where U is the potential energy of the system. It is worth mentioning that the above equation is only strictly valid in the thermodynamic limit, when both left and right sides of the equation are unique numbers. However, for finite systems with limited sampling of phase space, these quantities are stochastic variables with associated probability distributions. This is due to the extreme sensitivity of MD simulations to their initial conditions, which leads to differences in the configurations sampled for each repeat simulation and cause fluctuations in free energies obtained using equation 2. Therefore, when performing a single MD simulation at each intermediate λ state, every repeat calculation will yield a different result, which makes it unreliable. Thus, an ensemble simulation is necessary to bring such stochastic uncertainties under control. In this study, we employ an ensemble-simulation based method called "Thermodynamic Integration with Enhanced Sampling (TIES)" that involves performing an ensemble of MD simulations at each λ state and integrating the ensemble averaged energy derivative in equation 2 using stochastic calculus. The resultant free energies are reported along with proper estimates of associated aleatoric uncertainties.