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Related papers: On Beating $2^n$ for the Closest Vector Problem

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The closest vector problem (CVP) and shortest (nonzero) vector problem (SVP) are the core algorithmic problems on Euclidean lattices. They are central to the applications of lattices in many problems of communications and cryptography.…

Information Theory · Computer Science 2016-11-17 Laura Luzzi , Damien Stehle , Cong Ling

We give a randomized $2^{n+o(n)}$-time and space algorithm for solving the Shortest Vector Problem (SVP) on n-dimensional Euclidean lattices. This improves on the previous fastest algorithm: the deterministic $\widetilde{O}(4^n)$-time and…

Data Structures and Algorithms · Computer Science 2019-01-28 Divesh Aggarwal , Daniel Dadush , Oded Regev , Noah Stephens-Davidowitz

In this paper we consider the closest vector problem (CVP) for lattices $\Lambda \subseteq \mathbb{Z}^n$ given by a generator matrix $A\in \mathcal{M}_{n\times n}(\mathbb{Z})$. Let $b>0$ be the maximum of the absolute values of the entries…

Cryptography and Security · Computer Science 2023-04-10 Eduardo Canale , Claudio Qureshi , Alfredo Viola

A particular instance of the Shortest Vector Problem (SVP) appears in the context of Compute-and-Forward. Despite the NP-hardness of the SVP, we will show that this certain instance can be solved in complexity order $O(n\psi\log(n\psi))$…

Information Theory · Computer Science 2017-11-28 Saeid Sahraei , Michael Gastpar

In a seminal work, Micciancio & Voulgaris (2013) described a deterministic single-exponential time algorithm for the Closest Vector Problem (CVP) on lattices. It is based on the computation of the Voronoi cell of the given lattice and thus…

Data Structures and Algorithms · Computer Science 2020-01-08 Christoph Hunkenschröder , Gina Reuland , Matthias Schymura

We give a deterministic O(log n)^n algorithm for the {\em Shortest Vector Problem (SVP)} of a lattice under {\em any} norm, improving on the previous best deterministic bound of n^O(n) for general norms and nearly matching the bound of…

Computational Complexity · Computer Science 2011-07-28 Daniel Dadush , Santosh Vempala

The assumed hardness of the Shortest Vector Problem in high-dimensional lattices is one of the cornerstones of post-quantum cryptography. The fastest known heuristic attacks on SVP are via so-called sieving methods. While these still take…

$ \newcommand{\SVP}{\mathsf{SVP}} \newcommand{\NP}{\mathsf{NP}} \newcommand{\RTIME}{\mathsf{RTIME}} \newcommand{\RSUBEXP}{\mathsf{RSUBEXP}} \newcommand{\eps}{\epsilon} \newcommand{\poly}{\mathop{\mathrm{poly}}} $We show that unless $\NP…

Computational Complexity · Computer Science 2018-06-12 Ishay Haviv , Oded Regev

We establish deterministic hardness of approximation results for the Shortest Vector Problem in $\ell_p$ norm ($\mathsf{SVP}_p$) and for Unique-SVP ($\mathsf{uSVP}_p$) for all $p > 2$. Previously, no deterministic hardness results were…

Computational Complexity · Computer Science 2025-10-21 Yahli Hecht , Muli Safra

We show that a constant factor approximation of the shortest and closest lattice vector problem w.r.t. any $\ell_p$-norm can be computed in time $2^{(0.802 +{\epsilon})\, n}$. This matches the currently fastest constant factor approximation…

Computational Geometry · Computer Science 2020-06-17 Friedrich Eisenbrand , Moritz Venzin

By applying Grover's quantum search algorithm to the lattice algorithms of Micciancio and Voulgaris, Nguyen and Vidick, Wang et al., and Pujol and Stehl\'{e}, we obtain improved asymptotic quantum results for solving the shortest vector…

Cryptography and Security · Computer Science 2013-06-12 Thijs Laarhoven , Michele Mosca , Joop van de Pol

We present algorithms for the $(1+\epsilon)$-approximate version of the closest vector problem for certain norms. The currently fastest algorithm (Dadush and Kun 2016) for general norms has running time of $2^{O(n)} (1/\epsilon)^n$. We…

Data Structures and Algorithms · Computer Science 2021-11-03 Márton Naszódi , Moritz Venzin

We study the complexity of lattice problems in a world where algorithms, reductions, and protocols can run in superpolynomial time, revisiting four foundational results: two worst-case to average-case reductions and two protocols. We also…

Lattice-based cryptography is one of the leading proposals for post-quantum cryptography. The Shortest Vector Problem (SVP) is arguably the most important problem for the cryptanalysis of lattice-based cryptography, and many lattice-based…

Quantum Physics · Physics 2021-05-13 André Chailloux , Johanna Loyer

We show conditional hardness of Approximate Nearest Neighbor Search (ANN) under the $\ell_\infty$ norm with two simple reductions. Our first reduction shows that hardness of a special case of the Shortest Vector Problem (SVP), which…

Computational Complexity · Computer Science 2020-11-13 Young Kun Ko , Min Jae Song

In 2018, the longest vector problem (LVP) and the closest vector problem (CVP) in $p$-adic lattices were introduced. These problems are closely linked to the orthogonalization process. In this paper, we first prove that every $p$-adic…

Number Theory · Mathematics 2025-09-11 Chi Zhang , Yingpu Deng , Zhaonan Wang

In this paper, we present a deterministic algorithm for the closest vector problem for all l_p-norms, 1 < p < \infty, and all polyhedral norms, especially for the l_1-norm and the l_{\infty}-norm. We achieve our results by introducing a new…

Data Structures and Algorithms · Computer Science 2011-09-27 Johannes Blömer , Stefanie Naewe

We show that, assuming NP $\not\subseteq$ $\cap_{\delta > 0}$DTIME$\left(\exp{n^\delta}\right)$, the shortest vector problem for lattices of rank $n$ in any finite $\ell_p$ norm is hard to approximate within a factor of $2^{(\log n)^{1 -…

Computational Complexity · Computer Science 2026-04-07 Isaac M Hair , Amit Sahai

Finding sparse vectors is a fundamental problem that arises in several contexts including codes, subspaces, and lattices. In this work, we prove strong inapproximability results for all these variants using a novel approach that even…

Computational Complexity · Computer Science 2025-06-26 Vijay Bhattiprolu , Venkatesan Guruswami , Euiwoong Lee , Xuandi Ren

Blomer and Naewe[BN09] modified the randomized sieving algorithm of Ajtai, Kumar and Sivakumar[AKS01] to solve the shortest vector problem (SVP). The algorithm starts with $N = 2^{O(n)}$ randomly chosen vectors in the lattice and employs a…

Data Structures and Algorithms · Computer Science 2018-05-16 Divesh Aggarwal , Priyanka Mukhopadhyay