Communication: A multiscale Bayesian inference approach to analyzing subdiffusion in particle trajectories - Archive ouverte HAL
Article Dans Une Revue The Journal of Chemical Physics Année : 2016

Communication: A multiscale Bayesian inference approach to analyzing subdiffusion in particle trajectories

Résumé

Anomalous diffusion is characterized by its asymptotic behavior for t → ∞. This makes it difficult to detect and describe in particle trajectories from experiments or computer simulations, which are necessarily of finite length. We propose a new approach using Bayesian inference applied directly to the observed trajectories sampled at different time scales. We illustrate the performance of this approach using random trajectories with known statistical properties and then use it for analyzing the motion of lipid molecules in the plane of a lipid bilayer.

Dates et versions

hal-02154066 , version 1 (12-06-2019)

Identifiants

Citer

Konrad Hinsen, Gérald Kneller. Communication: A multiscale Bayesian inference approach to analyzing subdiffusion in particle trajectories. The Journal of Chemical Physics, 2016, 145 (15), pp.151101-151106. ⟨10.1063/1.4965881⟩. ⟨hal-02154066⟩
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