TY  - JOUR
A1  - Thapa, Samudrajit
A1  - Wyłomańska, Agnieszka
A1  - Sikora, Grzegorz
A1  - Wagner, Caroline E.
A1  - Krapf, Diego
A1  - Kantz, Holger
A1  - Chechkin, Aleksei V.
A1  - Metzler, Ralf
T1  - Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories
T2  - New Journal of Physics
N2  - Extensive time-series encoding the position of particles such as viruses, vesicles, or individualproteins are routinely garnered insingle-particle tracking experiments or supercomputing studies.They contain vital clues on how viruses spread or drugs may be delivered in biological cells.Similar time-series are being recorded of stock values in financial markets and of climate data.Such time-series are most typically evaluated in terms of time-averaged mean-squareddisplacements (TAMSDs), which remain random variables for finite measurement times. Theirstatistical properties are different for differentphysical stochastic processes, thus allowing us toextract valuable information on the stochastic process itself. To exploit the full potential of thestatistical information encoded in measured time-series we here propose an easy-to-implementand computationally inexpensive new methodology, based on deviations of the TAMSD from itsensemble average counterpart. Specifically, we use the upper bound of these deviations forBrownian motion (BM) to check the applicability of this approach to simulated and real data sets.By comparing the probability of deviations fordifferent data sets, we demonstrate how thetheoretical bound for BM reveals additional information about observed stochastic processes. Weapply the large-deviation method to data sets of tracer beads tracked in aqueous solution, tracerbeads measured in mucin hydrogels, and of geographic surface temperature anomalies. Ouranalysis shows how the large-deviation properties can be efficiently used as a simple yet effectiveroutine test to reject the BM hypothesis and unveil relevant information on statistical propertiessuch as ergodicity breaking and short-time correlations.
KW  - diffusion
KW  - anomalous diffusion
KW  - large-deviation statistic
KW  - time-averaged mean squared displacement
KW  - Chebyshev inequality
Y1  - 2021
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/49348
SN  - 1367-2630
VL  - 23
PB  - Dt. Physikalische Ges. ; IOP
CY  - Bad Honnef ; London
ER  -