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Polynomial Random Dynamical Systems with Complete Connections and the Probability of Tending to Infinity

Yoshiyuki Endo

Abstract

We study polynomial random dynamical systems with complete connections on the Riemann sphere. In this framework, the choice of the next polynomial map is governed by a state-dependent rule with memory, extending both i.i.d. random dynamics and non-i.i.d. Markovian models. For each initial state, we define the probability that the random orbit tends to infinity. We prove that it is locally constant on the Fatou set, and that if all kernel Julia sets are empty, then it is continuous on the whole space. We also introduce stationary-averaged escaping probabilities with respect to stationary distributions of the induced state chain. Under the same kernel-emptiness assumption, these averaged probabilities are continuous. In addition, for each point of the Riemann sphere, the set of all possible stationary-averaged values is shown to be a compact interval determined by ergodic stationary distributions. We further give a sufficient condition for the stationary-averaged escaping probability to be everywhere positive and nontrivial. Finally, we provide examples showing RSCC-specific phenomena, including reinforcement-induced discontinuity, recovery of continuity under truncation, and genuinely mixed escaping behavior produced by stationary averaging.

Polynomial Random Dynamical Systems with Complete Connections and the Probability of Tending to Infinity

Abstract

We study polynomial random dynamical systems with complete connections on the Riemann sphere. In this framework, the choice of the next polynomial map is governed by a state-dependent rule with memory, extending both i.i.d. random dynamics and non-i.i.d. Markovian models. For each initial state, we define the probability that the random orbit tends to infinity. We prove that it is locally constant on the Fatou set, and that if all kernel Julia sets are empty, then it is continuous on the whole space. We also introduce stationary-averaged escaping probabilities with respect to stationary distributions of the induced state chain. Under the same kernel-emptiness assumption, these averaged probabilities are continuous. In addition, for each point of the Riemann sphere, the set of all possible stationary-averaged values is shown to be a compact interval determined by ergodic stationary distributions. We further give a sufficient condition for the stationary-averaged escaping probability to be everywhere positive and nontrivial. Finally, we provide examples showing RSCC-specific phenomena, including reinforcement-induced discontinuity, recovery of continuity under truncation, and genuinely mixed escaping behavior produced by stationary averaging.
Paper Structure (13 sections, 16 theorems, 135 equations)

This paper contains 13 sections, 16 theorems, 135 equations.

Key Result

Theorem 2.3

Let $\{(W,\mathcal{W}), (X,\mathcal{X}), u, P\}$ be an RSCC, and fix an arbitrary state $w_{0}\in W$. Then there exists a unique probability measure $\mathbf{P}_{w_{0}}$ on $(X^{\mathbb{N}}, \mathcal{X}^{\mathbb{N}})$ and a sequence of $X$-valued random variables $(\xi_{n})_{n\in\mathbb{N}}$ defined where $\xi^{(n)}=(\xi_{1},\ldots,\xi_{n})$, $\zeta_{n}=w_{0}\xi^{(n)}$, and $\zeta^{(n)}=(\zeta_{1}

Theorems & Definitions (36)

  • Definition 2.1: MR1070097
  • Theorem 2.3: MR1070097
  • Definition 2.5: MR1070097
  • Definition 2.6
  • Definition 2.7
  • Definition 2.11
  • Definition 2.12
  • Definition 2.14: Transition operator
  • Lemma 2.15
  • Definition 2.16
  • ...and 26 more