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Stochastic processes and their applications, 2006-12, Vol.116 (12), p.1876-1891
Ort / Verlag
Amsterdam: Elsevier B.V
Erscheinungsjahr
2006
Link zum Volltext
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
We consider the path
Z
t
described by a standard Brownian motion in
R
d
on some time interval
[
0
,
t
]
. This is a random compact subset of
R
d
. Using the support (curvature) measures of [D. Hug, G. Last, W. Weil, A local Steiner-type formula for general closed sets and applications, Math. Z. 246 (2004) 237–272] we introduce and study two mean curvature functions of Brownian motion. The geometric interpretation of these functions can be based on the Wiener sausage
Z
⊕
r
t
of radius
r
>
0
which is the set of all points
x
∈
R
d
whose Euclidean distance
d
(
Z
t
,
x
)
from
Z
t
is at most
r
. The mean curvature functions can be easily expressed in terms of the Gauss and mean curvature of
Z
⊕
r
t
as integrated over the positive boundary of
Z
⊕
r
t
. We will show that these are continuous functions of locally bounded variation. A consequence is that the volume of
Z
⊕
r
t
is almost surely differentiable at any fixed
r
>
0
with the derivative given as the content of the positive boundary of
Z
⊕
r
t
. This will imply that also the expected volume of
Z
⊕
r
t
is differentiable with the derivative given as the expected content of the positive boundary of
Z
⊕
r
t
. In fact it has been recently shown in [J. Rataj, V. Schmidt, E. Spodarev, On the expected surface area of the Wiener sausage (2005) (submitted for publication)
http://www.mathematik.uni-ulm.de/stochastik/] that for
d
≤
3
the derivative is just the expected surface content of
Z
⊕
r
t
and that for
d
≥
4
this is true at least for almost all
r
>
0
. The paper [J. Rataj, V. Schmidt, E. Spodarev, On the expected surface area of the Wiener sausage (2005) (submitted for publication)
http://www.mathematik.uni-ulm.de/stochastik/] then proceeds to use a result from [A.M. Berezhkovskii, Yu.A. Makhnovskii, R.A. Suris, Wiener sausage volume moments, J. Stat. Phys. 57 (1989) 333–346] to get explicit formulae for this expected surface content. We will use here this result to derive a linear constraint on the mean curvature functions. For
d
=
3
we will provide a more detailed analysis of the mean curvature functions based on a classical formula in [F. Spitzer, Electrostatic capacity, heat flow, and Brownian motion, Z. Wahrscheinlichkeitstheorie und Verw. Gebiete 3 (1964) 110–121].