期刊
JOURNAL OF STATISTICAL PHYSICS
卷 156, 期 5, 页码 896-907出版社
SPRINGER
DOI: 10.1007/s10955-014-1035-6
关键词
Anomalous diffusion; Model identification; Polymer; E. coli; Gulf of Mexico
资金
- NSF [EAR 1314828]
- Directorate For Geosciences
- Division Of Earth Sciences [1314828] Funding Source: National Science Foundation
Single particle tracking is a tool that is being increasingly used to study diffusive or dispersive processes in many branches of natural science. Often the ability to collect these trajectories experimentally or produce them numerically outpaces the ability to understand them theoretically. On the other hand many stochastic models have been developed and continue to be developed capable of capturing complex diffusive behavior such as heavy tails, long-range correlations, nonstationarity, and combinations of these things. We describe a computational method for connecting particle trajectory data with stochastic models of diffusion. Several tests are performed to demonstrate the efficacy of the method, and the method is applied to polymer diffusion, RNA diffusion in E. coli, and RAFOS dispersion in the Gulf of Mexico.
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