Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 148 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 20 tok/s Pro
GPT-5 High 22 tok/s Pro
GPT-4o 87 tok/s Pro
Kimi K2 185 tok/s Pro
GPT OSS 120B 461 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Simple vertex coloring algorithms (2102.07089v1)

Published 14 Feb 2021 in cs.DS and quant-ph

Abstract: Given a graph $G$ with $n$ vertices and maximum degree $\Delta$, it is known that $G$ admits a vertex coloring with $\Delta + 1$ colors such that no edge of $G$ is monochromatic. This can be seen constructively by a simple greedy algorithm, which runs in time $O(n\Delta)$. Very recently, a sequence of results (e.g., [Assadi et. al. SODA'19, Bera et. al. ICALP'20, Alon Assadi Approx/Random'20]) show randomized algorithms for $(\epsilon + 1)\Delta$-coloring in the query model making $\tilde{O}(n\sqrt{n})$ queries, improving over the greedy strategy on dense graphs. In addition, a lower bound of $\Omega(n\sqrt n)$ for any $O(\Delta)$-coloring is established on general graphs. In this work, we give a simple algorithm for $(1 + \epsilon)\Delta$-coloring. This algorithm makes $O(\epsilon{-1/2}n\sqrt{n})$ queries, which matches the best existing algorithms as well as the classical lower bound for sufficiently large $\epsilon$. Additionally, it can be readily adapted to a quantum query algorithm making $\tilde{O}(\epsilon{-1}n{4/3})$ queries, bypassing the classical lower bound. Complementary to these algorithmic results, we show a quantum lower bound of $\Omega(n)$ for $O(\Delta)$-coloring.

Summary

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

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube