To accelerate the reruns further, the Python script has been parallelized using a parallel Python module to distribute the reruns over all available cores as each so that mapping, reevaluating configurations, and energy estimation can be run independently. After computing reduced potentials, the property estimation and final MSE estimation is also parallelized. The array of dimensionless free energies estimated by MBAR, f k , for the sampled states are stored and used as initial guesses for subsequent iterations. After the first iteration, the subsequent runs use only require updating the reduced energies relating to the new unsampled states. which reduces the rerun and energy estimation at each step to 22 (T) × 6 (F)) × 21 (P) = 2772 states.