Physica A 168 (1990) 637-645
North-Holland
Ll~VY WALK APPROACH TO ANOMALOUS DIFFUSION
J. KLAFTER a, A. BLUMEN b, G. ZUMOFEN c and
M.F. SHLESINGER d
aSchool of Chemistry, Tel Aviv University, Tel Aviv 69978, Israel
bphysics Institute and B1MF, University of Bayreuth, D-8580, Bayreuth,
Fed. Rep. Germany
CLaboratorium fiir Physikalische Chemie, ETH-Zentrum, CH-8092 Ziirich, Switzerland
dphysics Division, Office of Naval Research, Arlington, VA 22217, USA
The transport properties of L6vy walks are discussed in the framework of continuous time
random walks (CTRW) with coupled memories. This type of walks may lead to anomalous
diffusion where the mean squared displacement (r2(t))~ t~ with ct ~ 1. We focus on the
enhanced diffusion limit, ct > 1, in one dimension and present our results on (r2(t)), the
mean number of distinct sites visited S(t) and P(r, t), the probability of being at position r at
time t.
1. Introduction
Recently there has been growing interest in systems that display anomalous
diffusion, a fact which is manifested through the dependence of the mean
squared displacement <r2(t)> on time. Whereas for simple diffusion (r2(t)) - t
holds, anomalous diffusion is characterized by [1-13]
(rZ(t)> ~ t ~
with a ~ 1. Cases with a < 1 (known as the dispersive transport regime) have
been the topic of many theoretical and experimental studies [11-15] and have
been related to the presence of geometrical (fractal) [12] or of temporal
disorder [13, 14]. For t~ < 1 it is established that the probability distributions
P(r, t) of being at position r at time t are generally non-Gaussian [16, 17]. In a
review article [14] we have summarized different scale-invaraint models-
continuous-time random walks (CTRW), fractals and ultrametric spaces-
which give rise to ot < 1.
Less explored has been the enchanced transport regime, which corresponds
to a > 1. Although a number of experimental and theoretical examples are
already well-documented, a basic theoretical framework for an overall descrip-
tion of enhanced transport is still missing. Examples for enhanced diffusion are
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