Preprint:
Optimal Reward on a Sparse Tree with Random Edge-Weights

D. Khoshnevisan and T. M. Lewis

Abstract. It is well known that the maximal displacement of a random walk indexed by an m-ary tree with bounded i.i.d. edge-weights can reliably yield much larger asymptotics than a classical random walk whose summands are drawn from the same distribution. Presently we show that if the edge-weights are mean-zero, then nonclassical asymptotics arise even when the tree grows much more slowly than subexponentially. Our conditions are stated in terms of a Minkowski-type logarithmic dimension of the boundary of the tree.

Keywords. Optimal reward, tree-indexed random walks, logarithmic dimension.

AMS Classification (2000). 60G50, 05C05.

Support. Research supported in part by grants from the U.S. National Science Foundation.

Pre/E-Prints. This paper is available in

Davar Khoshnevisan
Department of Mathematics
University of Utah
155 S, 1400 E JWB 233
Salt Lake City, UT 84112-0090, U.S.A.
davar@math.utah.edu
Thomas M. Lewis
Department of Mathematics
Furman University
Greenville, SC 29613, U.S.A.
tom.lewis@math.furman.edu

Last Update: July 22, 2002
© 2002 - Davar Khoshnevisan and Thomas M. Lewis