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Abstract We present a refinement of the classical alteration method for constructing ‐free graphs for suitable edge‐probabilities , we show that removing all edges in ‐copies of the binomial random graph does not significantly change the independence number. This differs from earlier alteration approaches of Erdős and Krivelevich, who obtained similar guarantees by removing one edge from each ‐copy (instead of all of them). We demonstrate the usefulness of our refined alternation method via two applications to online graph Ramsey games, where it enables easier analysis.more » « less
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Abstract The clique chromatic number of a graph is the smallest number of colors in a vertex coloring so that no maximal clique is monochromatic. In 2016 McDiarmid, Mitsche and Prałat noted that around the clique chromatic number of the random graph changes by when we increase the edge‐probability by , but left the details of this surprising “jump” phenomenon as an open problem. We settle this problem, that is, resolve the nature of this polynomial “jump” of the clique chromatic number of the random graph around edge‐probability . Our proof uses a mix of approximation and concentration arguments, which enables us to (i) go beyond Janson's inequality used in previous work and (ii) determine the clique chromatic number of up to logarithmic factors for any edge‐probability .more » « less
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Abstract We consider rooted subgraphs in random graphs, that is, extension counts such as (i) the number of triangles containing a given vertex or (ii) the number of paths of length three connecting two given vertices. In 1989, Spencer gave sufficient conditions for the event that, with high probability, these extension counts are asymptotically equal for all choices of the root vertices. For the important strictly balanced case, Spencer also raised the fundamental question as to whether these conditions are necessary. We answer this question by a careful second moment argument, and discuss some intriguing problems that remain open.more » « less
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null (Ed.)For $$r \ge 2$$, let $$X$$ be the number of $$r$$-armed stars $$K_{1,r}$$ in the binomial random graph $$G_{n,p}$$. We study the upper tail $${\mathbb P}(X \ge (1+\epsilon){\mathbb E} X)$$, and establish exponential bounds which are best possible up to constant factors in the exponent (for the special case of stars $$K_{1,r}$$ this solves a problem of Janson and Ruciński, and confirms a conjecture by DeMarco and Kahn). In contrast to the widely accepted standard for the upper tail problem, we do not restrict our attention to constant $$\epsilon$$, but also allow for $$\epsilon \ge n^{-\alpha}$$ deviations.more » « less
