Monte Carlo Sampling

• MC method permits great flexibility in developing improved sampling methods

• Biasing methods improve sampling without changing the limiting distribution

  • Modification of trial probabilities compensated by changes in acceptance and reverse-trial probabilities

• Non-Boltzmann sampling methods modify the limiting distribution

  • Desired ensemble average obtained by taking a weighted average over the non-Boltzmann sample

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