(588f) Uncertainty Quantification in Transition-Matrix Monte Carlo Simulations

Flat histogram methods vastly improve the efficiency of Monte Carlo methods used to simulate a wide variety of phenomena including phase equilibrium, self-assembly and aggregation in biological materials, colloids, polymers, ionic liquids and other complex fluids. However, the iterative convergence of these methods complicates quantification of the uncertainty. We develop a methodology for on-the-fly quantification of uncertainty in transition-matrix Monte Carlo simulations of fluid phase separation and self-assembly with Van der Waals and charged interactions. This new methodology will be compared with existing methods by considering both accuracy and efficiency.