English

Dense Subset Sum in Multi-Dimension

Data Structures and Algorithms 2026-07-11 v1 Combinatorics

Abstract

We study the additive structure of dense subset sum in multi-dimension, and use the structure to develop efficient algorithms for the dense subset sum problem. More precisely, given a set AA of nn vectors in the dd-dimensional hyperrectangle [N1]×[N2]××[Nd][N_1]\times [N_2]\times\cdots\times [N_d], we study the structure of S(A)\mathcal{S}(A), which is the set of all subset sums of AA. We focus on the dense regime of the problem where nΦn \gg \sqrt{\Phi} and Φ=N1××Nd\Phi = N_1 \times \cdots \times N_d. We show that for any constant d1d\geq 1, if nΦn \gg \sqrt{\Phi}, then S(A)\mathcal{S}(A) contains a long generalized progression in multi-dimension. If we further have that no non-trivial lattice can contain the majority of AA, then S(A)\mathcal{S}(A) contains all the integer points in the zonotope {x1a1++xnan:o(1)xj1o(1),xjR}\{x_1\vec{a}_1 + \cdots + x_n\vec{a}_n: o(1)\leq x_j \leq 1-o(1), x_j \in \mathbb{R}\}. Compared to the previous results for d2d \geq 2, our result significantly reduces the density threshold and enlarges the region inside which all the integer points belong to S(A)\mathcal{S}(A). Also, it matches the bound for the 1-dimensional case. Using our combinatorics result, we also develop an O~(n)\tilde{O}(n)-time algorithm for the dense subset sum problem in multi-dimension.

Cite

@article{arxiv.2607.10343,
  title  = {Dense Subset Sum in Multi-Dimension},
  author = {Lin Chen and Tingwei Hu and Yuchen Mao and Guochuan Zhang},
  journal= {arXiv preprint arXiv:2607.10343},
  year   = {2026}
}

Comments

A preliminary version to appear in FOCS'26