By Darwin C. G.

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Privault is the Poisson kernel on S(y, r). In this case we have µ = σry , which is the normalized surface measure on S(y, r), and the Martin boundary ∆B(y, r) of B(y, r) equals its usual boundary S(y, r). 1 Markov Property Let C0 (Rn ) denote the class of continuous functions tending to 0 at infinity. Recall that f is said to tend to 0 at infinity if for all ε > 0 there exists a compact subset K of Rn such that |f (x)| ≤ ε for all x ∈ Rn \K. 1. e. a family (Xt )t∈R+ of random variables on a probability space (Ω, F , P ), is a Markov process if for all t ∈ R+ the σ-fields Ft+ := σ(Xs : s ≥ t) and Ft := σ(Xs : 0 ≤ s ≤ t).

0 ii) If 0 ≤ t ≤ a we have for all bounded Ft -measurable random variable F : ∞ IE F us dMs = IE [F G(Mb − Ma )] = 0, 0 hence ∞ IE ∞ us dMs Ft = IE [G(Mb − Ma )|Ft ] = 0 = 0 1[0,t] (s)us dMs . 0 This statement is extended by linearity and density, since from the continuity of the conditional expectation on L2 we have: ∞ t us dMs − IE IE 0 2 us dMs Ft 0 ∞ t uns dMs − IE = lim IE n→∞ 0 0 ∞ = lim IE n→∞ IE n→∞ n→∞ 2 us dMs Ft 0 2 (uns − us )dMs 0 ∞ = lim IE n→∞ ∞ uns dMs − 0 ∞ 2 us dMs Ft 0 ∞ ≤ lim IE IE ∞ uns dMs − 0 ≤ lim IE 2 us dMs Ft |uns − us |2 ds 0 = 0.

S. non-negative random variable τ is called a stopping time with respect to a filtration Ft if {τ ≤ t} ∈ Ft , t > 0. The σ-algebra Fτ is defined as the collection of measurable sets A such that A ∩ {τ < t} ∈ Ft for all t > 0. Note that for all s > 0 we have {τ < s}, {τ ≤ s}, {τ > s}, {τ ≥ s} ∈ Fτ . 4. s. 5) for all bounded measurable f . The hitting time τB of a Borel set B ⊂ Rn is defined as τB = inf{t > 0 : Xt ∈ B}, with the convention inf ∅ = +∞. A set B such that Px (τB < ∞) = 0 for all x ∈ Rn is said to be polar.

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