Invariance principle for biased Boostrap Random Walk
Andrea Collevecchio, Kais Hamza, Yunxuan Liu

TL;DR
This paper investigates the long-term behavior of a process generated by cellular automata applied to biased random walk increments, establishing invariance principles and analyzing transience and recurrence properties.
Contribution
It introduces a novel cellular automata-based construction for dependent Bernoulli sequences derived from biased random walks and studies their asymptotic behavior.
Findings
Establishes transience and recurrence criteria for the process.
Proves an invariance principle for the constructed process.
Reveals directional dependence and surprising features in the limiting behavior.
Abstract
Our main goal is to study a class of processes whose increments are generated via a cellular automata rule. Given the increments of a simple biased random walk, a new sequence of (dependent) Bernoulli random variables is produced. It is built, from the original sequence, according to a cellular automata rule. Equipped with these two sequences, we construct two more according to the same cellular automata rule. The construction is repeated a fixed number of times yielding an infinite array () of (dependent) Bernoulli random variables. %In turn, using this new sequence as input, we reiterate a construction of a new sequence. %This process is repeated a finite number of times resulting in an infinite array, herein called the "downward process", of highly dependent Bernoulli random variables. The process of taking partial products can be reversed allowing to…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Cellular Automata and Applications · Mathematical Dynamics and Fractals
