4. Simulation data is then extracted from the output log files for each of the six GaMD simulations. Reweighting is then performed with several reweighting methods, i.e., cumulant expansion to the first order, second order, and third order, to recover the original free energy landscape. Then with the desired target number of walkers per macrostate n w , initial structures/configurations for WE are saved with appropriate weights from the binning probabilities. In the subsequent Results section, we show that GaMD has greater coverage of the free energy landscape and closer to steady-state probabilities compared to WE within the same simulation time. Even if WE has a similar amount of coverage of the free energy landscape compared to GaMD for some systems, GaMD has an advantage over WE with reweighting since appropriate probabilities or weights can be recovered from the added biasing potentials.