Physics – Chemical Physics
Scientific paper
1995-07-05
Physics
Chemical Physics
29 Pages, uuencoded, compressed Dvi file, 89kB. pictures included as uuencoded, compressed tar file, 32 Kb full postscript ver
Scientific paper
10.1142/S0129183195000216
We describe a new algorithm for simulating complex Markoff-processes. We have used a reaction-cell method in order to simulate arbitrary reactions. It can be used for any kind of RDS on arbitrary topologies, including fractal dimensions or configurations not being related to any spatial geometry. The events within a single cell are managed by an event handler which has been implemented independently of the system studied. The method is exact on the Markoff level including the correct treatment of finite numbers of molecules. To demonstrate its properties, we apply it on a very simple reaction-diffusion-systems (RDS). The chemical equations A+A -> inert and A+B -> inert in 1 to 4 dimensions serve as models for systems whose dynamics on an intermediate time scale are governed by fluctuations. We compare our results to the analytic approach by the scaling ansatz. The simulations confirm the exponents of the A+B system within statistical errors, including the logarithmic corrections in the dimension d=2. The method is capable to simulate the crossover from the reaction to diffusion limited regime, which is defined by a crossover time depending on the system size.
Fricke Thomas
Wendt Dietmar
No associations
LandOfFree
The Markoff-Automaton - a New Algorithm for Simulating the Time--Evolution of Large Stochastic Dynamic Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with The Markoff-Automaton - a New Algorithm for Simulating the Time--Evolution of Large Stochastic Dynamic Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Markoff-Automaton - a New Algorithm for Simulating the Time--Evolution of Large Stochastic Dynamic Systems will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-538232