Stronger 3-SUM Lower Bounds for Approximate Distance Oracles via Additive Combinatorics

11/14/2022
by   Amir Abboud, et al.
0

The "short cycle removal" technique was recently introduced by Abboud, Bringmann, Khoury and Zamir (STOC '22) to prove fine-grained hardness of approximation. Its main technical result is that listing all triangles in an n^1/2-regular graph is n^2-o(1)-hard under the 3-SUM conjecture even when the number of short cycles is small; namely, when the number of k-cycles is O(n^k/2+γ) for γ<1/2. Abboud et al. achieve γ≥ 1/4 by applying structure vs. randomness arguments on graphs. In this paper, we take a step back and apply conceptually similar arguments on the numbers of the 3-SUM problem. Consequently, we achieve the best possible γ=0 and the following lower bounds under the 3-SUM conjecture: * Approximate distance oracles: The seminal Thorup-Zwick distance oracles achieve stretch 2k± O(1) after preprocessing a graph in O(m n^1/k) time. For the same stretch, and assuming the query time is n^o(1) Abboud et al. proved an Ω(m^1+1/12.7552 · k) lower bound on the preprocessing time; we improve it to Ω(m^1+1/2k) which is only a factor 2 away from the upper bound. We also obtain tight bounds for stretch 2+o(1) and 3-ϵ and higher lower bounds for dynamic shortest paths. * Listing 4-cycles: Abboud et al. proved the first super-linear lower bound for listing all 4-cycles in a graph, ruling out (m^1.1927+t)^1+o(1) time algorithms where t is the number of 4-cycles. We settle the complexity of this basic problem by showing that the O(min(m^4/3,n^2) +t) upper bound is tight up to n^o(1) factors. Our results exploit a rich tool set from additive combinatorics, most notably the Balog-Szemerédi-Gowers theorem and Rusza's covering lemma. A key ingredient that may be of independent interest is a subquadratic algorithm for 3-SUM if one of the sets has small doubling.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro