The Improvement of the Commonly Used Linear Polynomial Selection Methods

Hao Zhu, Shenghui Su
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引用次数: 1

Abstract

The general number field sieve (GNFS) is asymptotically the fastest algorithm known for factoring large integers. One of the most important steps of GNFS is to select a good polynomial pair. Whether we can select a good polynomial pair, directly affects the efficiency of the sieving step. Now there are three linear methods widely used which base-m method, Murphy method and Klein Jung method. Base-m method is to construct polynomial based on the m-expansion of the integer, Murphy method mainly focuses on the root property of the polynomial and Klein Jung method restricts the first three coefficients size of the polynomial in a certain range. In this paper, we compare the size property and root property of the polynomials which select from the three methods. A good leading coefficient ad of f1 is important. The good means that ad has some small prime divisors. Klein Jung method does not give a concrete method to choose a good ad in its first step. We choose these better ad first and store in a set Ad, then take the Ad as input. Through the pretreatment we can get better polynomial and speed up the efficiency of Klein Jung method at the same time.
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常用线性多项式选择方法的改进
一般数字字段筛选(GNFS)是已知的分解大整数的最快算法。GNFS的一个重要步骤是选择一个好的多项式对。能否选择好的多项式对,直接影响到筛分步骤的效率。目前广泛使用的线性方法有三种:base-m法、Murphy法和Klein Jung法。基-m法是基于整数的m展开构造多项式,Murphy法主要关注多项式的根性质,Klein Jung法将多项式的前三个系数大小限制在一定范围内。本文比较了从三种方法中选取的多项式的大小性质和根性质。一个好的前导系数ad是很重要的。好的意思是它有一些小质因数。Klein Jung方法在第一步并没有给出一个具体的方法来选择一个好的广告。我们首先选择这些较好的广告,并存储在一个集合广告中,然后将该广告作为输入。通过预处理可以得到更好的多项式,同时提高了Klein - Jung方法的效率。
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