TY - JOUR
T1 - Dynamic renormalization group and noise induced transitions in a reaction diffusion model
AU - Zorzano, M.P.
AU - Hochberg, D.
AU - Morán, F.
PY - 2004
Y1 - 2004
N2 - We investigate how additive weak noise (correlated as well as uncorrelated) modifies the parameters of the Gray–scott reaction diffusion system by performing numerical simulations and applying a renormalization group (RG) analysis in the neighborhood of the spatial scale where biochemical reactions take place. One can obtain the same sequence of spatial–temporal patterns by means of two equivalent routes: (i) by increasing only the noise intensity and keeping all other model parameters fixed; or (ii) keeping the noise fixed, and adjusting certain model parameters to their running scale-dependent values as predicted by the RG. This explicit demonstration validates the dynamic RG transformation for finite scales in a two-dimensional stochastic model and provides further physical insight into the coarse-graining analysis proposed by this scheme. Through several study cases we explore the role of noise and its temporal correlation in self-organization and propose a way to drive the system into a new desired state in a controlled way.
AB - We investigate how additive weak noise (correlated as well as uncorrelated) modifies the parameters of the Gray–scott reaction diffusion system by performing numerical simulations and applying a renormalization group (RG) analysis in the neighborhood of the spatial scale where biochemical reactions take place. One can obtain the same sequence of spatial–temporal patterns by means of two equivalent routes: (i) by increasing only the noise intensity and keeping all other model parameters fixed; or (ii) keeping the noise fixed, and adjusting certain model parameters to their running scale-dependent values as predicted by the RG. This explicit demonstration validates the dynamic RG transformation for finite scales in a two-dimensional stochastic model and provides further physical insight into the coarse-graining analysis proposed by this scheme. Through several study cases we explore the role of noise and its temporal correlation in self-organization and propose a way to drive the system into a new desired state in a controlled way.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-0942277597&partnerID=MN8TOARS
U2 - 10.1016/j.physa.2003.10.064
DO - 10.1016/j.physa.2003.10.064
M3 - Article
SN - 0378-4371
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -