The nearest neighbor search problem has been widely studied for more than 30 years (Arya & Mount, 1993). Given Although this problem has many motivating examples, there a dataset D, the problem requires the construction of an is a dearth of papers examining it in the literature. Some vector index that can efficiently answer queries of the form "what databases analyze window search-like problem instances is the closest vector to x in D?" Solving this problem exactly as an additional feature of their system, but this analysis degrades to a brute force linear search in high dimensions is typically secondary to their main approach and too slow (Rubinstein, 2018), so instead both theoreticians and for large-scale real-world systems; as far as we are aware, practitioners focus on the relaxed c-approximate nearest we are the first to propose, analyze, and experiment with a neighbor search problem (ANNS), which asks "what is a non-trivial solution to the window search problem.