随机矩阵
特征向量
理论(学习稳定性)
透视图(图形)
基质(化学分析)
生态学
理论生态学
应用数学
光学(聚焦)
随机场
限制
领域(数学)
数学
工作(物理)
统计物理学
计算机科学
纯数学
生物
统计
人工智能
物理
人口
材料科学
社会学
光学
工程类
复合材料
量子力学
机器学习
热力学
机械工程
人口学
作者
Stefano Allesina,Si Tang
标识
DOI:10.1007/s10144-014-0471-0
摘要
Abstract Since the work of Robert May in 1972, the local asymptotic stability of large ecological systems has been a focus of theoretical ecology. Here we review May's work in the light of random matrix theory, the field of mathematics devoted to the study of large matrices whose coefficients are randomly sampled from distributions with given characteristics. We show how May's celebrated “stability criterion” can be derived using random matrix theory, and how extensions of the so‐called circular law for the limiting distribution of the eigenvalues of large random matrix can further our understanding of ecological systems. Our goal is to present the more technical material in an accessible way, and to provide pointers to the primary mathematical literature on this subject. We conclude by enumerating a number of challenges, whose solution is going to greatly improve our ability to predict the stability of large ecological networks.
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