We obtain complete characterizations of the Unique Bipartite Perfect Matching function, and of its Boolean dual, using multilinear polynomials over the reals. Building on previous results, we show that, surprisingly, the dual description is sparse and has low $\ell_1$-norm -- only exponential in $\Theta(n \log n)$, and this result extends even to other families of matching-related functions. Our approach relies on the M\"obius numbers in the matching-covered lattice, and a key ingredient in our proof is M\"obius' inversion formula. These polynomial representations yield complexity-theoretic results. For instance, we show that unique bipartite matching is evasive for classical decision trees, and nearly evasive even for generalized query models. We also obtain a tight $\Theta(n \log n)$ bound on the log-rank of the associated two-party communication task.
翻译:我们获得了单一双边完美匹配功能的完整描述, 以及它的双布尔值的完整描述, 使用多线性多元匹配对真实值。 我们根据先前的结果, 令人惊讶地显示, 双向描述很少, 低$\ ell_ 1$- norm -- 仅以$\ Theta( n\log n) 指数计算, 而这个结果甚至延伸到匹配相关功能的其他家族。 我们的方法在匹配覆盖的 lattice 中依赖于 M\ “ obius ” 数字, 而我们证据中的一个关键成分是 M\ “ Obius ” 的反向公式。 这些多线性表示产生复杂的理论结果。 例如, 我们显示, 独特的双向匹配对于传统的决策树是蒸发的, 甚至对于通用的查询模型也几乎是蒸发的 。 我们还在相关的双方通信任务的日志顺序上得到了紧紧的 $\ Theta( n) $( log n) 。