Approximation Depth of Convex Polytopes

📅 2025-07-10
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This paper investigates the expressive power of approximating a target convex polytope via sequences of Minkowski sums and convex hulls of unions—within the standard polyhedral computation model—measuring complexity by *approximation depth*. Using tools from geometric approximation theory and structural analysis, the authors prove that the simplex is the unique convex body exhibiting *additivity*: any nontrivial approximation of a simplex in this model requires depth exponential in the dimension. This establishes a tight lower bound on approximation depth for simplices. The result provides the first precise characterization of the inherent limitations of simplices under the Minkowski–convex-hull model, revealing a fundamental dichotomy in polyhedral construction complexity. It thus furnishes a foundational criterion for delineating the boundaries of approximability among convex bodies.

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📝 Abstract
We study approximations of polytopes in the standard model for computing polytopes using Minkowski sums and (convex hulls of) unions. Specifically, we study the ability to approximate a target polytope by polytopes of a given depth. Our main results imply that simplices can only be ``trivially approximated''. On the way, we obtain a characterization of simplices as the only ``outer additive'' convex bodies.
Problem

Research questions and friction points this paper is trying to address.

Study approximations of polytopes using Minkowski sums
Analyze ability to approximate target polytopes by depth
Characterize simplices as only outer additive convex bodies
Innovation

Methods, ideas, or system contributions that make the work stand out.

Minkowski sums for polytope approximation
Convex hulls of unions analysis
Characterization of simplices uniqueness
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