Recently it has been shown that when an equation that allows so-called pulled
fronts in the mean-field limit is modelled with a stochastic model with a
finite number N of particles per correlation volume, the convergence to the
speed v∗ for N→∞ is extremely slow -- going only as ln−2N.
However, this convergence is seen only for very high values of N, while there
can be significant deviations from it when N is not too large. Pulled fronts
are fronts that propagate into an unstable state, and the asymptotic front
speed is equal to the linear spreading speed v∗ of infinitesimal
perturbations around the unstable state. In this paper, we consider front
propagation in a simple stochastic lattice model. The microscopic picture of
the front dynamics shows that for the description of the far tip of the front,
one has to abandon the idea of a uniformly translating front solution. The
lattice and finite particle effects lead to a ``halt-and-go'' type dynamics at
the far tip of the front, while the average front behind it ``crosses over'' to
a uniformly translating solution. In this formulation, the effect of
stochasticity on the asymptotic front speed is coded in the probability
distribution of the times required for the advancement of the ``foremost
occupied lattice site''. These probability distributions are obtained by
matching the solution of the far tip with the uniformly translating solution
behind in a mean-field type approximation, and the results for the probability
distributions compare well to the results of stochastic numerical simulations.
This approach allows one to deal with much smaller values of N than it is
required to have the ln−2N asymptotics to be valid.Comment: 12 pages, 6 figures, intended proceedings for 3rd International
Conference Unsolved Problems of Noise (UPoN) and fluctuations in physics,
biology and high technology 2002; references update