We present an algorithm for adaptive mesh refinement applied to mesoscopic stochastic simulations of spatially evolving reaction-diffusion processes. The transition rates for the diffusion process are derived on adaptive, locally refined structured meshes. Convergence of the diffusion process is presented and the fluctuations of the stochastic process are verified. Furthermore, a refinement criterion is proposed for the evolution of the adaptive mesh. The method is validated in simulations of reaction-diffusion processes as described by the Fisher-Kolmogorov and Gray-Scott equations
actants is used to compute the time evolution of reactant concentrations. The stochastic algorithm i...
The reaction-diffusion master equation is a stochastic model often utilized in the study of biochemi...
Quantitative descriptions of reaction kinetics formulated at the stochastic mesoscopic level are fre...
Stochastic models of chemical systems are often analysed by solving the corresponding Fokker-Planck ...
Stochastic models of chemical systems are often analyzed by solving the corresponding Fokker--Planck...
Stochastic models of chemical systems are often analyzed by solving the corresponding Fokker--Planck...
Stochastic simulations of reaction-diffusion processes are used extensively for the modeling of comp...
Abstract. We construct a hybrid particle/continuum algorithm for linear diffusion in the fluctuating...
Spatial distributions characterize the evolution of reaction-diffusion models of several physical, c...
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrody...
Stochastic modelling is critical for studying many biochemical processes in a cell, in particular wh...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
Abstract-Modern numerical process simulators are becom-ing increasingly complicated in both physical...
The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simula...
The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simula...
actants is used to compute the time evolution of reactant concentrations. The stochastic algorithm i...
The reaction-diffusion master equation is a stochastic model often utilized in the study of biochemi...
Quantitative descriptions of reaction kinetics formulated at the stochastic mesoscopic level are fre...
Stochastic models of chemical systems are often analysed by solving the corresponding Fokker-Planck ...
Stochastic models of chemical systems are often analyzed by solving the corresponding Fokker--Planck...
Stochastic models of chemical systems are often analyzed by solving the corresponding Fokker--Planck...
Stochastic simulations of reaction-diffusion processes are used extensively for the modeling of comp...
Abstract. We construct a hybrid particle/continuum algorithm for linear diffusion in the fluctuating...
Spatial distributions characterize the evolution of reaction-diffusion models of several physical, c...
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrody...
Stochastic modelling is critical for studying many biochemical processes in a cell, in particular wh...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
Abstract-Modern numerical process simulators are becom-ing increasingly complicated in both physical...
The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simula...
The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simula...
actants is used to compute the time evolution of reactant concentrations. The stochastic algorithm i...
The reaction-diffusion master equation is a stochastic model often utilized in the study of biochemi...
Quantitative descriptions of reaction kinetics formulated at the stochastic mesoscopic level are fre...