Deterministic Time-Space Tradeoffs for k-SUM

TL;DR

This paper introduces deterministic algorithms with optimized time-space tradeoffs for the k-SUM problem, applicable in both integer and real number models, with implications for complexity conjectures.

Contribution

It presents a unified deterministic self-reduction for k-SUM, improving known bounds and establishing equivalences related to the 3-SUM conjecture.

Findings

3-SUM in deterministic time O(n^2 log log n / log n) and space O(√(n log n / log log n))

3-SUM in deterministic time O(n^2) and space O(√n)

Equivalence between 3-SUM conjecture and space-bounded algorithms requiring near-quadratic time

Abstract

Given a set of numbers, the $k$-SUM problem asks for a subset of $k$ numbers that sums to zero. When the numbers are integers, the time and space complexity of $k$-SUM is generally studied in the word-RAM model; when the numbers are reals, the complexity is studied in the real-RAM model, and space is measured by the number of reals held in memory at any point. We present a time and space efficient deterministic self-reduction for the $k$-SUM problem which holds for both models, and has many interesting consequences. To illustrate: * $3$-SUM is in deterministic time $O(n^2 \lg\lg(n)/\lg(n))$ and space $O\left(\sqrt{\frac{n \lg(n)}{\lg\lg(n)}}\right)$. In general, any polylogarithmic-time improvement over quadratic time for $3$-SUM can be converted into an algorithm with an identical time improvement but low space complexity as well. * $3$-SUM is in deterministic time $O(n^2)$ and space $O(\sqrt n)$, derandomizing an algorithm of Wang. * A popular conjecture states that 3-SUM requires $n^{2-o(1)}$ time on the word-RAM. We show that the 3-SUM Conjecture is in fact equivalent to the (seemingly weaker) conjecture that every $O(n^{.51})$-space algorithm for $3$-SUM requires at least $n^{2-o(1)}$ time on the word-RAM. * For $k \ge 4$, $k$-SUM is in deterministic $O(n^{k - 2 + 2/k})$ time and $O(\sqrt{n})$ space.