日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細


公開

学術論文

Quantifying non-ergodicity of anomalous diffusion with higher order moments.

MPS-Authors
/persons/resource/persons206062

Godec,  A.
Research Group of Mathematical Biophysics, MPI for Biophysical Chemistry, Max Planck Society;

External Resource
There are no locators available
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
フルテキスト (公開)

2472246.pdf
(出版社版), 2MB

付随資料 (公開)
There is no public supplementary material available
引用

Schwarzl, M., Godec, A., & Metzler, R. (2017). Quantifying non-ergodicity of anomalous diffusion with higher order moments. Scientific Reports, 7:. doi:10.1038/s41598-017-03712-x.


引用: https://hdl.handle.net/11858/00-001M-0000-002D-CAC5-0
要旨
Anomalous diffusion is being discovered in a fast growing number of systems. The exact nature of this anomalous diffusion provides important information on the physical laws governing the studied system. One of the central properties analysed for finite particle motion time series is the intrinsic variability of the apparent diffusivity, typically quantified by the ergodicity breaking parameter EB. Here we demonstrate that frequently EB is insufficient to provide a meaningful measure for the observed variability of the data. Instead, important additional information is provided by the higher order moments entering by the skewness and kurtosis. We analyse these quantities for three popular anomalous diffusion models. In particular, we find that even for the Gaussian fractional Brownian motion a significant skewness in the results of physical measurements occurs and needs to be taken into account. Interestingly, the kurtosis and skewness may also provide sensitive estimates of the anomalous diffusion exponent underlying the data. We also derive a new result for the EB parameter of fractional Brownian motion valid for the whole range of the anomalous diffusion parameter. Our results are important for the analysis of anomalous diffusion but also provide new insights into the theory of anomalous stochastic processes.