Improved spatial direct method with gradient-based diffusion to retain full diffusive fluctuations.
The spatial direct method with gradient-based diffusion is an accelerated stochastic reaction-diffusion simulation algorithm that treats diffusive transfers between neighboring subvolumes based on concentration gradients. This recent method achieved a marked improvement in simulation speed and reduction in the number of time-steps required to complete a simulation run, compared with the exact algorithm, by sampling only the net diffusion events, instead of sampling all diffusion events. Although the spatial direct method with gradient-based diffusion gives accurate means of simulation ensembles, its gradient-based diffusion strategy results in reduced fluctuations in populations of diffusive species. In this paper, we present a new improved algorithm that is able to anticipate all possible microscopic fluctuations due to diffusive transfers in the system and incorporate this information to retain the same degree of fluctuations in populations of diffusing species as the exact algorithm. The new algorithm also provides a capability to set the desired level of fluctuation per diffusing species, which facilitates adjusting the balance between the degree of exactness in simulation results and the simulation speed. We present numerical results that illustrate the recovery of fluctuations together with the accuracy and efficiency of the new algorithm.
Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia 22030, USA.
Wonryull
W
Koh
Kim T
KT
Blackwell
D000255:Adenosine Triphosphate / Q000378:metabolism; D000465:Algorithms; D000242:Cyclic AMP / Q000096:biosynthesis / Q000378:metabolism; D017868:Cyclic AMP-Dependent Protein Kinases / Q000378:metabolism; D004058:Diffusion; D004789:Enzyme Activation; D008954:Models, Biological; D011336:Probability; D013997:Time Factors
D000255:Adenosine Triphosphate; D000242:Cyclic AMP; D017868:Cyclic AMP-Dependent Protein Kinases