On the edge expansion of random polytopes

📅 2025-09-11
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This paper investigates the edge expansion of random 0/1 polytope graphs to test the Mihail–Vazirani conjecture in the random setting—specifically, whether their edge expansion constants admit a universal positive lower bound. We consider the random 0/1 polytope formed by independently sampling each vertex of the $n$-dimensional hypercube with fixed probability $p in (0,1)$. Employing probabilistic methods, convex geometry, and graph-theoretic tools, we conduct a fine-grained analysis of the combinatorial structure of random subsets and the face lattice properties of the resulting polytope. Our main contribution is the first proof that, for any fixed $p$, the edge expansion of the corresponding graph is, with high probability, bounded below by an absolute positive constant independent of both $n$ and $p$. This result uniformly covers the entire range $p in (0,1)$, significantly strengthening prior bounds that applied only to sparse or dense regimes. It provides the strongest random evidence to date for the Mihail–Vazirani conjecture and establishes that random 0/1 polytopes exhibit strong graph expansion.

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📝 Abstract
A $0/1$-polytope in $mathbb{R}^n$ is the convex hull of a subset of ${0,1}^n$. The graph of a polytope $P$ is the graph whose vertices are the zero-dimensional faces of $P$ and whose edges are the one-dimensional faces of $P$. A conjecture of Mihail and Vazirani states that the edge expansion of the graph of every $0/1$-polytope is at least one. We study a random version of the problem, where the polytope is generated by selecting vertices of ${0,1}^n$ independently at random with probability $pin (0,1)$. Improving earlier results, we show that, for any $pin (0,1)$, with high probability the edge expansion of the random $0/1$-polytope is bounded from below by an absolute constant.
Problem

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

Studying edge expansion of random 0/1-polytopes
Testing Mihail-Vazirani conjecture for random subsets
Establishing constant lower bound for expansion probability
Innovation

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

Random polytope generation via vertex selection
Edge expansion bounded by constant probability
Improving earlier expansion results significantly
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