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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 $$ f(theta_1, dots, theta_n) = sum_{i,j=1}^{n} a_{ij} cos{(theta_i - theta_j)}$$ 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 $cos{(theta_i - theta_j)}$ with an explicit function $g_{varepsilon}(theta_i - theta_j)$ global minima of this new functional lead to a $(1-varepsilon)$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.
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 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 solu
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
Many coordination phenomena are based on a synchronisation process, whose global behaviour emerges from the interactions among the individual parts. Often in Nature, such self-organising mechanism allows the system to behave as a whole and thus groun
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