Asymptotic behavior of a stationary silo with absorbing walls

Details Asymptotic behavior of a stationary silo with absorbing walls Asymptotic behavior of a stationary silo with absorbing walls

2001-04-03

arxiv.org/abs/math/0104043v2

J. Statist. Phys. 106 (2002), no. 3-4, 521--546

Mathematics

Probability

23 pages, 3 figures. Revised version after referee reports. Main changes: extended introduction, some extra references, and so

Scientific paper

10.1023/A:1013702220938

We study the nearest neighbors one dimensional uniform q-model of force fluctuations in bead packs [Coppersmith et al (1996)], a stochastic model to simulate the stress of granular media in two dimensional silos. The vertical coordinate plays the role of time, and the horizontal coordinate the role of space. The process is a discrete time Markov process with state space $\R^{\{1,...,N\}}$. At each layer (time), the weight supported by each grain is a random variable of mean one (its own weight) plus the sum of random fractions of the weights supported by the nearest neighboring grains at the previous layer. The fraction of the weight given to the right neighbor of the successive layer is a uniform random variable in $[0,1]$ independent of everything. The remaining weight is given to the left neighbor. In the boundaries, a uniform fraction of the weight leans on the wall of the silo. This corresponds to \emph{absorbing boundary conditions}. For this model we show that there exists a unique invariant measure. The mean weight at site $i$ under the invariant measure is $i(N+1-i)$; we prove that its variance is $\frac12(i(N+1-i))^2 + O(N^3)$ and the covariances between grains $i\neq j$ are of order $O(N^3)$. Moreover, as $N\to\infty$, the law under the invariant measure of the weights divided by $N^2$ around site (integer part of) $rN$, $r\in (0,1)$, converges to a product of gamma distributions with parameters 2 and $2(r(1-r))^{-1}$ (sum of two exponentials of mean $r(1-r)/2$). Liu {\it et al} (1995) proved that for a silo with infinitely many weightless grains, any product of gamma distributions with parameters 2 and $2/\rho$ with $\rho\in [0,\infty)$ are invariant. Our result shows that as the silo grows, the model selects exactly one of these Gamma's at each macroscopic place.

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