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首页> 美国卫生研究院文献>Journal of the Royal Society Interface >Coupling volume-excluding compartment-based models of diffusion at different scales: Voronoi and pseudo-compartment approaches
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Coupling volume-excluding compartment-based models of diffusion at different scales: Voronoi and pseudo-compartment approaches

机译：耦合体积（不包括基于隔室的不同比例扩散模型）：Voronoi和伪隔室方法

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摘要

Numerous processes across both the physical and biological sciences are driven by diffusion. Partial differential equations are a popular tool for modelling such phenomena deterministically, but it is often necessary to use stochastic models to accurately capture the behaviour of a system, especially when the number of diffusing particles is low. The stochastic models we consider in this paper are ‘compartment-based’: the domain is discretized into compartments, and particles can jump between these compartments. Volume-excluding effects (crowding) can be incorporated by blocking movement with some probability. Recent work has established the connection between fine- and coarse-grained models incorporating volume exclusion, but only for uniform lattices. In this paper, we consider non-uniform, hybrid lattices that incorporate both fine- and coarse-grained regions, and present two different approaches to describe the interface of the regions. We test both techniques in a range of scenarios to establish their accuracy, benchmarking against fine-grained models, and show that the hybrid models developed in this paper can be significantly faster to simulate than the fine-grained models in certain situations and are at least as fast otherwise.
机译：物理和生物科学中的许多过程都是由扩散驱动的。偏微分方程是确定性地对这种现象进行建模的一种流行工具，但是经常需要使用随机模型来准确地捕获系统的行为，尤其是当扩散粒子的数量较少时。我们在本文中考虑的随机模型是“基于隔室的”：领域离散化为隔室，粒子可以在这些隔室之间跳跃。排除体积的效果（拥挤）可以通过一定程度地阻止运动来实现。最近的工作已经建立了包含体积排除的细粒度和粗粒度模型之间的联系，但仅适用于均匀晶格。在本文中，我们考虑了同时包含细粒度和粗粒度区域的非均匀混合晶格，并提出了两种不同的方法来描述区域的界面。我们在一系列场景中测试了这两种技术，以确立它们的准确性，并针对细粒度模型进行基准测试，结果表明，在某些情况下，本文开发的混合模型比细粒度模型的仿真速度要快得多，并且至少否则速度很快。

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