Matroidal Entropy Functions: Constructions, Characterizations and Representations
Qi Chen, Minquan Cheng, Baoming Bai
TL;DR
This work defines matroidal entropy functions as $\mathbf{h} = \log v \cdot \mathbf{r}_M$ and develops a VOA-based framework that links matroids, partitions, and information-theoretic constraints. It provides constructions for VOAs under deletions, contractions, and binary matroid operations, and uses these to characterize matroidal entropy for regular matroids and for matroids sharing the $p$-characteristic set with $U_{2,4}$. A key contribution is the complete identification of the p-characteristic set for regular matroids and the characterization of a broad class of matroids with the same $\chi$ as $U_{2,4}$, via 3-connected components and wheel/whirl structures. The results yield both structural insights into the entropy region and practical implications for network coding and related information-theoretic problems, where matroidal entropy functions underpin capacity characterizations and code constructions.
Abstract
Matroidal entropy functions are entropy functions in the form $\mathbf{h} = \log v \cdot \mathbf{r}_M$ , where $v \ge 2$ is an integer and $\mathbf{r}_M$ is the rank function of a matroid $M$. They can be applied into capacity characterization and code construction of information theory problems such as network coding, secret sharing, index coding and locally repairable code. In this paper, by constructing the variable strength arrays of some matroid operations, we characterized matroidal entropy functions induced by regular matroids and some matroids with the same p-characteristic set as uniform matroid $U_{2,4}$.
