The efficiency depends on the query size relative to the data distribution. A small query in a sparse region prunes almost everything. A query that covers the whole space prunes nothing (because every node overlaps), degenerating to a brute-force scan. The quadtree gives you the most benefit when your queries are spatially local, which is exactly the common case for map applications, game physics, and spatial databases.
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Games and physics simulations need to detect which objects are touching or overlapping. With nnn objects, checking every pair is O(n2)O(n^2)O(n2) comparisons, which gets expensive fast. A hundred objects means roughly 5,000 pair checks. A thousand means nearly 500,000.，更多细节参见快连下载安装