Deciding whether a lattice has an orthonormal basis is in co-NP

IF 2.2 2区 数学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Christoph Hunkenschröder
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引用次数: 0

Abstract

We show that the problem of deciding whether a given Euclidean lattice L has an orthonormal basis is in NP and co-NP. Since this is equivalent to saying that L is isomorphic to the standard integer lattice, this problem is a special form of the lattice isomorphism problem, which is known to be in the complexity class SZK. We achieve this by deploying a result on characteristic vectors by Elkies that gained attention in the context of 4-manifolds and Seiberg-Witten equations, but seems rather unnoticed in the algorithmic lattice community. On the way, we also show that for a given Gram matrix \(G \in \mathbb {Q}^{n \times n}\), we can efficiently find a rational lattice that is embedded in at most four times the initial dimension n, i.e. a rational matrix \(B \in \mathbb {Q}^{4n \times n}\) such that \(B^\intercal B = G\).

Abstract Image

决定一个网格是否有正交基础属于共 NP
我们证明,判断给定欧几里得网格 L 是否具有正交基础的问题属于 NP 和 co-NP。由于这等同于说 L 与标准整数格同构,因此这个问题是格同构问题的一种特殊形式,而格同构问题已知属于复杂度类 SZK。我们利用埃尔基斯(Elkies)关于特征向量的一个结果来实现这个问题,这个结果在 4-芒形和塞伯格-维滕方程的背景下获得了关注,但在算法晶格领域却似乎没有引起注意。在此过程中,我们还证明了对于一个给定的克矩阵(G \in \mathbb {Q}^{n\times n}\),我们可以高效地找到一个嵌入在最多四倍初始维度 n 中的有理网格,即一个有理矩阵(B \in \mathbb {Q}^{4n\times n}\),使得 \(B^\intercal B = G\).
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Programming
Mathematical Programming 数学-计算机:软件工程
CiteScore
5.70
自引率
11.10%
发文量
160
审稿时长
4-8 weeks
期刊介绍: Mathematical Programming publishes original articles dealing with every aspect of mathematical optimization; that is, everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Included, along with the standard topics of linear, nonlinear, integer, conic, stochastic and combinatorial optimization, are techniques for formulating and applying mathematical programming models, convex, nonsmooth and variational analysis, the theory of polyhedra, variational inequalities, and control and game theory viewed from the perspective of mathematical programming.
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