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The effect of induced subgraphs on quasi-randomness

机译:诱导子图对拟随机性的影响

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摘要

One of the main questins that arise when studying random and quasi-random structures is which properties p are such that any object that satisfies P "behaves" like a truly random one. In the context of graphs, Chung, Graham, and Wilson [9] call a graph p-quasi-random if it satisfies a long list of the properties that hold in G(n, p) with high probability, like edge distribution, spectral gap, cut size, and more.

Our main result here is that the following holds for any fixed graph H: if the distribution of induced copies of H in a graph G is close (in a well defined way) to the distribuition we would expect to have in G(n,p), then G is either P-quasi-random or p-quasirandom, where &pmacr; is the unique non-trivial solution of the polynomial equation xΔ (1 -- x)1-Δ = pΔ (1 -- p)1--Δ, with Δ being the edge density of H. We thus infer that having the correct distribution of induced copies of any single graph H, is enough to guarantee that a graph has the properties of a random one. The proof techniques we develop here, which combine probabilistic, algebraic and combinatorial tools, may be of independent interest to the study of quasi-random structures.

机译:

研究随机和准随机结构时出现的主要问题之一是,哪些属性p使得满足 P 的任何对象都“表现”得像真正的随机对象一样。在图的上下文中,Chung,Graham和Wilson [9]如果满足一长串包含在 G(n,p ),例如边缘分布,光谱间隙,切割尺寸等等。

我们在这里的主要结果是,对于任何固定图 H ,以下条件均成立:如果 H 诱导副本在图中的分布 G 非常接近(以明确的方式)我们期望在 G(n,p)中具有的分布,因此 G 为P准随机或P准随机,其中&pmacr;是多项式方程x Δ(1-x)1-Δ = p Δ(1- p)1-Δ,其中Δ是H的边沿密度。因此,我们推断具有正确分布的任何单个图 H 的诱导副本的分布足以保证图具有以下性质:一个随机的。我们在这里开发的结合概率,代数和组合工具的证明技术可能对研究拟随机结构具有独立的兴趣。

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