and $N_{\rm max}$, where $\hbar\Omega$ is the HO energy and $N_{\rm max}$ is the basis truncation parameter. In this approach, all possible configurations with $N_{\rm max}$ excitations above the unperturbed gs (the HO configuration with the minimum HO energy defined to be the $N_{\rm max} = 0$ configuration) are considered. Even values of $N_{\rm max}$ correspond to states with the same parity as the unperturbed gs and are called the “natural" parity states, while odd values of $N_{\rm max}$ correspond to states with “unnatural" parity.

Due to the strong short-range correlations of nucleons in a nucleus, a large basis space, or model space, one that is often not feasible, is required to achieve convergence. To obtain the gs energy and other observables as close as possible to the exact results one has to choose the largest feasible basis spaces. Next, if numerical convergence is not achieved, which is often the case, the results are extrapolated to the infinite model space. To take the infinite matrix limit, several extrapolation methods have been developed (see, for example, [@ExtrapolationMethods:2009]).

Artificial Neural Networks {#sec:ANNs}
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ANNs are powerful tools that can be used for function approximation, classification and pattern recognition, such as finding clusters 