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Stochastic Growths Models and Hamilton-Jacobi Equations
Probability| Speaker: | Prof. Fraydoun Rezakhanlou, UC Berkeley |
| Location: | 693 Kerr |
| Start time: | Tue, Nov 14 2000, 3:10PM |
Description
I will discuss law of large numbers and central limit theorem for a class of
growth
models that includes a well studied particle system known as simple exclusion
process.
Given a function $v:{Bbb Z}^d o {Bbb N}$, we define the space of
configurations to be
the set of height functions $h:{Bbb Z}^d o {Bbb Z}$ such that
$h(i)-h(j)le v(i-j)$.
A $v$-exclusion process is a Markov process with the following stochastic rules:
At a site $i$ the height $h(i)$ increases (respect. decreases) by one unit
with rate
$lambda^+$ (respect. $lambda^-$) provided that the resulting height
function is still
in the configuration space, otherwise the increase (respect. decrease) is
suppressed.
Under some conditions on $v$, the rescaled height function
$u^{epsilon}(x,t)=epsilon
h([frac xepsilon],frac tepsilon)$ converges to a deterministic function
$u(x,t)$
that satisfies a Hamilton-Jacobi equation of the form $u_t+H(u_x)=0$.
If the growth
rates change with space, the corresponding equation is of the form
$u_t+H(x,u,u_x)=0$.
Such a Hamilton-Jacobi eqution is not well-posed in general. However, the above
growth model leads to a variational formula for the limit $u$.
When $v(i)=i^+$, the $v$-exclusion model is the celebrated simple exclusion
process.
In this case, I will discuss a central limit theorem for the convergence of
$u^epsilon$ to $u$.
