Recursive McCormick relaxations have been among the most popular convexification techniques for binary polynomial optimization problems. It is well-understood that both the quality and the size of these relaxations depend on the recursive sequence and finding an optimal recursive sequence amounts to solving a difficult combinatorial optimization problem. In this paper, we prove that any recursive McCormick relaxation is implied by the extended flower relaxation, a simple linear programming relaxation, which for binary polynomial optimization problems with fixed degree can be solved in strongly polynomial time.

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under review

## Article

View On the strength of recursive McCormick relaxations for binary polynomial optimization