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Abstract How many copies of a fixed odd cycle, , can a planar graph contain? We answer this question asymptotically for and prove a bound which is tight up to a factor of 3/2 for all other values of . This extends the prior results of Cox and Martin and of Lv, Győri, He, Salia, Tompkins, and Zhu on the analogous question for even cycles. Our bounds result from a reduction to the following maximum likelihood question: which probability mass on the edges of some clique maximizes the probability that edges sampled independently from form either a cycle or a path? 

Abstract Given a hereditary property of graphs $$\mathcal{H}$$ and a $$p\in [0,1]$$ , the edit distance function $$\textrm{ed}_{\mathcal{H}}(p)$$ is asymptotically the maximum proportion of edge additions plus edge deletions applied to a graph of edge density p sufficient to ensure that the resulting graph satisfies $$\mathcal{H}$$ . The edit distance function is directly related to other well-studied quantities such as the speed function for $$\mathcal{H}$$ and the $$\mathcal{H}$$ -chromatic number of a random graph. Let $$\mathcal{H}$$ be the property of forbidding an Erdős–Rényi random graph $$F\sim \mathbb{G}(n_0,p_0)$$ , and let $$\varphi$$ represent the golden ratio. In this paper, we show that if $$p_0\in [1-1/\varphi,1/\varphi]$$ , then a.a.s. as $$n_0\to\infty$$ , \begin{align*} {\textrm{ed}}_{\mathcal{H}}(p) = (1+o(1))\,\frac{2\log n_0}{n_0} \cdot\min\left\{ \frac{p}{-\log(1-p_0)}, \frac{1-p}{-\log p_0} \right\}. \end{align*} Moreover, this holds for $$p\in [1/3,2/3]$$ for any $$p_0\in (0,1)$$ . A primary tool in the proof is the categorization of p -core coloured regularity graphs in the range $$p\in[1-1/\varphi,1/\varphi]$$ . Such coloured regularity graphs must have the property that the non-grey edges form vertex-disjoint cliques. 

Abstract For a planar graph , let denote the maximum number of copies of in an ‐vertex planar graph. In this paper, we prove that , , , and , where is the 1‐subdivision of . In addition, we obtain significantly improved upper bounds on and for . For a wide class of graphs , the key technique developed in this paper allows us to bound in terms of an optimization problem over weighted graphs.