Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
140 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Shameful Inequalities for List and DP Coloring of Graphs (2412.16790v1)

Published 21 Dec 2024 in math.CO

Abstract: The chromatic polynomial of a graph is an important notion in algebraic combinatorics that was introduced by Birkhoff in 1912; denoted $P(G,k)$, it equals the number of proper $k$-colorings of graph $G$. Enumerative analogues of the chromatic polynomial of a graph have been introduced for two well-studied generalizations of ordinary coloring, namely, list colorings: $P_{\ell}$, the list color function (1990); and DP colorings: $P_{DP}$, the DP color function (2019), and $P*_{DP}$, the dual DP color function (2021). For any graph $G$ and $k \in \mathbb{N}$, $P_{DP}(G, k) \leq P_\ell(G,k) \leq P(G,k) \leq P_{DP}*(G,k)$. In 2000, Dong settled a conjecture of Bartels and Welsh from 1995 known as the Shameful Conjecture by proving that for any $n$-vertex graph $G$, $P(G,k+1)/(k+1)n \geq P(G,k)/kn$ for all $k \in \mathbb{N}$ satisfying $k \geq n-1$. In contrast, for infinitely many positive integers $n$, Seymour (1997) gave an example of an $n$-vertex graph for which the above inequality does not hold for some $k = \Theta(n/ \log n)$. In this paper, we consider analogues of Dong's result for list and DP color functions. Specifically, in contrast to the chromatic polynomial, we prove that for any $n$-vertex graph $G$, $P_{\ell}(G,k+1)/(k+1)n \geq P_{\ell}(G,k)/kn$ and $P_{DP}(G,k+1)/(k+1)n \geq P_{DP}(G,k)/kn$ for all $k \in \mathbb{N}$. For the dual DP analogue of these inequalities, we show that there is a graph $G$ and $k \in \mathbb{N}$ such that $P_{DP}*(G,k+1)/(k+1)n < P_{DP}*(G,k)/kn$, and we prove $P_{DP}*(G,k+1)/(k+1)n \geq P_{DP}*(G,k)/kn$ for all $k \in \mathbb{N}$ satisfying $k \geq n-1$ when $G$ is an $n$-vertex complete bipartite graph.

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com