Work

Exponential loss of memory for random Lasota--Yorke convex maps with local average expansion

Year: 2026

Type: preprint

Abstract: We study i.i.d. random compositions of piecewise convex interval maps whose first branch is full. Uniform expansion is not required, and the maps may have contracting branches. Under a local average expansion condition at the origin, we prove both quenched and annealed exponential loss of memory for initial densities of bounded variation. The proof is based on a coupling argument. As applications, we obtain the quenched almost sure invariance principle and a rate of convergence in the quenched central limit theorem.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.25037

Authors: Cui, Hongfei, Leppänen, Juho

Institutions: Wuhan University of Science and Technology, Tokai University

Language: English

Topic: Mathematical Dynamics and Fractals

Subfield: Mathematical Physics

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: Hubei Provincial Department of Education, National Natural Science Foundation of China, Wuhan University of Science and Technology, Japan Society for the Promotion of Science

Awards: G225105005, G8541507302

OpenAlex ID: W7223042910

Cites: 1

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Related to: 10