Monte Carlo eigenvalue and variance estimates from several functional optimizations

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Abstract
Using several simple systems as examples, we show that the choice of optimization functional can have a significant influence on the accuracy of variational Monte Carlo calculations. In addition, we demonstrate that the Monte Carlo analog of the Rayleigh–Ritz procedure, which explicitly orthogonalizes ground and excited states, can be used to produce accurate eigenvalue and variance estimates of excited states.