Definitions Convergence of the diffusion rate
4.4.4 An approximate equilibrium equation
Write i : = {ξ ∈ N i : ξ ≤ k i − 1} i ∈ N 4.4.37 for the k i − 1-block around the origin in the hierarchical group N i . For ˆ θ ∈ K and i ∈ N , we introduce an operator A i ˆθ with domain D A i ˆθ : = C 2 K i and A i ˆθ f x : = ξ ∈ i k i −1 k =1 c N i k −1 α [x k,α ξ − x α ξ ] ∂ ∂ x α ξ f x + ξ ∈ i gx ξ α ∂ ∂ x α ξ 2 f x + ξ ∈ i c N i k i −1 α [ ˆ θ α − x α ξ ] ∂ ∂ x α ξ f x = ξ ∈ i η ∈ i a i η − ξ α [x α η − x α ξ ] ∂ ∂ x α ξ f x + ξ ∈ i gx ξ α ∂ ∂ x α ξ 2 f x + ξ ∈ i c N i k i −1 α [ ˆ θ α − x α ξ ] ∂ ∂ x α ξ f x, 4.4.38 where a i ξ : = k i −1 k =ξ 1 N k i c N i k −1 ξ ∈ i . 4.4.39 Lemma 4.4.3 below gives us an estimate of how close the expectation of functions f i of large k i −1-blocks is to their equilibrium value with respect to the dynamics described by the operator A i x ki . Lemma 4.4.3 For i ∈ N let X N i be a solution of 4.1.5 with initial condition 4.4.22 and let τ i be as in Section 4.4.2. For i ∈ N , let f i ∈ C 2 K i , let ∇ ξ f i : = ∂ ∂ x α ξ f i α =1,...,d , 4.4.40 and let ∇ ξ f i ∞ be the supremum norm of |∇ ξ f i | the Euclidean norm of ∇ ξ f i . Then there exist constants M 1 , M 2 such that for all i ∈ N , x ∈ K Ni and ω ∈ C ξ i , K [0, ∞ E ω A i x ki f i X N i τ i ≤ 2λ −1 i f i ∞ + M 1 c k i −1 N 1 − 3 2 k i i λ 1 2 i + M 2 c k i N −k i i ξ ∈ i ∇ ξ f i ∞ . 4.4.41 Here, in the left-hand side of 4.4.41, we lift the function A i x k f i to the space K Ni in the obvious way. Proof of Lemma 4.4.3: Use the fact that the process M in 4.4.25 is a martingale and apply optional stopping to see that E ω [ f i X N i τ i ] − E ω [ f i X N i 0] = E ω τ i A f i X N i t dt , 4.4.42 where for x ∈ K Ni A f i x = ξ ∈ i ,α ∞ k =1 c N k −1 [x k,α ξ − x α ξ ] ∂ ∂ x α ξ f i x + ξ ∈ i ,α gx ξ ∂ ∂ x α ξ 2 f i x, 4.4.43 and we have lifted the function f i to K Ni in the obvious way. Note that ξ i ∈ i , so that in our summations we do not have to write ξ = ξ i .Parts
» largspscb. 826KB Jun 04 2011 12:09:08 AM
» The diffusion limit Particle models and diffusion limits
» Examples Particle models and diffusion limits
» The p-type q-tuple model with migration
» Uniqueness problems Particle models and diffusion limits
» Interacting p-type q-tuple models
» Other models Particle models and diffusion limits
» Renormalization theory Overview of the three articles
» Renormalization of interacting diffusions
» A renormalization transformation Overview of the three articles
» Higher-dimensional generalizations Overview of the three articles
» Renormalization of isotropic diffusions
» Non-isotropic models Overview of the three articles
» Harmonic functions and clustering
» Doing the iterations at once
» Non-invariant harmonics Open problems
» Renormalization on other lattices Discrete models
» Outlook and conclusion Open problems
» The hierarchical model Introduction
» The local mean-field limit N
» The renormalization transformation Introduction
» Multiple space-time scale analysis
» Large space-time behavior and universality
» Generalizations to different state spaces
» Isotropic models Renormalization in d
» Two renormalization classes: Theorems 2.2.5–2.2.10
» Difficulties for d Results for d
» Notation Preliminaries The renormalization transformation
» Proof of Theorem 2.2.1 The renormalization transformation
» Proof of Theorems 2.2.2–2.2.4 The renormalization transformation
» Ergodicity: Proof of Theorem 2.2.5
» Existence: Proof of Theorem 2.2.6 Strong uniqueness: Proof of Theorem 2.2.9
» Weak uniqueness: Proof of Theorem 2.2.10
» Definitions Introduction and main results
» Existence and uniqueness: Theorems 3.1.1 and
» Biological background Introduction and main results
» The non-interacting model Introduction and main results
» Clustering: Theorem 3.1.3 Introduction and main results
» Covariance calculations: Lemma 3.1.4 Introduction and main results
» Universality of the long-time distribution: Theorem 3.1.5
» Harmonic functions: Lemma 3.1.6 Introduction and main results
» Special models: Corollary 3.1.7 Examples
» Proof of Theorem 3.1.1 Proofs of Theorems 3.1.1 and 3.1.2
» Proof of Theorem 3.1.2 Proofs of Theorems 3.1.1 and 3.1.2
» Proof of Lemma 3.1.4 Proofs of Theorem 3.1.3 and Lemma 3.1.4
» Random walk representations Proofs of Theorem 3.1.3 and Lemma 3.1.4
» Spatially ergodic measures Proofs of Theorem 3.1.3 and Lemma 3.1.4
» Proof of Theorem 3.1.3 Proofs of Theorem 3.1.3 and Lemma 3.1.4
» Potential theory Proofs of Theorem 3.1.5, Lemma 3.1.6
» Infinite-dimensional differentiation Proofs of Theorem 3.1.5, Lemma 3.1.6
» Proof of Lemma 3.1.6 Proofs of Theorem 3.1.5, Lemma 3.1.6
» Proof of Theorem 3.1.5 Proofs of Theorem 3.1.5, Lemma 3.1.6
» Proof of Corollary 3.1.7 Proofs of Theorem 3.1.5, Lemma 3.1.6
» Finite largspscb. 826KB Jun 04 2011 12:09:08 AM
» Definitions Introduction and main result
» Main scaling theorem Introduction and main result
» Identification of the drift and diffusion rate of ˆ
» Definitions Convergence of the diffusion rate
» Block immobility Convergence of the diffusion rate
» An approximate equilibrium equation
» Equilibrium calculations Convergence of the diffusion rate
» Asymptotics of the scaling factor µ
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