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Let $\tau: I=[0, 1]\to [0, 1]$ be a piecewise convex map with countably infinite number of branches. In \cite{GIR}, the existence of absolutely continuous invariant measure (ACIM) $\mu$ for $\tau$ and the exactness of the system $(\tau,…

Dynamical Systems · Mathematics 2024-05-07 Md Shafiqul Islam , Paweł Góra , A H M Mahbubur Rahman

We present a rigorous numerical scheme for the approximation of the linear response of the invariant density of a map with an indifferent fixed point, with explicit and computed estimates for the error and all the involved constants.

Dynamical Systems · Mathematics 2022-06-03 Isaia Nisoli , Toby Taylor-Crush

In this paper we present a general, axiomatical framework for the rigorous approximation of invariant densities and other important statistical features of dynamics. We approximate the system trough a finite element reduction, by composing…

Dynamical Systems · Mathematics 2023-04-05 Stefano Galatolo , Maurizio Monge , Isaia Nisoli , Federico Poloni

We use Ulam's method to provide rigorous approximation of diffusion coefficients for uniformly expanding maps. An algorithm is provided and its implementation is illustrated using Lanford's map.

Dynamical Systems · Mathematics 2016-04-13 Wael Bahsoun , Stefano Galatolo , Isaia Nisoli , Xiaolong Niu

In this article we study a piecewise linear discretization schemes for transfer operators (Perron-Frobenius operators) associated with interval maps. We show how these can be used to provide rigorous {\bf pointwise} approximations for…

Dynamical Systems · Mathematics 2010-08-04 Wael Bahsoun , Christopher Bose

Ulam's method is a rigorous numerical scheme for approximating invariant densities of dynamical systems. The phase space is partitioned into connected sets and an inter-set transition matrix is computed from the dynamics; an approximate…

Dynamical Systems · Mathematics 2013-02-05 Christopher Bose , Gary Froyland , Cecilia González-Tokman , Rua Murray

We describe a framework in which is possible to develop and implement algorithms for the approximation of invariant measures of dynamical systems with a given bound on the error of the approximation. Our approach is based on a general…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli

For random piecewise linear systems T of the interval that are expanding on average we construct explicitly the density functions of absolutely continuous T-invariant measures. In case the random system uses only expanding maps our…

Dynamical Systems · Mathematics 2023-06-22 Charlene Kalle , Marta Maggioni

For a map of the unit interval with an indifferent fixed point, we prove an upper bound for the variance of all observables of $n$ variables $K:[0,1]^n\to\R$ which are componentwise Lipschitz. The proof is based on coupling and decay of…

Dynamical Systems · Mathematics 2009-08-27 J. -R. Chazottes , P. Collet , F. Redig , E. Verbitskiy

We establish stability of random absolutely continuous invariant measures (acims) for cocycles of random Lasota-Yorke maps under a variety of perturbations. Our family of random maps need not be close to a fixed map; thus, our results can…

Dynamical Systems · Mathematics 2012-12-12 Gary Froyland , Cecilia González-Tokman , Anthony Quas

A method is introduced for the construction of meshless discretization schemes which preserve Lie symmetries of the differential equations that these schemes approximate. The method exploits the fact that equivariant moving frames provide a…

Mathematical Physics · Physics 2015-06-11 Alexander Bihlo

This paper is concerned with the optimal approximation of a given multivariate Dirac mixture, i.e., a density comprising weighted Dirac distributions on a continuous domain, by an equally weighted Dirac mixture with a reduced number of…

Systems and Control · Computer Science 2014-11-18 Uwe D. Hanebeck

Weakly chaotic maps with unstable fixed points are investigated in the regime where the invariant density is non-normalizable. We propose that the infinite invariant density of these maps can be estimated using as the long time limit of…

Statistical Mechanics · Physics 2013-09-03 Nickolay Korabel , Eli Barkai

This is a detailed analysis of invariant measures for one-dimensional dynamical systems with random switching. In particular, we prove smoothness of the invariant densities away from critical points and describe the asymptotics of the…

Dynamical Systems · Mathematics 2015-10-28 Yuri Bakhtin , Tobias Hurth , Jonathan C. Mattingly

This paper generalizes the results of [13] and then provides an interesting example. We construct a family of $W$-like maps $\{W_a\}$ with a turning fixed point having slope $s_1$ on one side and $-s_2$ on the other. Each $W_a$ has an…

Dynamical Systems · Mathematics 2013-10-18 Zhenyang Li

The approximation of invariant measures for nonlinear ergodic stochastic differential equations (SDEs) is a central problem in scientific computing, with important applications in stochastic sampling, physics, and ecology. We first propose…

Numerical Analysis · Mathematics 2025-11-18 Shan Huang , Xiaoyue Li

Invariant discretization schemes are derived for the one- and two-dimensional shallow-water equations with periodic boundary conditions. While originally designed for constructing invariant finite difference schemes, we extend the usage of…

Mathematical Physics · Physics 2013-01-04 Alexander Bihlo , Roman O. Popovych

In the class of nonlinear one-parameter real maps we study those with bifurcation that exhibits period doubling cascade. The fixed points of such a map form a finite discrete real set with dimension (2^n)m, where m is the (odd) number of…

Mathematical Physics · Physics 2009-11-11 A. D. Alhaidari

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

Given $iid$ observations from an unknown absolute continuous distribution defined on some domain $\Omega$, we propose a nonparametric method to learn a piecewise constant function to approximate the underlying probability density function.…

Machine Learning · Statistics 2018-03-13 Dangna Li , Kun Yang , Wing Hung Wong
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