论文标题
连续时间数字搜索树和边框聚合模型
Continuous time digital search tree and a border aggregation model
论文作者
论文摘要
我们考虑了随机数字搜索树的连续时间版本，并与Thacker和Volkov（2018）研究的边框聚合模型构建耦合，显示了树高度与聚集所需的时间之间的关系。这种关系将延续到相应的离散时间模型。结果，我们使用Drmota等人（2020）对数字搜索树的最新结果找到了聚集时间非常精确的渐近结果。
We consider the continuous-time version of the random digital search tree, and construct a coupling with a border aggregation model as studied in Thacker and Volkov (2018), showing a relation between the height of the tree and the time required for aggregation. This relation carries over to the corresponding discrete-time models. As a consequence we find a very precise asymptotic result for the time to aggregation, using recent results by Drmota et al.\ (2020) for the digital search tree.
