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arXiv math/0402343math.DSmath.PR
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函数空间中指数线性映射的动力学

Dynamics of exponential linear map in functional space

David Gamarnik, Tomasz Nowicki, Grzegorz Swirszcz

摘要:

我们考虑一个唯一不变的概率分布,满足某些演化性质的存在性问题。这个问题来自随机图论,但为了回答它,我们将其视为函数空间中的动力系统,在那里我们寻找全局吸引子。我们考虑以下分歧问题:给定一个概率测度$μ$,它对应于一个随机图的链接的重量分布,我们形成一个正的线性算子$Φ$(卷积)的分布函数,然后我们分析了一个家庭的指数与参数$λ$,它对应于一个稀疏的随机图的连通性。证明了对每个测度$μ$(\emph{i.e.},卷积$Φ$)和每个$λ< e$,存在唯一的算子的全局吸引不动点,从而得到了随机图上极限概率分布的存在唯一性.这个估计是早先为确定性权重分布建立的\cite{KarpSipser}(狄拉克测度$μ$),被称为$e$ -截止现象,因为对于这样的分布和$λ>e$没有固定点吸引子。因此,我们在一个更普遍的意义上确立了这一现象。

英文摘要:

We consider the question of existence of a unique invariant probability distribution which satisfies some evolutionary property. The problem arises from the random graph theory but to answer it we treat it as a dynamical system in the functional space, where we look for a global attractor. We consider the following bifurcation problem: Given a probability measure $μ$, which corresponds to the weight distribution of a link of a random graph we form a positive linear operator $Φ$ (convolution) on distribution functions and then we analyze a family of its exponents with a parameter $λ$ which corresponds to connectivity of a sparse random graph. We prove that for every measure $μ$ (\emph{i.e.}, convolution $Φ$) and every $λ< e$ there exists a unique globally attracting fixed point of the operator, which yields the existence and uniqueness of the limit probability distribution on the random graph. This estimate was established earlier \cite{KarpSipser} for deterministic weight distributions (Dirac measures $μ$) and is known as $e$-cutoff phenomena, as for such distributions and $λ>e$ there is no fixed point attractor. We thus establish this phenomenon in a much more general sense.

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