论文标题

带有应用程序的星形图上的捕获问题

Trapping problem on star-type graphs with applications

论文作者

Ma, Fei, Wang, Ping

论文摘要

过去,图形(或网络)上的诱捕问题是典型的兴趣重点,这引起了过去的各种科学领域的更多关注,包括应用数学和理论计算机科学。在这里,我们首先在任意图上研究了此问题,并获得了计算平均陷阱时间($ att $)理论下限的闭合形式公式,该数量是使用光谱图理论的方法评估所讨论图的捕获效率的数量。结果表明,陷阱位置的选择对确定参数$ att $有重大影响。结果,我们考虑了Star-Type图上的问题,这是一个特殊的图形家族,它将以单个陷阱$θ$进行引入,然后使用概率生成函数得出数量$ ATT $的精确解决方案。我们的结果表明,通过实现$ ATT $的相应理论下限,所有星形型图具有最佳的捕获效率。更重要的是,我们进一步发现,只有在考虑诱捕问题时,给定的图是最佳的,它的基础结构是星形型。同时,我们还以众所周知的持有人不平等为$ ATT $的上限,其中有些是锋利的。通过使用所有获得的后果,人们可能能够为复杂网络设计更好的控制方案,从诱捕效率的尊重,这与许多其他以前的想法都非常吻合。

The trapping problem on graph (or network) as a typical focus of great interest has attracted more attention from various science fields, including applied mathematics and theoretical computer science, in the past. Here, we first study this problem on an arbitrary graph and obtain the closed-form formula for calculating the theoretical lower bound of average trapping time ($ATT$), a quantity that evaluates trapping efficiency of graph in question, using methods from spectral graph theory. The results show that the choice of the trap's location has a significant influence on determining parameter $ATT$. As a result, we consider the problem on star-type graphs, a special graph family which will be introduced shortly, with a single trap $θ$ and then derive using probability generating functions the exact solution to quantity $ATT$. Our results suggest that all star-type graphs have most optimal trapping efficiency by achieving the corresponding theoretical lower bounds of $ATT$. More importantly, we further find that a given graph is most optimal only if its underlying structure is star-type when considering the trapping problem. At meantime, we also provide the upper bounds for $ATT$ of several graphs in terms of well-known Holder inequality, some of which are sharp. By using all the consequences obtained, one may be able to design better control scheme for complex networks from respect of trapping efficiency, to some extent, which are in well agreement with many other previous thoughts.

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