The first experimental evidence of quantum Drude oscillator behavior in liquids is uncovered using probabilistic machine learning-augmented iterative Boltzmann inversion applied to noble gas radial distribution functions. Furthermore, classical force fields for noble gases are shown to be reduced to a single parameter through simple empirical relations linked to atomic dipole polarizability. These findings highlight how neutron scattering data can inspire innovative force field design and offer insight into interatomic forces to advance molecular simulations.

Department of Chemical Engineering and Materials Science University of Minnesota Minneapolis Minnesota 55455 USA

Department of Chemical Engineering University of Utah Salt Lake City Utah 84112 USA

Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Prague Czechia

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Physics-Informed Gaussian Process Inference of Liquid Structure from Scattering Data