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On the Complexity of Computing Prime Tables

机译:论计算主要表的复杂性

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Many large arithmetic computations rely on tables of all primes less than n. For example, the fastest algorithms for computing n! takes time O(M(n log n) + P(n)), where M(n) is the time to multiply two n-bit numbers, and P(n) is the time to compute a prime table up to n. The fastest algorithm to compute ({sup}n {down}n/2) also uses a prime table. We show that it takes time O(M(n) + P(n)). In various models, the best bound on P(n) is greater than M(n log n), given advances in the complexity of multiplication [8,13]. In this paper, we give two algorithms to computing prime tables and analyze their complexity on a multitape Turing machine, one of the standard models for analyzing such algorithms. These two algorithms run in time O(M(n log n)) and O(n log~2 n/log log n), respectively. We achieve our results by speeding up Atkin's sieve. Given that the current best bound on M(n) is n log n2~(O(log~* n)), the second algorithm is faster and improves on the previous best algorithm by a factor of log~2 log n. Our fast prime-table algorithms speed up both the computation of n! and ({sup}n {down}n/2). Finally, we show that computing the factorial takes Ω(M(n log~(4/7-ε) n)) for any constant ε > 0 assuming only multiplication is allowed.
机译:许多大型算术计算依赖于小于n的所有素数的表格。例如,计算n的最快算法!需要时间o(m(n log n)+ p(n)),其中m(n)是乘以两个n比特数的时间,并且p(n)是计算最多的prime表的时间。计算的最快算法({sup} n {down} n / 2)也使用Prime表。我们表明它需要时间o(m(n)+ p(n))。在各种模型中,P(n)的最佳界限大于m(n log n),给出了乘法复杂性的进步[8,13]。在本文中,我们将两种算法用于计算主要表,并分析它们在多级图标机上的复杂性,是分析这种算法的标准模型之一。这两个算法分别在时间o(m(n log n))和o(n log〜2 n / log log n)中运行。通过加快atkin的筛子来实现我们的结果。鉴于M(n)上的当前最佳绑定为n log n2〜(o(log〜* n)),第二算法更快,并通过日志〜2 log n的一个最佳算法来提高先前的最佳算法。我们的快速Prime-Table算法加速了N的计算! ({sup} n {down} n / 2)。最后,我们表明计算因子是针对任何常数ε> 0的ω(n(n log〜(4/7-ε)n))假设仅允许乘法。

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