简洁布尔矩阵-向量乘法的紧单元探测边界

Diptarka Chakraborty, Lior Kamma, Kasper Green Larsen
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引用次数: 27

摘要

布尔矩阵-向量乘法的推测硬度已被成功地用于证明许多重要数据结构问题的条件下界,参见Henzinger等人[STOC ' 15]。在最近的工作中,Larsen和Williams [SODA ' 17]从上界方面解决了这个问题,并给出了一个令人惊讶的单元探测数据结构(即,我们只对内存访问收费,而计算是免费的)。他们的单元探测数据结构在Õ(n7/4)时间内回答查询,并且简洁,因为它将输入矩阵存储在只读存储器中,外加额外的Õ(n7/4)位。本文主要解决了简洁布尔矩阵-向量乘法的单元探测复杂度问题。我们提出了一个新的单元探测数据结构,查询时间Õ(n3/2)只存储了Õ(n3/2)位。然后,我们用一个下界来补充我们的数据结构,该下界表明,任何在n < r < n2的一侧存储r位的数据结构必须具有满足tr = Ω(n3)的查询时间t。对于r≤n,任何数据结构必须有t = Ω(n2)。由于单元探测模型中的下界也适用于经典的word-RAM数据结构,所以下界自然会延续下去。我们也证明了类似的矩阵-向量乘法在F2上的下界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tight cell probe bounds for succinct Boolean matrix-vector multiplication
The conjectured hardness of Boolean matrix-vector multiplication has been used with great success to prove conditional lower bounds for numerous important data structure problems, see Henzinger et al. [STOC’15]. In recent work, Larsen and Williams [SODA’17] attacked the problem from the upper bound side and gave a surprising cell probe data structure (that is, we only charge for memory accesses, while computation is free). Their cell probe data structure answers queries in Õ(n7/4) time and is succinct in the sense that it stores the input matrix in read-only memory, plus an additional Õ(n7/4) bits on the side. In this paper, we essentially settle the cell probe complexity of succinct Boolean matrix-vector multiplication. We present a new cell probe data structure with query time Õ(n3/2) storing just Õ(n3/2) bits on the side. We then complement our data structure with a lower bound showing that any data structure storing r bits on the side, with n < r < n2 must have query time t satisfying t r = Ω(n3). For r ≤ n, any data structure must have t = Ω(n2). Since lower bounds in the cell probe model also apply to classic word-RAM data structures, the lower bounds naturally carry over. We also prove similar lower bounds for matrix-vector multiplication over F2.
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