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 $\left\{θ_1, θ_2, \dots, θ_n\right\} \subset [0, 2π]$, minima of the energy $$ f(θ_1, \dots, θ_n) = \sum_{i,j=1}^{n} a_{ij} \cos{(θ_i - θ_j)}$$ 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 $\cos{(θ_i - θ_j)}$ with an explicit function $g_{\varepsilon}(θ_i - θ_j)$ 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.