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Two Linear Programs are Better than One

Alexander E. Black, Christoph Hertrich, Stefan Kober, Georg Loho

Source record

Source: arXiv

Published: Oct 11, 2026

arXiv: 2610.15909

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Source abstract

The extension complexity xc⁡(P)\operatorname{xc}(P) of a polytope PP is the minimum number of facets of a polytope that projects onto it. Motivated by the complexity of neural networks, Hertrich and Loho introduced the virtual extension complexity vxc⁡(P)\operatorname{vxc}(P) of a polytope PP, which is the minimum of xc⁡(Q)+xc⁡(R)\operatorname{xc}(Q) + \operatorname{xc}(R) among all polytopes QQ and RR such that P+Q=RP+Q=R. We show the following results pertaining to virtual extension complexity. First, we resolve the core open problem on the topic by showing the virtual extension complexity can be exponentially smaller than extension complexity. Second, we show there are matroid base polytopes with exponential virtual extension complexity by adapting a semi-algebraic counting argument by Hrubeš that extends the counting arguments of Rothvoss. Finally, we show that the maximum virtual extension complexity of a polygon with nn vertices is Θ(n)Θ(\sqrt{n}). This resolves an analogue of a question on extension complexity of Fiorini, Rothvoss, and Tiwary in 2011 in the case of virtual extension complexity.

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Two Linear Programs are Better than One — Mathematical Frontier Network