  Reaction networks in the bulk and on surfaces are widespread in physical,
chemical and biological systems. In macroscopic systems, which include large
populations of reactive species, stochastic fluctuations are negligible and the
reaction rates can be evaluated using rate equations. However, many physical
systems are partitioned into microscopic domains, where the number of molecules
in each domain is small and fluctuations are strong. Under these conditions,
the simulation of reaction networks requires stochastic methods such as direct
integration of the master equation. However, direct integration of the master
equation is infeasible for complex networks, because the number of equations
proliferates as the number of reactive species increases. Recently, the
multiplane method, which provides a dramatic reduction in the number of
equations, was introduced [A. Lipshtat and O. Biham, Phys. Rev. Lett. 93,
170601 (2004)]. The reduction is achieved by breaking the network into a set of
maximal fully connected sub-networks (maximal cliques). Lower-dimensional
master equations are constructed for the marginal probability distributions
associated with the cliques, with suitable couplings between them. In this
paper we test the multiplane method and examine its applicability. We show that
the method is accurate in the limit of small domains, where fluctuations are
strong. It thus provides an efficient framework for the stochastic simulation
of complex reaction networks with strong fluctuations, for which rate equations
fail and direct integration of the master equation is infeasible. The method
also applies in the case of large domains, where it converges to the rate
equation results.
