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Statistical errors and application to QMC

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Motivated by the observation that outliers appear to occur more frequently in QMC results than in statistics from other sources, I will present an investigation into factors influencing the distribution of results.

First, we examine uncertainty in the correlation length and show that this serves to increase the probability of observing energies more than one error bar from the mean. We then extend the work to non-Gaussian distributions of local energies and show that this exacerbates the effect. We will touch briefly on the analogue of the central limit theorem that is applicable.

The talk will finish with a comparison between the predictions of this simple theory and real variational Monte Carlo data.

This talk is part of the Electronic Structure Discussion Group series.

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