{ "id": "2205.04285", "version": "v1", "published": "2022-05-09T13:55:43.000Z", "updated": "2022-05-09T13:55:43.000Z", "title": "A fourth moment phenomenon for asymptotic normality of monochromatic subgraphs", "authors": [ "Sayan Das", "Zoe Himwich", "Nitya Mani" ], "comment": "24 pages, 1 figure; comments welcome!", "categories": [ "math.PR", "math.CO" ], "abstract": "Given a graph sequence $\\{G_n\\}_{n\\ge1}$ and a simple connected subgraph $H$, we denote by $T(H,G_n)$ the number of monochromatic copies of $H$ in a uniformly random vertex coloring of $G_n$ with $c \\ge 2$ colors. In this article, we prove a central limit theorem for $T(H,G_n)$ with explicit error rates. The error rates arise from graph counts of collections formed by joining copies of $H$ that we call good joins. Counts of good joins are closely related to the fourth moment of a normalized version of $T(H,G_{n})$, and that connection allows us to show a fourth moment phenomenon for the central limit theorem. Precisely, for $c\\ge 30$, we show that $T(H,G_n)$ (appropriately centered and rescaled) converges in distribution to $\\mathcal{N}(0,1)$ whenever its fourth moment converges to 3 (the fourth moment of the standard normal distribution). We show the convergence of the fourth moment is necessary to obtain a normal limit when $c\\ge 2$. The combination of these results implies that the fourth moment condition characterizes the limiting normal distribution of $T(H,G_n)$ for all subgraphs $H$, whenever $c\\ge 30$.", "revisions": [ { "version": "v1", "updated": "2022-05-09T13:55:43.000Z" } ], "analyses": { "subjects": [ "60C05", "60F05", "05C15" ], "keywords": [ "fourth moment phenomenon", "asymptotic normality", "monochromatic subgraphs", "central limit theorem", "fourth moment condition characterizes" ], "note": { "typesetting": "TeX", "pages": 24, "language": "en", "license": "arXiv", "status": "editable" } } }