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Spectral dynamics of guided edge removals and identifying transient amplifiers for death–Birth updating

机译:引导边缘去除的频谱动力学和识别死亡瞬态放大器 - 出生更新

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Abstract The paper deals with two interrelated topics: (1) identifying transient amplifiers in an iterative process, and (2) analyzing the process by its spectral dynamics, which is the change in the graph spectra by edge manipulation. Transient amplifiers are networks representing population structures which shift the balance between natural selection and random drift. Thus, amplifiers are highly relevant for understanding the relationships between spatial structures and evolutionary dynamics. We study an iterative procedure to identify transient amplifiers for death–Birth updating. The algorithm starts with a regular input graph and iteratively removes edges until desired structures are achieved. Thus, a sequence of candidate graphs is obtained. The edge removals are guided by quantities derived from the sequence of candidate graphs. Moreover, we are interested in the Laplacian spectra of the candidate graphs and analyze the iterative process by its spectral dynamics. The results show that although transient amplifiers for death–Birth updating are generally rare, a substantial number of them can be obtained by the proposed procedure. The graphs identified share structural properties and have some similarity to dumbbell and barbell graphs. We analyze amplification properties of these graphs and also two more families of bell-like graphs and show that further transient amplifiers for death–Birth updating can be found. Finally, it is demonstrated that the spectral dynamics possesses characteristic features useful for deducing links between structural and spectral properties. These feature can also be taken for distinguishing transient amplifiers among evolutionary graphs in general.
机译:摘要 本文涉及两个相互关联的主题:(1)识别迭代过程中的瞬态放大器,以及(2)通过其频谱动力学分析该过程,即通过边缘操纵对图谱的变化。瞬态放大器是代表种群结构的网络,它改变了自然选择和随机漂移之间的平衡。因此,放大器对于理解空间结构和进化动力学之间的关系高度相关。我们研究了一种迭代程序来识别死亡的瞬态放大器——出生更新。该算法从常规输入图开始,并迭代删除边,直到实现所需的结构。因此,获得了候选图的序列。边缘去除由从候选图形序列中得出的量指导。此外,我们对候选图的拉普拉斯谱感兴趣,并通过其谱动力学分析了迭代过程。结果表明,尽管用于死亡-出生更新的瞬态放大器通常很少见,但通过所提出的程序可以获得大量瞬态放大器。识别出的图形具有相同的结构特性,并且与哑铃和杠铃图有一些相似之处。我们分析了这些图的放大特性以及另外两个钟形图家族,并表明可以找到更多用于死亡-出生更新的瞬态放大器。最后,证明了光谱动力学具有有助于推导结构和光谱特性之间联系的特征。这些特征也可用于区分一般演化图中的瞬态放大器。

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