It seems that Goemans and Williamson give a unique representation for each graph of the semidefinite relaxation (elements $y_{ij}$ of Y). However, semidefinite programming may give the same maximum value of the objective function for different matrices Y, if I am correct. This means that you may get up to more than one unique representation in n dimensions of a graph. Can somebody tell me if this is correct please?PS: the Cholesky decomposition we do, gives a unique set of n vectors after finding Y, however I believe that Y is not necessarily unique, so you may get many different sets of vectors $v_{ij}$.
Gram matrix of Max-Cut relaxation
ds.algorithms;max cut;semidefinite programming