Reverse Monte Carlo (RMC) is a computational technique used primarily in the fields of materials science and crystallography to model and analyze the structures of materials, particularly those that are disordered, such as amorphous solids or liquids. Unlike traditional Monte Carlo methods, which typically start with an initial model and sample configurations that mimic a known distribution, RMC starts with experimental data and seeks configurations that can reproduce that data.
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