Given a set $P$ of $n$ points in the plane, we consider the problem of computing the number of points of $P$ in a query unit disk (i.e., all query disks have the same radius). We show that the main techniques for simplex range searching in the plane can be adapted to this problem. For example, by adapting Matou\v{s}ek's results, we can build a data structure of $O(n)$ space so that each query can be answered in $O(\sqrt{n})$ time. Our techniques lead to improvements for several other classical problems, such as batched range searching, counting/reporting intersecting pairs of unit circles, distance selection, discrete 2-center, etc. For example, given a set of $n$ unit disks and a set of $n$ points in the plane, the batched range searching problem is to compute for each disk the number of points in it. Previous work [Katz and Sharir, 1997] solved the problem in $O(n^{4/3}\log n)$ time while our new algorithm runs in $O(n^{4/3})$ time.
翻译:鉴于飞机上固定的1美元点数,我们考虑在查询单位磁盘中计算1美元点数的问题(即,所有盘盘都具有相同的半径)。我们显示,在飞机上简单范围搜索的主要技术可以适应这个问题。例如,通过调整Matou\v{s}k的结果,我们可以建造一个数据结构为O(n)美元的空间,以便每个查询都能用$(sqrt{n})时间回答。我们的技术导致若干其他古老问题的改进,例如分批范围的搜索、计数/报告单位圆的对对交叉切、远程选择、离心2分点等。例如,考虑到一套单位磁盘和飞机上一组美元点数,分批的距离搜索问题是要对每个磁盘的点数进行计算。我们的新算法用$(n)4/3美元时间(美元)解决了问题。