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Maximizing subgraph counts in regular graphs

Gabor Lippner, Arturo Ortiz San Miguel

TL;DR

The paper addresses the problem of maximizing the $H$-density in $d$-regular graphs by recasting subgraph counts as injective and ordinary homomorphism densities and then embedding the problem into a spectral optimization framework. It introduces degree-$|V(H)|$ polynomials $p_H( ext{λ},d)$ that bound injective counts in terms of the spectrum $ ext{σ}(G)$ and proves that, for large $d$, extremizers are disjoint unions of either $K_{d,d}$ (when $H$ is bipartite) or $K_{d+1}$ (when $H$ is non-bipartite), with sharpness and uniqueness results tied to the spectral characterizations of these graphs. In the special case $H=C_5$, the threshold is $d eq 7$ and the unique optimal $3$-regular graph is the Petersen graph, while for larger $d$ the optimizers align with the corresponding clique structures; the paper also develops a general methodology and discusses near-optimal behavior and potential extensions to constrained extremal problems. Overall, the work provides a unified toolbox that blends homomorphism inequalities with spectral optimization to tackle Turán-type questions in regular graphs and offers a pathway to analyze a broad class of subgraph-count extremal problems.

Abstract

Given a graph $H$, we investigate the $d$-regular graphs $G$ with the highest $H$-density. We reframe the problem as a continuous optimization problem on the eigenvalues of $G$ by relating injective homomorphism numbers from $H$ and homomorphism numbers from quotient graphs of $H$. For almost all $H$, this relation has non-spectral terms, which require bounding by spectral terms in a way that is sharp at the optimal graph. For bipartite $H$ and $d$ large enough, we show $G$ consists of disjoint copies of $K_{d,d}$. For non-bipartite $H$ and $d$ sufficiently large, $G$ is a collection of disjoint $K_{d+1}$ graphs. For $H=C_5$ and $d=3$, disjoint Petersen graphs emerge.

Maximizing subgraph counts in regular graphs

TL;DR

The paper addresses the problem of maximizing the -density in -regular graphs by recasting subgraph counts as injective and ordinary homomorphism densities and then embedding the problem into a spectral optimization framework. It introduces degree- polynomials that bound injective counts in terms of the spectrum and proves that, for large , extremizers are disjoint unions of either (when is bipartite) or (when is non-bipartite), with sharpness and uniqueness results tied to the spectral characterizations of these graphs. In the special case , the threshold is and the unique optimal -regular graph is the Petersen graph, while for larger the optimizers align with the corresponding clique structures; the paper also develops a general methodology and discusses near-optimal behavior and potential extensions to constrained extremal problems. Overall, the work provides a unified toolbox that blends homomorphism inequalities with spectral optimization to tackle Turán-type questions in regular graphs and offers a pathway to analyze a broad class of subgraph-count extremal problems.

Abstract

Given a graph , we investigate the -regular graphs with the highest -density. We reframe the problem as a continuous optimization problem on the eigenvalues of by relating injective homomorphism numbers from and homomorphism numbers from quotient graphs of . For almost all , this relation has non-spectral terms, which require bounding by spectral terms in a way that is sharp at the optimal graph. For bipartite and large enough, we show consists of disjoint copies of . For non-bipartite and sufficiently large, is a collection of disjoint graphs. For and , disjoint Petersen graphs emerge.
Paper Structure (15 sections, 14 theorems, 51 equations, 3 figures)

This paper contains 15 sections, 14 theorems, 51 equations, 3 figures.

Key Result

Theorem 1.1

Let $H$ be a tree. Then for any $d \geq \Delta(H)$ we have

Figures (3)

  • Figure 1: A 3-regular graph with 5 edges through $e$ and a cut edge.
  • Figure 2: 4-regular graphs with high $C_5$ density
  • Figure 3: Maximal cases for $x_1=z_1,~x_2=z_2$ and $x_1=z_1,~x_2 \neq z_2$.

Theorems & Definitions (26)

  • Theorem 1.1
  • Theorem 1.2
  • Theorem 1.3
  • Remark 1.4
  • Proposition 1.5
  • Corollary 1.6
  • Proposition 1.7
  • Definition 2.1
  • Proposition 2.2: lovasz2012large
  • Proposition 2.3: lovasz2012large
  • ...and 16 more