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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.
We consider the Max-Cut problem. Let $G = (V,E)$ be a graph with adjacency matrix $(a_{ij})_{i,j=1}^{n}$. Burer, Monteiro & Zhang proposed to find, for $n$ angles $left{theta_1, theta_2, dots, theta_nright} subset [0, 2pi]$, minima of the energy $$ f
We show that the linear or quadratic 0/1 program[P:quadmin{ c^Tx+x^TFx : :A,x =b;:xin{0,1}^n},]can be formulated as a MAX-CUT problem whose associated graph is simply related to the matrices $F$ and $A^TA$.Hence the whole arsenal of approximation tec
The Potts model has many applications. It is equivalent to some min-cut and max-flow models. Primal-dual algorithms have been used to solve these problems. Due to the special structure of the models, convergence proof is still a difficult problem. In
In this work, we initiate the study of fault tolerant Max Cut, where given an edge-weighted undirected graph $G=(V,E)$, the goal is to find a cut $Ssubseteq V$ that maximizes the total weight of edges that cross $S$ even after an adversary removes $k
We show that the smoothed complexity of the FLIP algorithm for local Max-Cut is at most $smash{phi n^{O(sqrt{log n})}}$, where $n$ is the number of nodes in the graph and $phi$ is a parameter that measures the magnitude of perturbations applied on it