English

Max-Cut via Kuramoto-type Oscillators

Optimization and Control 2021-02-10 v1 Data Structures and Algorithms

Abstract

We consider the Max-Cut problem. Let G=(V,E)G = (V,E) be a graph with adjacency matrix (aij)i,j=1n(a_{ij})_{i,j=1}^{n}. Burer, Monteiro & Zhang proposed to find, for nn angles {θ1,θ2,,θn}[0,2π]\left\{\theta_1, \theta_2, \dots, \theta_n\right\} \subset [0, 2\pi], minima of the energy f(θ1,,θn)=i,j=1naijcos(θiθj) f(\theta_1, \dots, \theta_n) = \sum_{i,j=1}^{n} a_{ij} \cos{(\theta_i - \theta_j)} because configurations achieving a global minimum leads to a partition of size 0.878 Max-Cut(G). This approach is known to be computationally viable and leads to very good results in practice. We prove that by replacing cos(θiθj)\cos{(\theta_i - \theta_j)} with an explicit function gε(θiθj)g_{\varepsilon}(\theta_i - \theta_j) global minima of this new functional lead to a (1ε)(1-\varepsilon)Max-Cut(G). This suggests some interesting algorithms that perform well. It also shows that the problem of finding approximate global minima of energy functionals of this type is NP-hard in general.

Keywords

Cite

@article{arxiv.2102.04931,
  title  = {Max-Cut via Kuramoto-type Oscillators},
  author = {Stefan Steinerberger},
  journal= {arXiv preprint arXiv:2102.04931},
  year   = {2021}
}
R2 v1 2026-06-23T22:59:13.697Z