We extend the definitions of complexity measures of functions to domains such as the symmetric group. The complexity measures we consider include degree, approximate degree, decision tree complexity, sensitivity, block sensitivity, and a few others. We show that these complexity measures are polynomially related for the symmetric group and for many other domains. To show that all measures but sensitivity are polynomially related, we generalize classical arguments of Nisan and others. To add sensitivity to the mix, we reduce to Huang's sensitivity theorem using "pseudo-characters", which witness the degree of a function. Using similar ideas, we extend the characterization of Boolean degree 1 functions on the symmetric group due to Ellis, Friedgut and Pilpel to the perfect matching scheme. As another application of our ideas, we simplify the characterization of maximum-size $t$-intersecting families in the symmetric group and the perfect matching scheme.
翻译:我们将功能的复杂度度量的定义扩大到对称组等领域。 我们考虑的复杂度度量包括程度、近似度、决定树复杂性、敏感性、区块敏感性和其他几个领域。 我们显示这些复杂度度量与对称组和许多其他领域有多元性关联。 要显示除灵敏度之外的所有度量都与多元性相关, 我们将尼桑等的古典理论推广为典型的。 为了给组合增加敏感性, 我们使用“ 假体- 字符” 来降低黄蜂的敏感度定理, 以证明函数的程度 。 我们使用类似的想法, 将因艾利斯、 弗里德古特 和 Pilpel 而在对称组中的布尔特一级功能的定性扩大到完美匹配计划。 作为我们思想的另一个应用, 我们简化了对称组和完美匹配计划中最大规模的$t- intercommect 家庭的定性。