论文标题
使用重新持续特征值的定向图和超图的Cheeger不平等现象
Cheeger Inequalities for Directed Graphs and Hypergraphs Using Reweighted Eigenvalues
论文作者
论文摘要
我们使用重新持续的特征值方法来得出针对有向图和超图的Cheeger不等式,该方法最近在无向图中开发用于顶点扩展[OZ22,KLT22,JPV22]。目的是为有向图开发新的光谱理论,以及用于超图的替代光谱理论。 第一个主要结果是将有向图$ g $的顶点扩展$ \vecψ(g)$的cheeger不平等与顶点计算的最大重新加权的第二个eigenvalue $ \vecλ_2^{v {v*} $: \ sqrt {\vecλ_2^{v*} \ cdot \ log(δ/\vecλ_2^{v*})}。 \]这提供了通过顶点扩展的有向图的最快混合时间的组合表征,并在重新重量的特征值,顶点扩展和有向图的最快混合时间之间建立了新的连接。 第二个主要结果是将有向图$ g $的边缘电导$ \ vecC(g)$ \ v $与边缘负相关的最大重新重新重新重磅第二个Eigenvalue $ \vecλ_2^{e*} $: \ sqrt {\vecλ_2^{e*} \ cdot \ log(1/\vecλ_2^{e*})}。 \]这为有向图提供了证书,以作为扩展器和光谱算法,以在有向图中找到稀疏的切割,在证明图形扩展和光谱分区算法中扮演与Cheeger的不平等相似的角色。 我们还使用这种重新加权的特征值方法来得出有针对性图的改善的脸颊不平等,并在[Lou15,cltz18]中得出匹配和改善现有结果的超图和改善现有结果的多种cheeger不平等。这些支持结果是,这提供了一种统一的方法,可以将无向图的光谱理论提升为更通用的环境。
We derive Cheeger inequalities for directed graphs and hypergraphs using the reweighted eigenvalue approach that was recently developed for vertex expansion in undirected graphs [OZ22,KLT22,JPV22]. The goal is to develop a new spectral theory for directed graphs and an alternative spectral theory for hypergraphs. The first main result is a Cheeger inequality relating the vertex expansion $\vecψ(G)$ of a directed graph $G$ to the vertex-capacitated maximum reweighted second eigenvalue $\vecλ_2^{v*}$: \[ \vecλ_2^{v*} \lesssim \vecψ(G) \lesssim \sqrt{\vecλ_2^{v*} \cdot \log (Δ/\vecλ_2^{v*})}. \] This provides a combinatorial characterization of the fastest mixing time of a directed graph by vertex expansion, and builds a new connection between reweighted eigenvalued, vertex expansion, and fastest mixing time for directed graphs. The second main result is a stronger Cheeger inequality relating the edge conductance $\vecϕ(G)$ of a directed graph $G$ to the edge-capacitated maximum reweighted second eigenvalue $\vecλ_2^{e*}$: \[ \vecλ_2^{e*} \lesssim \vecϕ(G) \lesssim \sqrt{\vecλ_2^{e*} \cdot \log (1/\vecλ_2^{e*})}. \] This provides a certificate for a directed graph to be an expander and a spectral algorithm to find a sparse cut in a directed graph, playing a similar role as Cheeger's inequality in certifying graph expansion and in the spectral partitioning algorithm for undirected graphs. We also use this reweighted eigenvalue approach to derive the improved Cheeger inequality for directed graphs, and furthermore to derive several Cheeger inequalities for hypergraphs that match and improve the existing results in [Lou15,CLTZ18]. These are supporting results that this provides a unifying approach to lift the spectral theory for undirected graphs to more general settings.