AVALANCHES IN A SHORT-MEMORY EXCITABLE NETWORK.

Pub Date : 2021-09-01 Epub Date: 2021-10-08 DOI:10.1017/apr.2021.2
Reza Rastegar, Alexander Roitershtein
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Abstract

We study propagation of avalanches in a certain excitable network. The model is a particular case of the one introduced in [24], and is mathematically equivalent to an endemic variation of the Reed-Frost epidemic model introduced in [28]. Two types of heuristic approximation are frequently used for models of this type in applications, a branching process for avalanches of a small size at the beginning of the process and a deterministic dynamical system once the avalanche spreads to a significant fraction of a large network. In this paper we prove several results concerning the exact relation between the avalanche model and these limits, including rates of convergence and rigorous bounds for common characteristics of the model.

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雪崩在短记忆兴奋网络。
研究雪崩在某可激网络中的传播。该模型是[24]中引入的模型的一个特例,在数学上等同于[28]中引入的Reed-Frost流行病模型的地方性变异。在应用中,两种类型的启发式近似经常用于这种类型的模型,一种是在过程开始时小规模雪崩的分支过程,另一种是雪崩扩散到大网络的重要部分时的确定性动力系统。在本文中,我们证明了关于雪崩模型和这些极限之间的确切关系的几个结果,包括收敛速度和模型共同特征的严格界限。
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