Breaking the 2^n Barrier for Graph k-Coloring

in_between1 pts0 comments

[2607.27159] Breaking the $2^n$ barrier for graph $k$-coloring

0$ such that graph $k$-coloring can be solved by a randomized algorithm with one-sided error in time $O((2-\varepsilon_k)^n)$. Prior to this work and independent concurrent work of Zamir [arXiv, 2026], exponential improvements over the $2^n \cdot \mathrm{poly}(n)$-time algorithm of Björklund, Husfeldt, and Koivisto [SIAM Journal on Computing, 2009] were only known for $k \le 6$."/>

0$ such that graph $k$-coloring can be solved by a randomized algorithm with one-sided error in time $O((2-\varepsilon_k)^n)$. Prior to this..."/>

0$ such that graph $k$-coloring can be solved by a randomized algorithm with one-sided error in time $O((2-\varepsilon_k)^n)$. Prior to this work and independent concurrent work of Zamir [arXiv, 2026], exponential improvements over the $2^n \cdot \mathrm{poly}(n)$-time algorithm of Bj\"orklund, Husfeldt, and Koivisto [SIAM Journal on Computing, 2009] were only known for $k \le 6$." />

Skip to main content

Search arXiv

Press Enter to search · Advanced search

-->

Computer Science > Data Structures and Algorithms

arXiv:2607.27159 (cs)

[Submitted on 29 Jul 2026]

Title:Breaking the $2^n$ barrier for graph $k$-coloring

Authors:Kevin Pratt<br>View a PDF of the paper titled Breaking the $2^n$ barrier for graph $k$-coloring, by Kevin Pratt

View PDF

Abstract:We show that for all $k$, there exists $\varepsilon_k > 0$ such that graph $k$-coloring can be solved by a randomized algorithm with one-sided error in time $O((2-\varepsilon_k)^n)$. Prior to this work and independent concurrent work of Zamir [arXiv, 2026], exponential improvements over the $2^n \cdot \mathrm{poly}(n)$-time algorithm of Björklund, Husfeldt, and Koivisto [SIAM Journal on Computing, 2009] were only known for $k \le 6$.

Subjects:

Data Structures and Algorithms (cs.DS)

Cite as:<br>arXiv:2607.27159 [cs.DS]

(or<br>arXiv:2607.27159v1 [cs.DS] for this version)

https://doi.org/10.48550/arXiv.2607.27159

Focus to learn more

arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Kevin Pratt [view email]<br>[v1]<br>Wed, 29 Jul 2026 17:36:11 UTC (16 KB)

Full-text links:<br>Access Paper:

View a PDF of the paper titled Breaking the $2^n$ barrier for graph $k$-coloring, by Kevin Pratt<br>View PDF<br>TeX Source

view license

Current browse context:

cs.DS

next >

new<br>recent<br>| 2026-07

Change to browse by:

cs

References & Citations

NASA ADS<br>Google Scholar

Semantic Scholar

export BibTeX citation<br>Loading...

BibTeX formatted citation

&times;

loading...

Data provided by:

Bookmark

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Bibliographic Explorer (What is the Explorer?)

Connected Papers Toggle

Connected Papers (What is Connected Papers?)

Litmaps Toggle

Litmaps (What is Litmaps?)

scite.ai Toggle

scite Smart Citations (What are Smart Citations?)

Code, Data, Media

Code, Data and Media Associated with this Article

alphaXiv Toggle

alphaXiv (What is alphaXiv?)

Links to Code Toggle

CatalyzeX Code Finder for Papers (What is CatalyzeX?)

DagsHub Toggle

DagsHub (What is DagsHub?)

GotitPub Toggle

Gotit.pub (What is GotitPub?)

Huggingface Toggle

Hugging Face (What is Huggingface?)

ScienceCast Toggle

ScienceCast (What is ScienceCast?)

Demos

Demos

Replicate Toggle

Replicate (What is Replicate?)

Spaces Toggle

Hugging Face Spaces (What is Spaces?)

Spaces Toggle

TXYZ.AI (What is TXYZ.AI?)

Related Papers

Recommenders and Search Tools

Link to Influence Flower

Influence Flower (What are Influence Flowers?)

Core recommender toggle

CORE Recommender (What is CORE?)

Author

Venue

Institution

Topic

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Which authors of this paper are endorsers? |<br>Disable MathJax (What is MathJax?)

Major funding support from

toggle arxiv graph coloring algorithm time

Related Articles