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Minimal H-factors and covers

Lorenzo Federico, Joel Larsson Danielsson

TL;DR

This paper analyzes the minimum-weight tiling of a fixed graph $H$ into a complete graph $K_n$ with i.i.d. edge weights, focusing on $H$-factors (vertex-disjoint copies covering all vertices) and $H$-covers (overlapping copies allowed). The authors develop a divide-and-conquer framework using a red-green edge-splitting trick to construct large low-cost partial $H$-factors and complete them with small additional cost, enabling sharp concentration around a scale $L_n=\Theta(n^{1-1/d^*})$, where $d^* = \max_{G\subseteq H} d_G$ is the maximum $1$-density of a subgraph of $H$. They prove lower and upper bounds, establish a concentration result around a median $M$ with $|F_H(\alpha n,n)-M|=O_{\mathbb{P}}(M^{3/4})$, and extend the discussion to $H$-covers, noting that sharp concentration may fail in unbalanced cases. Furthermore, they show the results hold under general edge-weight distributions with pseudo-dimension 1, via a coupling argument, and provide a detailed treatment of when $H$ is not balanced. The work advances understanding of random-weight tiling problems and demonstrates robust concentration phenomena for a broad class of structured graph completions.

Abstract

Given a fixed small graph H and a larger graph G, an H-factor is a collection of vertex-disjoint subgraphs $H'\subset G$, each isomorphic to H, that cover the vertices of G. If G is the complete graph $K_n$ equipped with independent U(0,1) edge weights, what is the lowest total weight of an H-factor? This problem has previously been considered for e.g.\ $H=K_2$. We show that if H contains a cycle, then the minimum weight is sharply concentrated around some $L_n = Θ(n^{1-1/d^*})$ (where $d^*$ is the maximum 1-density of any subgraph of H). Some of our results also hold for H-covers, where the copies of H are not required to be vertex-disjoint.

Minimal H-factors and covers

TL;DR

This paper analyzes the minimum-weight tiling of a fixed graph into a complete graph with i.i.d. edge weights, focusing on -factors (vertex-disjoint copies covering all vertices) and -covers (overlapping copies allowed). The authors develop a divide-and-conquer framework using a red-green edge-splitting trick to construct large low-cost partial -factors and complete them with small additional cost, enabling sharp concentration around a scale , where is the maximum -density of a subgraph of . They prove lower and upper bounds, establish a concentration result around a median with , and extend the discussion to -covers, noting that sharp concentration may fail in unbalanced cases. Furthermore, they show the results hold under general edge-weight distributions with pseudo-dimension 1, via a coupling argument, and provide a detailed treatment of when is not balanced. The work advances understanding of random-weight tiling problems and demonstrates robust concentration phenomena for a broad class of structured graph completions.

Abstract

Given a fixed small graph H and a larger graph G, an H-factor is a collection of vertex-disjoint subgraphs , each isomorphic to H, that cover the vertices of G. If G is the complete graph equipped with independent U(0,1) edge weights, what is the lowest total weight of an H-factor? This problem has previously been considered for e.g.\ . We show that if H contains a cycle, then the minimum weight is sharply concentrated around some (where is the maximum 1-density of any subgraph of H). Some of our results also hold for H-covers, where the copies of H are not required to be vertex-disjoint.
Paper Structure (19 sections, 17 theorems, 31 equations)

This paper contains 19 sections, 17 theorems, 31 equations.

Key Result

Theorem 1.1

Assume $H$ is a fixed graph with at least one cycle, $d^*>1$ is its maximum $1$-density as defined in subsection:density, and $O_\mathbb{P}$ is as defined in subsection:notation. Let the random variable $F_H=F_H(n)$ be the minimum weight of an $H$-factor on $K_n$ (equipped with i.i.d. uniform $[0,1]

Theorems & Definitions (26)

  • Theorem 1.1
  • Definition 2.1
  • Theorem 3.1
  • Conjecture 3.2
  • Theorem 3.3
  • Theorem 3.4: Theorems 2.1 & 2.2 in JohKahVu08
  • Corollary 3.5
  • Proposition 4.1
  • Lemma 4.2
  • Remark 4.3
  • ...and 16 more