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The blending region hybrid framework for the simulation of stochastic reaction-diffusion processes
Christian A Yates1, Adam George1, Armand Jordana2
1Department of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK.
Journal of the Royal Society, Interface
|October 21, 2020
Summary
This study introduces a hybrid simulation method combining coarse-grained and fine-grained models for reaction-diffusion systems. This approach efficiently handles large particle numbers and spatial variations, reducing computational cost.
Area of Science:
- Computational Biology
- Chemical Physics
- Mathematical Modeling
Background:
- Fine-grained simulations of stochastic reaction-diffusion systems are computationally expensive for large particle numbers.
- Coarse-grained models are efficient but may fail in multiscale systems with significant spatial concentration variations.
Purpose of the Study:
- To develop a hybrid simulation paradigm coupling coarse-grained and fine-grained models for reaction-diffusion systems.
- To enable accurate simulation of fine-scale dynamics in multiscale systems at reduced computational cost.
Main Methods:
- Implemented a hybrid model by allowing coarse-grained and fine-grained representations to overlap in a 'blending region'.
- Utilized complementary 'blending functions' to gradually transfer diffusion implementation control between models within the blending region.
Main Results:
- Demonstrated the reliability of the novel hybrid paradigm through simulations on four exemplar reaction-diffusion scenarios.
- The hybrid approach successfully balanced computational efficiency with accuracy for systems with varying spatial scales.
Conclusions:
- The proposed hybrid paradigm offers a computationally efficient and accurate method for simulating complex reaction-diffusion systems.
- This approach is particularly beneficial for multiscale systems where localized fine-grained detail is crucial.
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