Difficulties for d Results for d

Lemma 2.3.1 Let K D be the set of continuous probability kernels on D, equip- ped with the topology of uniform convergence, and let K ′ D be the space of all positive linear operators K : C D → C D satisfying K 1 = 1, equipped with the strong operator topology. Then a homeomorfism between K D and K ′ D is given by K f x = K x | f f ∈ C D. 2.3.5 In particular, K n converges to K in the topology on K D if and only if K n f − K f → 0 ∀ f ∈ C D. 2.3.6 Proof of Lemma 2.3.1: Let K ∈ K D, and for f ∈ C D define K ′ f x : = K x | f . By the continuity of K , the function x → K x | f is continuous. It is obvious that the map f → K ′ f is positive and linear, and therefore continuous, and satisfies K ′ 1 = 1. Conversely, by the Riesz-Markov theorem [30], Theorem IV.14, each such K ′ defines a probability measure K x for each x ∈ D. Since K ′ f ∈ C D for each f ∈ C D, the map x → K x is continuous in the weak topology. Finally, P D is continuously imbedded in C D ∗ , the dual of C D, so K D is continuously imbedded in C D, C D ∗ , if we equip the latter with the topology of uniform convergence, where the uniform structure on C D ∗ is given by the semi-norms l → |l| f |. The topology of uniform convergence in C D, C D ∗ is then defined by the semi-norms p f f ∈ C D given by p f F = sup x ∈D |Fx| f | F ∈ C D, C D ∗ . 2.3.7 If K ∈ K D, then p f K = sup x ∈D |K x | f | = K f , so uniform convergence of probability kernels corresponds to convergence of the associated operators in the strong operator topology. From now on we identify kernels with linear operators as in 2.3.5. Since D is convex, the Dirichlet problem on D always has a solution. We shall be interested in harmonic functions and functions of constant Laplacian. Lemma 2.3.2 a For every φ ∈ C ∂ D there exists a unique f ∈ C D ∩ C 2 D that solves f = 0 on D f = φ on ∂ D. 2.3.8 The solution is given by f = H φ, 2.3.9 where H ∈ K D is the probability kernel given by H x d y = P[B x τ ∈ dy], 2.3.10 where B x t t ≥0 is Brownian motion starting at x and τ : = inf{t ≥ 0 : B x t ∈ ∂ D}. 2.3.11 b There exists a unique g ∗ ∈ C D ∩ C 2 D that solves − 1 2 g ∗ = 1 on D g ∗ = 0 on ∂ D. 2.3.12 The solution is given with τ as in 2.3.11 by g ∗ x = E x [τ ] 2.3.13 and satisfies g ∗ 0 on D. There exists an L ∞ such that g ∗ x ≤ L|x − y| ∀x ∈ D, y ∈ ∂ D. 2.3.14 Proof of Lemma 2.3.2: Formulas 2.3.9 and 2.3.10 can be found in [22], Propo- sition 4.2.7 and Theorems 4.2.12 and 4.2.19. For 2.3.13 see [22], Problem 4.2.25. The fact that g ∗ 0 on D can easily be deduced from the representation 2.3.13, but alternatively one may consult [29], Theorem 2.5. To prove 2.3.14, we assume without loss of generality that y = 0 and x 1 ∀x ∈ D, where for any x ∈ R d we write x = x 1 , . . . , x d . Now choose L such that |x − ˜x| ≤ L for all x, ˜x ∈ D. Define a stopping time ˜τ by ˜τ := inf{t ≥ 0 : B 1 t ∈ {0, L}}, 2.3.15 where B t = B 1 t , . . . , B d t is d-dimensional Brownian motion. By [22], Prob- lem 4.2.25, we have g ∗ x = E x [τ ] ≤ E x [ ˜τ] = x 1 L − x 1 ≤ Lx 1 ≤ L|x − y|. 2.3.16

2.3.3 Proof of Theorem 2.2.1

Theorem 2.2.1 follows directly from the following lemma. Formula 2.3.17 ii below will be essential for the rest of this section. Lemma 2.3.3 Fix g ∈ H ′ and c ∈ 0, ∞. For any θ ∈ D, denote by S t t ≥0 the Feller semigroup related to the solution X t t ≥0 of the martingale problem asso- ciated with A in 2.2.8, and let G be the full generator of S t t ≥0 . Then, for any

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