Truly Subquadratic 3SUM and Truly Subcubic APSP via Triangles in Sparse Lopsided Graphs
Abstract — v1
We give the first polynomial improvements over the textbook algorithms for SUM and All-Pairs Shortest Paths (APSP): we show how to deterministically solve SUM on integers of polynomial size in time and APSP on directed -vertex graphs with polynomially bounded integer weights in time. This refutes the SUM and APSP hypotheses. Using known reductions, we also refute the real-valued versions of the SUM and APSP hypotheses, the Exact Triangle hypothesis, the Zero-Weight -Clique hypotheses, and the three rectangular hinted Online Matrix–Vector conjectures of van den Brand, Nanongkai, and Saranurak, and we give polynomial speedups for a variety of other problems. All of these results follow from a single new algorithm for thin matrix products. Let be an integer matrix and a integer matrix with , and let be any set of at most positions. We compute the entries , , in operations, which is polynomially less than the time needed to write down or to compute inner products one by one. We design this algorithm by modifying a variant of Coppersmith's rectangular matrix multiplication algorithm, built from a ten-multiplication identity of Schönhage, to perform only the operations needed for the entries in , and show that few operations are needed. Interpreted as a graph algorithm, this solves the All-Edges Sparse Triangle problem in truly subquadratic time on sparse lopsided tripartite graphs where two parts have vertices but one part has vertices for . By known reductions, Exact Triangle, and hence SUM and APSP, reduce to this problem. We also give a data structure version that answers queries for single entries of , not known in advance.
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