Acknowledgements Irreducible bounded symmetric random walks

1.4 Acknowledgements

I would like to thank Wendelin Werner for suggesting this problem to me. This work was done while I was a graduate student at the University of Chicago and I am very grateful to my advisors Steve Lalley and Greg Lawler for all their patient help and guidance. 2 Definitions and background

2.1 Irreducible bounded symmetric random walks

Throughout this paper, Λ will be a two-dimensional discrete lattice of R 2 . In other words, Λ is an additive subgroup of R 2 not generated by a single element such that there exists an open neighbor- hood of the origin whose intersection with Λ is just the origin. It can be shown see for example [16, Proposition 1.3.1] that Λ is isomorphic as a group to Z 2 . Now suppose that V ⊂ Λ \ {0} is a finite generating set for Λ with the property that the first nonzero component of every x ∈ V is positive. Suppose that κ : V → 0, 1 is such that X x ∈V κx ≤ 1. Let px = p −x = κx2 for x ∈ V and p0 = 1 − P x ∈V κx. Define the random walk S with distribution p to be S n = X 1 + X 2 + · · · + X n . where the random variables X k are independent with distribution p. Then S is a symmetric, irre- ducible random walk with bounded increments. It is a Markov chain with transition probabilities px, y = p y − x. If X = X 1 , X 2 has distribution p, then Γ i, j = E ” X i X j — i, j = 1, 2 is the covariance matrix associated to S. There exists a unique symmetric positive definite matrix A such that Γ = A 2 . Therefore, if e S j = A −1 S j , then e S is a random walk on the discrete lattice A −1 Λ with covariance matrix the identity. Since a linear transformation of a circle is an ellipse, it is clear that if we can show that the growth exponent α 2 is 5 4 for random walks whose covariance matrix is the identity, then α 2 will be 5 4 for random walks with arbitrary covariance matrix. Therefore, to simplify notation and proofs, throughout the paper S will denote a symmetric, irreducible random walk on a discrete lattice Λ with bounded increments and covariance matrix equal to the identity.

2.2 A note about constants

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