Papers › Spectral partitioning of graphs into compact, connected regions

Spectral partitioning of graphs into compact, connected regions

16 Jun 2025arXiv:2506.13982links table onlyarchive 2025-07-28

Ewan Davies, Ryan Job, Maxine Kampbell, Hannah Kim, Hyojin Seo

The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.

We define and study a spectral recombination algorithm, SpecReCom, for partitioning a graph into a given number of connected parts. It is straightforward to introduce additional constraints such as the requirement that the weight (or number of vertices) in each part is approximately balanced, and we exemplify this by stating a variant, BalSpecReCom, of the SpecReCom algorithm. We provide empirical evidence that the algorithm achieves more compact partitions than alternatives such as RevReCom by studying a 56×56 grid graph and a planar graph obtained from the state of Colorado.

PaperPDFCode

Code

maxflorescence/spectral_redistricting officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections