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Reconstruction of effective potential from statistical analysis of dynamic trajectories

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arxiv 2002.12193 v1 pith:WEC2QYGL submitted 2020-02-27 cond-mat.mes-hall cond-mat.mtrl-sciphysics.comp-ph

Reconstruction of effective potential from statistical analysis of dynamic trajectories

Ali Yousefzadi Nobakht , Ondrej Dyck , David B. Lingerfelt , Feng Bao , Maxim Ziatdinov , Artem Maksov , Bobby G. Sumpter , Richard Archibald
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Stephen Jesse Sergei V. Kalinin Kody J.H. Law
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classification cond-mat.mes-hall cond-mat.mtrl-sciphysics.comp-ph
keywords effectivestatisticalanalysisatomicdevelopdynamicobservedreconstruction
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The broad incorporation of microscopic methods is yielding a wealth of information on atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here we develop a method for stochastic reconstruction of effective acting potentials from observed trajectories. Using the Silicon vacancy defect in graphene as a model, we develop a statistical framework to reconstruct the free energy landscape from calculated atomic displacements.

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