Optimal solutions and ranks in the max-cut SDP
Optimization and Control
2021-09-07 v1
Abstract
The max-cut problem is a classical graph theory problem which is NP-complete. The best polynomial time approximation scheme relies on \emph{semidefinite programming} (SDP). We study the conditions under which graphs of certain classes have rank~1 solutions to the max-cut SDP. We apply these findings to look at how solutions to the max-cut SDP behave under simple combinatorial constructions. Our results determine when solutions to the max-cut SDP for cycle graphs are rank~1. We find the solutions to the max-cut SDP of the vertex~sum of two graphs. We then characterize the SDP solutions upon joining two triangle graphs by an edge~sum.
Cite
@article{arxiv.2109.02238,
title = {Optimal solutions and ranks in the max-cut SDP},
author = {Daniel Hong and Hyunwoo Lee and Alex Wei},
journal= {arXiv preprint arXiv:2109.02238},
year = {2021}
}
Comments
18 pages, 1 figure