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arXiv 1202.0644math.PRmath.COmath.OAmath.SP
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稀疏随机图上马氏生成元的谱

Spectrum of Markov generators on sparse random graphs

Charles Bordenave, Pietro Caputo, Djalil Chafai

摘要:

研究了随机加权定向图上连续时间随机游动的无穷小生成元的谱。这是由L(j,k)=X(j,k)定义的非埃尔米特随机nxn矩阵L,如果k<>j并且L(j,j)=-sum(L(j,k),k<>j),其中X(j,k)是i.i.d.随机权重在对权重法则的温和假设下,我们建立了当n趋于无穷大时L的经验谱分布在中心化和重新标度后的收敛性。特别地,我们的假设包括稀疏随机图,例如定向埃尔德什-雷尼图,其中每个边都以概率p(n)->0独立存在,只要np(n)>>(log(n))^6。极限分布的特点是作为一个加性高斯变形的标准圆律。在自由概率条件下,这与圆元的自由和的布朗测度和具有高斯谱测度的正规算子相一致。极限分布的密度分析使用从属公式。进一步研究了L的不变测度对一致分布的收敛性,并建立了L的极值特征值的估计。

英文摘要:

We investigate the spectrum of the infinitesimal generator of the continuous time random walk on a randomly weighted oriented graph. This is the non-Hermitian random nxn matrix L defined by L(j,k)=X(j,k) if k<>j and L(j,j)=-sum(L(j,k),k<>j), where X(j,k) are i.i.d. random weights. Under mild assumptions on the law of the weights, we establish convergence as n tends to infinity of the empirical spectral distribution of L after centering and rescaling. In particular, our assumptions include sparse random graphs such as the oriented Erdös-Rényi graph where each edge is present independently with probability p(n)->0 as long as np(n) >> (log(n))^6. The limiting distribution is characterized as an additive Gaussian deformation of the standard circular law. In free probability terms, this coincides with the Brown measure of the free sum of the circular element and a normal operator with Gaussian spectral measure. The density of the limiting distribution is analyzed using a subordination formula. Furthermore, we study the convergence of the invariant measure of L to the uniform distribution and establish estimates on the extremal eigenvalues of L.

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