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arXiv · 2511.02406

Arithmetic Circuits and Neural Networks for Regular Matroids

Christoph Hertrich·Stefan Kober·Georg Loho
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Abstract

We prove that there exist uniform $(+,\times,/)$-circuits of size $O(n^3)$ to compute the basis generating polynomial of regular matroids on $n$ elements. By tropicalization, this implies that there exist uniform $(\max,+,-)$-circuits and ReLU neural networks of the same size for weighted basis maximization of regular matroids. As a consequence in linear programming theory, we obtain a first example where taking the difference of two extended formulations can be more efficient than the best known individual extended formulation of size $O(n^6)$ by Aprile and Fiorini. Such differences have recently been introduced as virtual extended formulations. The proof of our main result relies on a fine-tuned version of Seymour's decomposition of regular matroids which allows us to identify and maintain graphic substructures to which we can apply a local version of the star-mesh transformation.

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BibTeXRIS

Christoph Hertrich, Stefan Kober, Georg Loho. 2025-11-04. Arithmetic Circuits and Neural Networks for Regular Matroids. https://arxiv.org/abs/2511.02406

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