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Enumeration and constructions of vertices of the polytope of polystochastic matrices

Anna A. Taranenko

TL;DR

This work advances the understanding of the Birkhoff polytope $\Omega_n^d$ for small dimensions by fully enumerating vertices of $\Omega_3^4$ (24 vertices across 21 equivalence classes with a notable symmetric subset) and $\Omega_4^3$ (533 equivalence classes, including symmetric cases), correcting prior results. It introduces algorithmic strategies that link vertex structure to supports via incidence matrices, and demonstrates new vertex-construction techniques based on multidimensional matrix products, including a broad family of symmetric vertices for $\Omega_3^d$ with explicit size formulas for the support and detailed permanence properties. The paper also connects these combinatorial objects to hypergraph fractional transversals, providing a unified framework for generating and analyzing vertices through Kronecker and dot products and hyperplane-structured constructions. Overall, the results yield both exact enumerations for small cases and scalable construction methods that push toward understanding vertices of high-dimensional polystochastic polytopes and their permanents.

Abstract

A multidimensional nonnegative matrix is called polystochastic if the sum of entries in each of its lines equals $1$. The set of all polystochastic matrices of order $n$ and dimension $d$ is a convex polytope $Ω_n^d$ known as the Birkhoff polytope. In this paper, we identify all vertices of the polytopes $Ω_4^3$ and $Ω_3^4$ correcting the results of Ke, Li, and Xiao (2016). Additionally, we describe constructions vertices of $Ω_n^d$ using multidimensional matrix products and find symmetric vertices of $Ω_3^d$ for all $d \geq 4$ with large support sizes.

Enumeration and constructions of vertices of the polytope of polystochastic matrices

TL;DR

This work advances the understanding of the Birkhoff polytope for small dimensions by fully enumerating vertices of (24 vertices across 21 equivalence classes with a notable symmetric subset) and (533 equivalence classes, including symmetric cases), correcting prior results. It introduces algorithmic strategies that link vertex structure to supports via incidence matrices, and demonstrates new vertex-construction techniques based on multidimensional matrix products, including a broad family of symmetric vertices for with explicit size formulas for the support and detailed permanence properties. The paper also connects these combinatorial objects to hypergraph fractional transversals, providing a unified framework for generating and analyzing vertices through Kronecker and dot products and hyperplane-structured constructions. Overall, the results yield both exact enumerations for small cases and scalable construction methods that push toward understanding vertices of high-dimensional polystochastic polytopes and their permanents.

Abstract

A multidimensional nonnegative matrix is called polystochastic if the sum of entries in each of its lines equals . The set of all polystochastic matrices of order and dimension is a convex polytope known as the Birkhoff polytope. In this paper, we identify all vertices of the polytopes and correcting the results of Ke, Li, and Xiao (2016). Additionally, we describe constructions vertices of using multidimensional matrix products and find symmetric vertices of for all with large support sizes.

Paper Structure

This paper contains 7 sections, 13 theorems, 51 equations.

Key Result

Proposition 1

Let $A$ be a vertex of the polytope of $d$-dimensional polystochastic matrices of order $n$. Then for the size $N(A)$ of the support of $A$ we have

Theorems & Definitions (31)

  • Proposition 1: JurRys.stochmatrmy.obzor
  • Conjecture 1: my.obzor
  • Proposition 2: JurRys.stochmatr
  • Proposition 3
  • proof
  • Proposition 4
  • proof
  • Proposition 5: JurRys.stochmatr
  • Proposition 6
  • Claim 1
  • ...and 21 more