Theoretical analysis demonstrates polynomial equivalence among complexity measures across the symmetric group, expanding classical Boolean sensitivity theorems.
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. Mathematics Subject Classifications: 06E30, 94D10 Keywords: Boolean functions, complexity measures
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Dafni et al. (2026) studied this question.