English

Palette Sparsification for Graphs with Sparse Neighborhoods

Data Structures and Algorithms 2024-11-05 v2 Discrete Mathematics Combinatorics

Abstract

A seminal palette sparsification result of Assadi, Chen, and Khanna states that in every nn-vertex graph of maximum degree Δ\Delta, sampling Θ(logn)\Theta(\log n) colors per vertex from {1,,Δ+1}\{1, \ldots, \Delta+1\} almost certainly allows for a proper coloring from the sampled colors. Alon and Assadi extended this work proving a similar result for O(Δ/logΔ)O\left(\Delta/\log \Delta\right)-coloring triangle-free graphs. Apart from being interesting results from a combinatorial standpoint, their results have various applications to the design of graph coloring algorithms in different models of computation. In this work, we focus on locally sparse graphs, i.e., graphs with sparse neighborhoods. We say a graph G=(V,E)G = (V, E) is kk-locally-sparse if for each vertex vVv \in V, the subgraph G[N(v)]G[N(v)] contains at most kk edges. A celebrated result of Alon, Krivelevich, and Sudakov shows that such graphs are O(Δ/log(Δ/k))O(\Delta/\log (\Delta/\sqrt{k}))-colorable. For any α(0,1)\alpha \in (0, 1) and kΔ2αk \ll \Delta^{2\alpha}, let GG be a kk-locally-sparse graph. For q=Θ(Δ/log(Δα/k))q = \Theta\left(\Delta/\log \left(\Delta^\alpha/\sqrt{k}\right)\right), we show that sampling O(Δα+logn)O\left(\Delta^\alpha + \sqrt{\log n}\right) colors per vertex is sufficient to obtain a proper qq-coloring of GG from the sampled colors. Setting k=1k = 1 recovers the aforementioned result of Alon and Assadi for triangle-free graphs. A key element in our proof is a proposition regarding correspondence coloring in the so-called color-degree setting, which improves upon recent work of Anderson, Kuchukova, and the author and is of independent interest.

Keywords

Cite

@article{arxiv.2408.08256,
  title  = {Palette Sparsification for Graphs with Sparse Neighborhoods},
  author = {Abhishek Dhawan},
  journal= {arXiv preprint arXiv:2408.08256},
  year   = {2024}
}

Comments

28 pages

R2 v1 2026-06-28T18:13:57.973Z