THE PENALTY METHOD FOR RANDOM WALKS WITH UNCERTAIN ENERGIES

@inproceedings{Ceperley1999THEPM,
  title={THE PENALTY METHOD FOR RANDOM WALKS WITH UNCERTAIN ENERGIES},
  author={David M. Ceperley and Mark Dewing},
  year={1999}
}
We generalize the Metropolis et al. random walk algorithm to the situation where the energy is noisy and can only be estimated. Two possible applications are for long range potentials and for mixed quantum-classical simulations. If the noise is normally distributed, we are able to modify the acceptance probability by applying a penalty to the energy difference and thereby achieve exact sampling even with very strong noise. When one has to estimate the variance we have an approximate formula… CONTINUE READING

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