English

Algebraic combinatorial optimization on the degree of determinants of noncommutative symbolic matrices

Combinatorics 2023-10-25 v1 Data Structures and Algorithms

Abstract

We address the computation of the degrees of minors of a noncommutative symbolic matrix of form A[c]:=k=1mAktckxk, A[c] := \sum_{k=1}^m A_k t^{c_k} x_k, where AkA_k are matrices over a field K\mathbb{K}, xix_i are noncommutative variables, ckc_k are integer weights, and tt is a commuting variable specifying the degree. This problem extends noncommutative Edmonds' problem (Ivanyos et al. 2017), and can formulate various combinatorial optimization problems. Extending the study by Hirai 2018, and Hirai, Ikeda 2022, we provide novel duality theorems and polyhedral characterization for the maximum degrees of minors of A[c]A[c] of all sizes, and develop a strongly polynomial-time algorithm for computing them. This algorithm is viewed as a unified algebraization of the classical Hungarian method for bipartite matching and the weight-splitting algorithm for linear matroid intersection. As applications, we provide polynomial-time algorithms for weighted fractional linear matroid matching and linear optimization over rank-2 Brascamp-Lieb polytopes.

Keywords

Cite

@article{arxiv.2310.15502,
  title  = {Algebraic combinatorial optimization on the degree of determinants of noncommutative symbolic matrices},
  author = {Hiroshi Hirai and Yuni Iwamasa and Taihei Oki and Tasuku Soma},
  journal= {arXiv preprint arXiv:2310.15502},
  year   = {2023}
}