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We study the 2-offer semirandom 3-uniform hypergraph model on vertices. At each step, we are presented with 2 uniformly random vertices. We choose any other vertex, thus creating a hyperedge of size 3. We show a strategy that constructs a perfect matching, and another that constructs a loose Hamilton cycle, both succeeding asymptotically almost surely within steps. Both results extend to -uniform hypergraphs. The challenges with hypergraphs, and our methods, are qualitatively different from what has been seen for semirandom graphs. Much of our analysis is done on an auxiliary graph that is a uniform -out subgraph of a random bipartite graph, and this tool may be useful in other contexts.

生成讲解博客的中文版本

生成AI智能校验的中文版本