Sorting as Gradient Flow on the Permutohedron

We investigate how sorting algorithms efficiently overcome the exponential size of the permutation space. Our main contribution is a new continuous-time formulation of sorting as a gradient flow on the permutohedron, yielding an independent proof of the classical $Ω(n \log n)$ lower bound for comparison-based sorting. This formulation reveals how exponential contraction of disorder occurs under simple geometric dynamics. In support of this analysis, we present algebraic, combinatorial, and geometric perspectives, including decision-tree arguments and linear constraints on the permutohedron. The idea that efficient sorting arises from structure-guided logarithmic reduction offers a unifying lens for how comparisons tame exponential spaces. These observations connect to broader questions in theoretical computer science, such as whether the existence of structure can explain why certain computational problems permit efficient solutions.