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首页> 外文期刊>Journal of nonlinear science >Diffusive Search for Diffusing Targets with Fluctuating Diffusivity and Gating
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Diffusive Search for Diffusing Targets with Fluctuating Diffusivity and Gating

机译:扩散搜索漫射漫射和门控的漫射目标

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The time that it takes a diffusing particle to find a small target has emerged as a critical quantity in many systems in molecular and cellular biology. In this paper, we extend the theory for calculating this time to account for several ubiquitous biological features which have largely been ignored in the mathematics and physics literature on this problem. In particular, we allow (i) targets to diffuse on the two-dimensional boundary of the three-dimensional domain, (ii) targets to diffuse in the interior of the domain, (iii) the diffusivities of the searcher particle and the targets to stochastically fluctuate, (iv) targets to be stochastically gated, and (v) the transition times between fluctuations in diffusivity and gating to have effectively any probability distribution. In this general framework, we analytically calculate the leading order behavior of the mean first passage time and splitting probability for the searcher to reach a target as the target size decays, which is the so-called narrow escape limit. To make these extensions, we use a generalized Ito's formula to derive a system of coupled partial differential equations which are satisfied by statistics of the process, where the size of the system and its spatial dimension can be arbitrarily large. We apply matched asymptotic analysis to this system and verify our analytical results by numerical simulation. Our results reveal several new features and generic principles of diffusive search for small targets.
机译:漫射颗粒在分子和细胞生物学中的许多系统中出现了漫射粒子所需的时间。在本文中,我们延长了计算这一时间的理论,以考虑在这个问题上大部分忽视的几种无处不在的生物学特征。特别地,我们允许(i)旨在扩散在三维域的二维边界上,(ii)靶向域内部扩散,(iii)搜索者粒子和目标的扩散性随机波动,(iv)目标是随机门控的,(v)(v)漫射率波动之间的转变时间和门控与有效的概率分布有效。在这一总体框架中,我们分析了Searcher的平均第一通道时间和分割概率的前导顺序行为,以达到目标作为目标尺寸衰减,这是所谓的窄逃避限制。为了使这些扩展来看,我们使用广义ITO的公式来推导一个耦合的部分微分方程系统,该系统满足了该过程的统计数据,其中系统的尺寸及其空间尺寸可以是任意大的。我们将匹配的渐近分析应用于该系统,并通过数值模拟验证我们的分析结果。我们的结果揭示了几种新的特征和通用原则的扩散搜索小目标。

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