Matrix Quasi-tree Theorem
Qingying Deng, Xian'an Jin, Qi Yan, Yexiang Yan
TL;DR
The paper generalizes the Matrix Tree Theorem to all embedded graphs by introducing symbolic skew-adjacency matrices and a reduction map that convert determinants into polynomials encoding spanning quasi-trees. The central result, the Matrix Quasi-tree Theorem, shows that $f(\det(I_n + \mathbf{A_{\\sigma}^s})) \\bmod 2$ equals the edge-sets of spanning quasi-trees, enabling the exact counting of quasi-trees via polynomial evaluation. The authors develop the framework of ribbon graphs, partial duality, and delta-matroids to extend the result from bouquets to general connected ribbon graphs, providing a complete topological analogue to Kirchhoff's theorem for orientable and non-orientable embeddings. This establishes new algebraic tools for quasi-tree enumeration and links to delta-matroid theory and topological graph concepts.
Abstract
Building on prior work that established Matrix Quasi-tree Theorems for special embedded graphs, in this paper, we develop a comprehensive theory applicable to all embedded graphs. We introduce symbolic skew-adjacency matrices and reduction maps as key innovations, and prove that a specific polynomial derived from these matrices encodes all spanning quasi-trees of a bouquet. This result provides a complete analogue of the Matrix Tree Theorem for topological graph theory, with applications to quasi-tree enumeration in both orientable and non-orientable embedded graphs.
