ASSTG Articles
Permanent URI for this collectionhttps://hdl.handle.net/2104/5502
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Browsing ASSTG Articles by Author "Ding, Zhiyue"
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Item A machine learning-based Bayesian optimization solution to nonlinear responses in dusty plasmas(IOP PUblishing, 2021-06) Ding, Zhiyue; Matthews, Lorin; Hyde, TruellNonlinear frequency response analysis is a widely used method for determining system dynamics in the presence of nonlinearities. In dusty plasmas, the plasma–grain interaction (e.g. grain charging fluctuations) can be characterized by a single-particle non-linear response analysis, while grain–grain non-linear interactions can be determined by a multi-particle non-linear response analysis. Here a machine learning-based method to determine the equation of motion in the non-linear response analysis for dust particles in plasmas is presented. Searching the parameter space in a Bayesian manner allows an efficient optimization of the parameters needed to match simulated non-linear response curves to experimentally measured non-linear response curves.