DeepLLL algorithm (Schnorr, 1994) is a famous variant of LLL lattice basis reduction algorithm, and PotLLL algorithm (Fontein et al., 2014) and $S^2$LLL algorithm (Yasuda and Yamaguchi, 2019) are recent polynomial-time variants of DeepLLL algorithm developed from cryptographic applications. However, the known polynomial bounds for computational complexity are shown only for parameter $\delta < 1$; for "optimal" parameter $\delta = 1$ which ensures the best output quality, no polynomial bounds are known, and except for LLL algorithm, it is even not formally proved that the algorithm always halts within finitely many steps. In this paper, we prove that these four algorithms always halt also with optimal parameter $\delta = 1$, and furthermore give explicit upper bounds for the numbers of loops executed during the algorithms. Unlike the known bound (Akhavi, 2003) applicable to LLL algorithm only, our upper bounds are deduced in a unified way for all of the four algorithms.
翻译:DeepLLL算法(Schnorr,1994年)是LLL Lattice基础削减算法和PotLLL算法(Fontein等人,2014年)和$S ⁇ 2$LLL 算法(Yasuda和Yamaguchi,2019年)的著名变体,是最近从加密应用中开发的DeepLLLLL算法的多元时变体。然而,已知的计算复杂性的多元数界限仅显示于参数$delta < 1美元;对于“最优”参数 $\delta = 1美元 = 1美元;对于“最优” 参数 $\delta = 1美元,确保最佳输出质量的参数 = 1美元,除了LLLL 算法之外,我们甚至没有正式证明该算法总是在有限的许多步骤中停止。在本文中,我们证明这四种算法也总是以最优参数$\delta = 1美元的方式停止,并且为在算法期间执行的圆圈数提供了明确的上明确的上限界限。与已知的界限(Akhvi,2003年)不同,我们仅适用于LL算法的上界线是以统一的方式推断所有四个算法的。