We present an efficient Monte Carlo method to simulate reaction-diffusion
processes with spatially varying particle annihilation or transformation rates
as it occurs for instance in the context of motor-driven intracellular
transport. Like Green's function reaction dynamics and first-passage time
methods, our algorithm avoids small diffusive hops by propagating sufficiently
distant particles in large hops to the boundaries of protective domains. Since
for spatially varying annihilation or transformation rates the single particle
diffusion propagator is not known analytically, we present an algorithm that
generates efficiently either particle displacements or annihilations with the
correct statistics, as we prove rigorously. The numerical efficiency of the
algorithm is demonstrated with an illustrative example.Comment: 13 pages, 5 figure