Exit-Problem for a Class of Non-Markov Processes With Path Dependency: Proofs of Auxiliary Lemmas

We take a closer look at our proofs of Auxiliary Lemmas.


This content originally appeared on HackerNoon and was authored by Class Path

Abstract and 1 Introduction

1.1 State of the art

1.2 Some remarks on dynamics and initial condition

1.3 Outline of the paper

1.4 List of notations

2 Large Deviation Principle

2.1 Establishing the LDP for the SID

2.2 Results related to the LDP

2.3 Compactness results

3 Exit-time

3.1 Auxiliary results

3.2 Proof of the main theorem

3.3 Proofs of auxiliary lemmas

4 Generalization and References

3.3 Proofs of auxiliary lemmas

3.3.1 Proof of Lemma 3.1: Initial descent to the point of attraction

3.3.2 Proof of Lemma 3.2: Convergence of deterministic process towards a

\

\

\ Then, by Grönwall’s inequality:

\

\

\ That guarantees exponentially fast convergence towards 0:

\

\

.3.3.3 Proof of Lemma 3.3: Attraction of stochastic process towards a

\ And this concludes the proof of the lemma.

3.3.4 Proof of Lemma 3.4: Behaviour in the annulus between Bρ(a) and ∂G

\

3.3.5 Proof of Lemma 3.5: Stabilization of the occupation measure

\ Proof. The proof of the following lemma follow the same logic as the one of Lemma 3.3.

\

\ We have to show now that

\

\ This completes the proof.

\ Now we are ready to prove Lemma 3.5 itself.

\

\ That gives us:

\

\

\ We recall that Lemma 3.9 establishes the following asymptotic behaviour for small σ:

\

\

\ Let us first deal with the term B. By (3.22), we have

\

\ Consider now A. Separate each probability inside the sum the following way

\

\

3.3.6 Proof of Lemma 3.6: Exit before nearing a

First, we show that it is possible to establish a lower bound for

\

\

\ By Lemma 2.5,

\

\ which proves the lemma by taking ρ → 0.

3.3.7 Proof of Lemma 3.7: Control of dynamics for small time intervals

\ Use the Jensen’s inequality, integrate the second part of the last integral over s, and get:

\

\ We apply Grönwall’s inequality and get:

\

\ Thus, it follows that, for the absolute value of the Brownian motion itself,

\

\

\ Taking into account these remarks, we can now use the Schilder theorem [DZ10, Lemma 5.2.1] that provides the LDP for the path of the Brownian motion. Hence, for some fixed ϵ and 0 < T < 1:

\

\ where d is the dimension of the space.

\ Note that for any ϵ > 0 the following limit holds:

\

3.3.8 Proof of Lemma 3.8: Uniform lower bound for probability of exit from G

\

\

\

\

\

\

\

\

\

\

:::info This paper is available on arxiv under CC BY-SA 4.0 DEED license.

:::

:::info Authors:

(1) Ashot Aleksian, Université Jean Monnet, Institut Camille Jordan, 23, rue du docteur Paul Michelon, CS 82301, 42023 Saint-Étienne Cedex 2, France;

(2) Aline Kurtzmann, Université de Lorraine, CNRS, Institut Elie Cartan de Lorraine UMR 7502, Vandoeuvre-lès-Nancy, F-54506, France;

(3) Julian Tugaut, Université Jean Monnet, Institut Camille Jordan, 23, rue du docteur Paul Michelon, CS 82301, 42023 Saint-Étienne Cedex 2, France.

:::

\


This content originally appeared on HackerNoon and was authored by Class Path


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