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Fluctuations of a Surface Submitted to a Random Average Process

  
@article{EJP28,
	author = {P.A. Ferrari and L. Fontes},
	title = {Fluctuations of a Surface Submitted to a Random Average Process},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {3},
	year = {1998},
	keywords = {random average process, random surfaces, product of random  matrices, linear process, voter model, smoothing process},
	abstract = {We consider a hypersurface of dimension $d$ imbedded in a $d+1$ dimensional  space. For each $x\in Z^d$, let $\eta_t(x)\in R$ be the height of the  surface at site $x$ at time $t$. At rate $1$ the $x$-th height is updated to  a random convex combination of the heights of the `neighbors' of $x$. The  distribution of the convex combination is translation invariant and does not  depend on the heights. This motion, named the random average process (RAP),  is one of the linear processes introduced by Liggett (1985). Special  cases of RAP are a type of smoothing process (when the convex combination is  deterministic) and the voter model (when the convex combination concentrates  on one site chosen at random). We start the heights located on a hyperplane  passing through the origin but different from the trivial one $\eta(x)\equiv  0$. We show that, when the convex combination is neither deterministic nor  concentrating on one site, the variance of the height at the origin at time  $t$ is proportional to the number of returns to the origin of a symmetric  random walk of dimension $d$. Under mild conditions on the distribution of  the random convex combination, this gives variance of the order of $t^{1/2}$  in dimension $d=1$, $\log t$ in dimension $d=2$ and bounded in $t$ in  dimensions $d\ge 3$. We also show that for each initial hyperplane the  process as seen from the height at the origin converges to an invariant  measure on the hyper surfaces conserving the initial asymptotic slope. The  height at the origin satisfies a central limit theorem. To obtain the  results we use a corresponding probabilistic cellular automaton for which  similar results are derived. This automaton corresponds to the product of  (infinitely dimensional) independent random matrices whose rows are  independent.},
	pages = {no. 6, 1-34},
	issn = {1083-6489},
	doi = {10.1214/EJP.v3-28},    
        url = {http://ejp.ejpecp.org/article/view/28}}