有限域上随机多项式的Poisson *负二项式卷积律

Hsien-Kuei Hwang
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引用次数: 4

摘要

设Fq[X]表示有限域Fq上有q个元素的多项式环。设n为Fq上n次的一元多项式的集合。假设n中qn个可能的一元多项式中的每一个都是等可能的,我们用一个对m≥1和n−m∞有效的一致渐近公式给出了P(Ωn=m)在n∞时的极限行为的完整表征。其中Ωn表示在n中随机多项式的分解中不可约因子的数量(计数的多重性)。Ωn的分布本质上是均值为log n的泊松分布和参数为q和q−1的负二项分布的卷积。这样的卷积律表现出三种渐近行为模式:当m很小时,它表现为泊松分布;当m变大时,其行为由负二项分布主导,过渡行为本质上是抛物线柱面函数(或标准正态律及其迭代积分的一些线性组合)。作为这个一致渐近公式的应用,我们得到了关于P(Ωn=m)的大多数已知结果,并提出了许多新的结果,如分布的单模性。所采用的方法可广泛应用于其他多集结构问题。本文还对Renyi的问题作了推广,讨论了不可约物总数与不同不可约物总数之差的分布。©1998 John Wiley & Sons, Inc随机结构。Alg。, 13, 17-47, 1998
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A Poisson * Negative Binomial Convolution Law for Random Polynomials over Finite Fields
Let Fq[X] denote a polynomial ring over a finite field Fq with q elements. Let n be the set of monic polynomials over Fq of degree n. Assuming that each of the qn possible monic polynomials in n is equally likely, we give a complete characterization of the limiting behavior of P(Ωn=m) as n∞ by a uniform asymptotic formula valid for m≥1 and n−m∞, where Ωn represents the number (multiplicities counted) of irreducible factors in the factorization of a random polynomial in n. The distribution of Ωn is essentially the convolution of a Poisson distribution with mean log n and a negative binomial distribution with parameters q and q−1. Such a convolution law exhibits three modes of asymptotic behaviors: when m is small, it behaves like a Poisson distribution; when m becomes large, its behavior is dominated by a negative binomial distribution, the transitional behavior being essentially a parabolic cylinder function (or some linear combinations of the standard normal law and its iterated integrals). As applications of this uniform asymptotic formula, we derive most known results concerning P(Ωn=m) and present many new ones like the unimodality of the distribution. The methods used are widely applicable to other problems on multiset constructions. An extension to Renyi's problem, concerning the distribution of the difference of the (total) number of irreducibles and the number of distinct irreducibles, is also presented. © 1998 John Wiley & Sons, Inc. Random Struct. Alg., 13, 17–47, 1998
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