Approximating the densest sublattice from Rankin’s inequality

Jianwei Li, Phong Q. Nguyen
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引用次数: 14

Abstract

We present a higher-dimensional generalization of the Gama{Nguyen algorithm (STOC '08) for approximating the shortest vector problem in a lattice. This generalization approximates the densest sublattice by using a subroutine solving the exact problem in low dimension, such as the Dadush{Micciancio algorithm (SODA '13). Our approximation factor corresponds to a natural inequality on Rankin's constant derived from Rankin's inequality.
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用Rankin不等式逼近最密子格
我们提出了Gama{Nguyen算法(STOC '08)的高维推广,用于逼近晶格中的最短向量问题。这种概化通过使用解决低维精确问题的子例程(如Dadush{Micciancio算法(SODA '13))来近似最密集的子格。我们的近似因子对应于由兰金不等式导出的兰金常数上的一个自然不等式。
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来源期刊
Lms Journal of Computation and Mathematics
Lms Journal of Computation and Mathematics MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
2.60
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: LMS Journal of Computation and Mathematics has ceased publication. Its final volume is Volume 20 (2017). LMS Journal of Computation and Mathematics is an electronic-only resource that comprises papers on the computational aspects of mathematics, mathematical aspects of computation, and papers in mathematics which benefit from having been published electronically. The journal is refereed to the same high standard as the established LMS journals, and carries a commitment from the LMS to keep it archived into the indefinite future. Access is free until further notice.
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