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This is the same idea behind binary search. In a sorted array, you compare against the middle element and eliminate half the remaining candidates. In a quadtree, you choose one of four quadrants and ignore the other three regions. Each level narrows the search space by a factor of four instead of two.
After OpenAI released GPT-5.3-Codex (high) which performed substantially better and faster at these types of tasks than GPT-5.2-Codex, I asked Codex to write a UMAP implementation from scratch in Rust, which at a glance seemed to work and gave reasonable results. I also instructed it to create benchmarks that test a wide variety of representative input matrix sizes. Rust has a popular benchmarking crate in criterion, which outputs the benchmark results in an easy-to-read format, which, most importantly, agents can easily parse.