iyer , Ethan Lu , James Nolen

Recently, there has been an increasing interest on nonautonomous composition of perturbed hyperbolic systems: composing perturbations of a given hyperbolic map $F$ results in statistical behaviour close to that of $F$. We show this fact in…

Dynamical Systems · Mathematics 2017-06-02 Matteo Tanzi , Tiago Pereira , Sebastian van Strien

We study random dynamical systems generated by volume-preserving piecewise $C^{1}$ maps. For this class of systems, we establish an invariance principle stating that if all Lyapunov exponents vanish, then there exists a measurable family of…

Dynamical Systems · Mathematics 2026-01-21 Gianluigi Del Magno , João Lopes Dias , José Pedro Gaivão

Chaotic deterministic dynamics of a particle can give rise to diffusive Brownian motion. In this paper, we compute analytically the diffusion coefficient for a particular two-dimensional stochastic layer induced by the kicked Harper map.…

chao-dyn · Physics 2008-02-03 P. Leboeuf

We discuss asymptotics for large random planar maps under the assumption that the distribution of the degree of a typical face is in the domain of attraction of a stable distribution with index $\alpha\in(1,2)$. When the number $n$ of…

Probability · Mathematics 2017-08-23 Jean-François Le Gall , Grégory Miermont

A sequential importance sampling algorithm is developed for the distribution that results when a matrix of independent, but not identically distributed, Bernoulli random variables is conditioned on a given sequence of row and column sums.…

Computation · Statistics 2013-01-18 Matthew T. Harrison , Jeffrey W. Miller

We consider transport properties of the chaotic (strange) attractor along unfolded trajectories of the dissipative standard map. It is shown that the diffusion process is normal except of the cases when a control parameter is close to some…

Chaotic Dynamics · Physics 2009-11-13 G. M. Zaslavsky , M. Edelman

The work [8] established memory loss in the time-dependent (non-random) case of uniformly expanding maps of the interval. Here we find conditions under which we have convergence to the normal distribution of the appropriately scaled…

Dynamical Systems · Mathematics 2016-03-25 Peter Nandori , Domokos Szasz , Tamas Varju

Here we study the long time behavior of an advection-diffusion equation with a general time varying (including random) shear flow imposing no-flux boundary conditions on channel walls. We derive the asymptotic approximation of the scalar…

Fluid Dynamics · Physics 2021-09-14 Lingyun. Ding , Richard M. McLaughlin

For a Markov process associated with a diffusion type Dirichlet form an upper bound is shown for the law of the finite dimensional distributions of the process. Under some more assumptions on the underlaying space this is also shown for the…

Probability · Mathematics 2009-07-28 Ann-Kathrin Jarecki

We study a stochastically perturbed version of the well-known Krasnoselski--Mann iteration for computing fixed points of nonexpansive maps in finite dimensional normed spaces. We discuss sufficient conditions on the stochastic noise and…

Optimization and Control · Mathematics 2023-04-04 Mario Bravo , Roberto Cominetti

We analyse the so-called Marginal Instability of linear switching systems, both in continuous and discrete time. This is a phenomenon of unboundedness of trajectories when the Lyapunov exponent is zero. We disprove two recent conjectures of…

Dynamical Systems · Mathematics 2014-11-04 Vladimir Y. Protasov , Raphael M. Jungers

We consider certain one dimensional ordinary stochastic differential equations driven by additive Brownian motion of variance $\varepsilon ^2$. When $\varepsilon =0$ such equations have an unstable non-hyperbolic fixed point and the drift…

Probability · Mathematics 2015-09-30 Giambattista Giacomin , Mathieu Merle

We consider the dynamics of `nonlinear tent maps': piecewise smooth unimodal maps with nowhere vanishing derivative. We show that if a nonlinear tent map $f$ is not infinitely renormalizable, then all its periodic orbits of sufficiently…

Dynamical Systems · Mathematics 2016-09-06 Ale Jan Homburg

This paper introduces Discrete Markov Probabilistic Models (DMPMs), a novel discrete diffusion algorithm for discrete data generation. The algorithm operates in discrete bit space, where the noising process is a continuous-time Markov chain…

Machine Learning · Statistics 2025-10-09 Le-Tuyet-Nhi Pham , Dario Shariatian , Antonio Ocello , Giovanni Conforti , Alain Durmus