MESOSCOPIC MODELING OF STOCHASTIC REACTION-DIFFUSION KINETICS IN THE SUBDIFFUSIVE REGIME.

IF 1.9 4区 数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Multiscale Modeling & Simulation Pub Date : 2016-01-01 Epub Date: 2016-05-03 DOI:10.1137/15M1013110
Emilie Blanc, Stefan Engblom, Andreas Hellander, Per Lötstedt
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引用次数: 9

Abstract

Subdiffusion has been proposed as an explanation of various kinetic phenomena inside living cells. In order to fascilitate large-scale computational studies of subdiffusive chemical processes, we extend a recently suggested mesoscopic model of subdiffusion into an accurate and consistent reaction-subdiffusion computational framework. Two different possible models of chemical reaction are revealed and some basic dynamic properties are derived. In certain cases those mesoscopic models have a direct interpretation at the macroscopic level as fractional partial differential equations in a bounded time interval. Through analysis and numerical experiments we estimate the macroscopic effects of reactions under subdiffusive mixing. The models display properties observed also in experiments: for a short time interval the behavior of the diffusion and the reaction is ordinary, in an intermediate interval the behavior is anomalous, and at long times the behavior is ordinary again.

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亚扩散状态下随机反应扩散动力学的介观模拟。
人们提出用亚扩散来解释活细胞内的各种动力学现象。为了促进亚扩散化学过程的大规模计算研究,我们将最近提出的亚扩散介观模型扩展到一个准确和一致的反应-亚扩散计算框架中。揭示了两种不同的可能的化学反应模型,并推导了一些基本的动力学性质。在某些情况下,这些介观模型在宏观层面上可以直接解释为有界时间区间内的分数阶偏微分方程。通过分析和数值实验,估计了亚扩散混合条件下反应的宏观效应。模型显示了在实验中也观察到的性质:在短时间间隔内,扩散和反应的行为是正常的,在中间时间间隔内,行为是异常的,在长时间内,行为又恢复正常。
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来源期刊
Multiscale Modeling & Simulation
Multiscale Modeling & Simulation 数学-数学跨学科应用
CiteScore
2.80
自引率
6.20%
发文量
45
审稿时长
6-12 weeks
期刊介绍: Centered around multiscale phenomena, Multiscale Modeling and Simulation (MMS) is an interdisciplinary journal focusing on the fundamental modeling and computational principles underlying various multiscale methods. By its nature, multiscale modeling is highly interdisciplinary, with developments occurring independently across fields. A broad range of scientific and engineering problems involve multiple scales. Traditional monoscale approaches have proven to be inadequate, even with the largest supercomputers, because of the range of scales and the prohibitively large number of variables involved. Thus, there is a growing need to develop systematic modeling and simulation approaches for multiscale problems. MMS will provide a single broad, authoritative source for results in this area.
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