Super-resolved anomalous diffusion: deciphering the joint distribution of anomalous exponent and diffusion coefficient
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| Format: | Preprint |
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2024
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| _version_ | 1866915539268403200 |
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| author | Lanoiselée, Yann Pagnini, Gianni Wyłomańska, Agnieszka |
| author_facet | Lanoiselée, Yann Pagnini, Gianni Wyłomańska, Agnieszka |
| contents | The molecular motion in heterogeneous media displays anomalous diffusion by the mean-squared displacement $\langle X^2(t) \rangle = 2 D t^α$. Motivated by experiments reporting populations of the anomalous diffusion parameters $α$ and $D$, we aim to disentangle their respective contributions to the observed variability when this last is due to a true population of these parameters and when it arises due to finite-duration recordings. We introduce estimators of the anomalous diffusion parameters on the basis of the time-averaged mean squared displacement and study their statistical properties. By using a copula approach, we derive a formula for the joint density function of their estimations conditioned on their actual values. The methodology introduced is indeed universal, it is valid for any Gaussian process and can be applied to any quadratic time-averaged statistics. We also explain the experimentally reported relation $D\propto\exp(αc_1+c_2)$ for which we provide the exact expression. We finally compare our findings to numerical simulations of the fractional Brownian motion and quantify their accuracy by using the Hellinger distance. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_18133 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Super-resolved anomalous diffusion: deciphering the joint distribution of anomalous exponent and diffusion coefficient Lanoiselée, Yann Pagnini, Gianni Wyłomańska, Agnieszka Biological Physics Statistical Mechanics Probability Data Analysis, Statistics and Probability The molecular motion in heterogeneous media displays anomalous diffusion by the mean-squared displacement $\langle X^2(t) \rangle = 2 D t^α$. Motivated by experiments reporting populations of the anomalous diffusion parameters $α$ and $D$, we aim to disentangle their respective contributions to the observed variability when this last is due to a true population of these parameters and when it arises due to finite-duration recordings. We introduce estimators of the anomalous diffusion parameters on the basis of the time-averaged mean squared displacement and study their statistical properties. By using a copula approach, we derive a formula for the joint density function of their estimations conditioned on their actual values. The methodology introduced is indeed universal, it is valid for any Gaussian process and can be applied to any quadratic time-averaged statistics. We also explain the experimentally reported relation $D\propto\exp(αc_1+c_2)$ for which we provide the exact expression. We finally compare our findings to numerical simulations of the fractional Brownian motion and quantify their accuracy by using the Hellinger distance. |
| title | Super-resolved anomalous diffusion: deciphering the joint distribution of anomalous exponent and diffusion coefficient |
| topic | Biological Physics Statistical Mechanics Probability Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2410.18133 |