The speed of biased random walk on percolation clusters

 We consider biased random walk on supercritical percolation clusters in ℤ². We show that the random walk is transient and that there are two speed regimes: If the bias is large enough, the random walk has speed zero, while if the bias is small enough, the speed of the random walk is positive. Received: 20 November 2002 / Revised version: 17 January 2003 Published online: 15 April 2003 Research supported by Microsoft Research graduate fellowship. Research partially supported by the DFG under grant SPP 1033. Research partially supported by NSF grant #DMS-0104073 and by a Miller Professorship at UC Berkeley. Mathematics Subject Classification (2000): 60K37; 60K35; 60G50 Key words or phrases: Percolation – Random walk     

Quenched invariance principle for simple random walk on percolation clusters

We consider the simple random walk on the (unique) infinite cluster of super-critical bond percolation in ℤ ^d with d≥2. We prove that, for almost every percolation configuration, the path distribution of the walk converges weakly to that of non-degenerate, isotropic Brownian motion. Our analysis is based on the consideration of a harmonic deformation of the infinite cluster on which the random walk becomes a square-integrable martingale. The size of the deformation, expressed by the so called corrector, is estimated by means of ergodicity arguments.     

Parabolic Harnack inequality and heat kernel estimates for random walks with long range jumps

We investigate the relationships between the parabolic Harnack inequality, heat kernel estimates, some geometric conditions, and some analytic conditions for random walks with long range jumps. Unlike the case of diffusion processes, the parabolic Harnack inequality does not, in general, imply the corresponding heat kernel estimates. M. T. Barlow’s research was partially supported by NSERC (Canada), the twenty-first century COE Program in Kyoto University (Japan), and by EPSRC (UK). R. F. Bass’s research was partially supported by NSF Grant DMS-0601783. T. Kumagai’s research was partially supported by the Grant-in-Aid for Scientific Research (B) 18340027 (Japan).     

Simple random walk on the line in random environment

Summary We obtain strong limiting bounds for the maximal excursion and for the maximum reached by a random walk in a random environment. Our results derive from a simple proof of Pólya's theorem for the recurrence of the random walk on the line. As applications, we obtain bounds for the number of visits of the random walk at the origin.     

Biased random walk in a one-dimensional percolation model

We consider random walk with a nonzero bias to the right, on the infinite cluster in the following percolation model: take i.i.d. bond percolation with retention parameter p$p$ on the so-called infinite ladder, and condition on the event of having a bi-infinite path from −∞$-\infty$ to ∞$\infty$. The random walk is shown to be transient, and to have an asymptotic speed to the right which is strictly positive or zero depending on whether the bias is below or above a certain critical value which we compute explicitly.     

On the range of random walk

Let {S _n , n=0, 1, 2, …} be a random walk (S _n being thenth partial sum of a sequence of independent, identically distributed, random variables) with values inE _d , thed-dimensional integer lattice. Letf _n =Prob {S ₁ ≠ 0, …,S _n −1 ≠ 0,S _n =0 |S ₀=0}. The random walk is said to be transient if and strongly transient if . LetR _n =cardinality of the set {S ₀,S ₁, …,S _n }. It is shown that for a strongly transient random walk with p<1, the distribution of [R _n −np]/σ √n converges to the normal distribution with mean 0 and variance 1 asn tends to infinity, where σ is an appropriate positive constant. The other main result concerns the “capacity” of {S ₀, …,S _n }. For a finite setA inE _d , let C(A=Σ _x∈A ) Prob {S _n ∉A, n≧1 |S ₀=x} be the capacity ofA. A strong law forC{S ₀, …,S _n } is proved for a transient random walk, and some related questions are also considered. This research was partially supported by the National Science Foundation.     

Global heat kernel bounds via desingularizing weights

We obtain global heat kernel bounds for semigroups which need not be ultracontractive by transferring them to appropriately chosen weighted spaces where they become ultracontractive. Our construction depends upon two assumptions: the classical Sobolev imbedding and a “desingularizing” (L¹,L¹) bound on the weighted semigroup.     

The range of two-parameter random walk in space

Summary Let {X _ij; i>0, j>0} be a double sequence of i.i.d. random variables taking values in the d-dimensional integer lattice E _d . Also let . Then the range of random walk {S _mn: m>0, n>0} up to time (m, n), denoted by R _mn , is the cardinality of the set {S _pq: 0m, n). In this paper a sufficient condition in terms of the characteristic function of X ₁₁ is given so that a.s. as either (m, n) or m(n) tends to infinity.     

Evolving sets, mixing and heat kernel bounds

We show that a new probabilistic technique, recently introduced by the first author, yields the sharpest bounds obtained to date on mixing times of Markov chains in terms of isoperimetric properties of the state space (also known as conductance bounds or Cheeger inequalities). We prove that the bounds for mixing time in total variation obtained by Lovász and Kannan, can be refined to apply to the maximum relative deviation |pⁿ(x,y)/π(y)−1| of the distribution at time n from the stationary distribution π. We then extend our results to Markov chains on infinite state spaces and to continuous-time chains. Our approach yields a direct link between isoperimetric inequalities and heat kernel bounds; previously, this link rested on analytic estimates known as Nash inequalities.Research supported in part by NSF Grants #DMS-0104073 and #DMS-0244479.     

Recurrence time and range for a generalized random walk

The notions of recurrence time, range, and the limit of probabilities P_k of return to the origin arise in the study of random walks on groups. We examine these notions and develop relationships among them in an ergodic theory setting in which the usual requirement of independence of the increments of the random walk can be relaxed to simply an ergodic requirement. Thus we consider generalized random walks or GRWs. The ergodic theory setting is related to Mackey's virtual group theory in that the GRW determines a virtual group homomorphism (or cocycle). We relate the condition- that the homomorphism is trivial (the cocycle is a coboundary) to the Cesáro limit of P_k. The basic ideas of virtual group theory were established by Mackey and further developed by Ramsay. Our virtual group homomorphism result does not require familiarity with the technicalities of virtual group theory.     

THE RANGE OF RANDOM WALK ON TREES AND RELATED TRAPPING PROBLEM

1.IntroductionLetTNbetheinfinitetreewithN 1branchesemanatingfromeachvertex.Namely,TNisaninfiniteconnectedgraphwithnonon-trivialclosedloopsinwhicheverynodebelongstoexactlyN Iedges.SinceTIcanbethoughtofasaonedimensionallattice,whichhasbeenwellstudied,throug…     

On gradient bounds for the heat kernel on the Heisenberg group

It is known that the couple formed by the two-dimensional Brownian motion and its Lévy area leads to the heat kernel on the Heisenberg group, which is one of the simplest sub-Riemannian space. The associated diffusion operator is hypoelliptic but not elliptic, which makes difficult the derivation of functional inequalities for the heat kernel. However, Driver and Melcher and more recently H.-Q. Li have obtained useful gradient bounds for the heat kernel on the Heisenberg group. We provide in this paper simple proofs of these bounds, and explore their consequences in terms of functional inequalities, including Cheeger and Bobkov type isoperimetric inequalities for the heat kernel.     

Slow movement of a random walk on the range of a random walk in the presence of an external field

In this article, a localisation result is proved for the biased random walk on the range of a simple random walk in high dimensions ( $d\ge 5$ ). This demonstrates that, unlike in the supercritical percolation setting, a slowdown effect occurs as soon as a non-trivial bias is introduced. The proof applies a decomposition of the underlying simple random walk path at its cut-times to relate the associated biased random walk to a one-dimensional random walk in a random environment in Sinai’s regime. Via this approach, a corresponding aging result is also proved.     

Gaussian heat kernel upper bounds via the Phragmen-Lindelof theorem

We prove that in the presence of L² Gaussian estimates, theso-called Davies–Gaffney estimates, on-diagonal upperbounds imply precise off-diagonal Gaussian upper bounds forthe kernels of analytic families of operators on metric measurespaces.