Interaction between skew-representability, tensor products, extension properties, and rank inequalities
Krist\'of B\'erczi, Bogl\'arka Geh\'er, Andr\'as Imolay, L\'aszl\'o Lov\'asz, Carles Padr\'o, Tam\'as Schwarcz

TL;DR
This paper introduces a tensor product framework to characterize skew-representable matroids, providing new insights into their structure, decidability, and associated rank inequalities, with implications for combinatorics and linear algebra.
Contribution
It offers a novel tensor product approach to characterize skew-representability and derive new rank inequalities, advancing understanding of matroid representability over skew fields.
Findings
Characterization of skew-representable matroids via tensor products
Decidability results: co-recursive enumerability of non-representability
New linear rank inequality for folded skew-representable matroids
Abstract
Skew-representable matroids form a fundamental class in matroid theory, bridging combinatorics and linear algebra. They play an important role in areas such as coding theory, optimization, and combinatorial geometry, where linear structure is crucial for both theoretical insights and algorithmic applications. Since deciding skew-representability is computationally intractable, much effort has been focused on identifying necessary or sufficient conditions for a matroid to be skew-representable. In this paper, we introduce a novel approach to studying skew-representability and structural properties of matroids and polymatroid functions via tensor products. We provide a characterization of skew-representable matroids, as well as of those representable over skew fields of a given prime characteristic, in terms of tensor products. As an algorithmic consequence, we show that deciding…
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Taxonomy
TopicsMatrix Theory and Algorithms
