Dense Subset Sum in Multi-Dimension

2026-07-11Data Structures and Algorithms

Data Structures and Algorithms
AI summary

The authors study the problem of finding sums of subsets from a large set of multi-dimensional vectors. They focus on cases where the number of vectors is large compared to the size of their coordinate ranges. They show that under these conditions, the sums have a very structured pattern and cover many points in a certain geometric shape. This extends earlier results to higher dimensions with fewer restrictions. Using these findings, the authors create a fast algorithm to solve the dense multi-dimensional subset sum problem.

subset sum problemmulti-dimensional vectorsadditive combinatoricsgeneralized arithmetic progressionzonotopelatticedense regimealgorithmic complexitycombinatorial structure
Authors
Lin Chen, Tingwei Hu, Yuchen Mao, Guochuan Zhang
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 $A$ of $n$ vectors in the $d$-dimensional hyperrectangle $[N_1]\times [N_2]\times\cdots\times [N_d]$, we study the structure of $\mathcal{S}(A)$, which is the set of all subset sums of $A$. We focus on the dense regime of the problem where $n \gg \sqrtΦ$ and $Φ= N_1 \times \cdots \times N_d$. We show that for any constant $d\geq 1$, if $n \gg \sqrtΦ$, then $\mathcal{S}(A)$ contains a long generalized progression in multi-dimension. If we further have that no non-trivial lattice can contain the majority of $A$, then $\mathcal{S}(A)$ contains all the integer points in the zonotope $\{x_1\vec{a}_1 + \cdots + x_n\vec{a}_n: o(1)\leq x_j \leq 1-o(1), x_j \in \mathbb{R}\}$. Compared to the previous results for $d \geq 2$, our result significantly reduces the density threshold and enlarges the region inside which all the integer points belong to $\mathcal{S}(A)$. Also, it matches the bound for the 1-dimensional case. Using our combinatorics result, we also develop an $\tilde{O}(n)$-time algorithm for the dense subset sum problem in multi-dimension.