cronokirby

(2026-08) Hardness of Euclidean Closest Vector within n^{1-8--epsilon} and Binary Nearest Codeword within n^{1-4--epsilon}

2026-08-11

Abstract

We prove two deterministic inapproximability results.

First, for every fixed ϵ>0\epsilon>0, Euclidean GapCVP(2)\mathrm{GapCVP}^{(2)} is NP-hard with gap factor n1/8ϵn^{1/8-\epsilon} under deterministic polynomial-time many-one reductions, where nn denotes the lattice rank. Consequently, the Euclidean closest vector problem is NP-hard to approximate within the same factor. This improves the previous n1/400n^{1/400} hardness factor in Chapter 7 of the OpenAI report [Ope26].

Second, for every fixed ϵ>0\epsilon>0, binary nearest codeword and binary syndrome decoding are NP-hard to approximate within n1/4ϵn^{1/4-\epsilon} under deterministic polynomial-time many-one reductions, where nn denotes the binary block length. This improves the previous n1/200n^{1/200} hardness factor in Chapter 7 of the OpenAI report [Ope26].