Objective comparison of methods to decode anomalous diffusion

G Muñoz-Gil, G Volpe, MA Garcia-March… - Nature …, 2021 - nature.com
Deviations from Brownian motion leading to anomalous diffusion are found in transport
dynamics from quantum physics to life sciences. The characterization of anomalous diffusion …

Time-averaging and nonergodicity of reset geometric Brownian motion with drift

D Vinod, AG Cherstvy, R Metzler, IM Sokolov - Physical Review E, 2022 - APS
How do near-bankruptcy events in the past affect the dynamics of stock-market prices in the
future? Specifically, what are the long-time properties of a time-local exponential growth of …

Classification of anomalous diffusion in animal movement data using power spectral analysis

O Vilk, E Aghion, R Nathan, S Toledo… - Journal of Physics A …, 2022 - iopscience.iop.org
The field of movement ecology has seen a rapid increase in high-resolution data in recent
years, leading to the development of numerous statistical and numerical methods to analyse …

Characterization of anomalous diffusion classical statistics powered by deep learning (CONDOR)

A Gentili, G Volpe - Journal of Physics A: Mathematical and …, 2021 - iopscience.iop.org
Diffusion processes are important in several physical, chemical, biological and human
phenomena. Examples include molecular encounters in reactions, cellular signalling, the …

Fractional Brownian motion in superharmonic potentials and non-Boltzmann stationary distributions

T Guggenberger, A Chechkin… - Journal of Physics A …, 2021 - iopscience.iop.org
We study the stochastic motion of particles driven by long-range correlated fractional
Gaussian noise (FGN) in a superharmonic external potential of the form U (x)∝ x 2n …

Stochastic processes in a confining harmonic potential in the presence of static and dynamic measurement noise

PG Meyer, R Metzler - New Journal of Physics, 2023 - iopscience.iop.org
We consider the overdamped dynamics of different stochastic processes, including
Brownian motion and autoregressive processes, continuous time random walks, fractional …

Efficient recurrent neural network methods for anomalously diffusing single particle short and noisy trajectories

Ò Garibo-i-Orts, A Baeza-Bosca… - Journal of Physics A …, 2021 - iopscience.iop.org
Anomalous diffusion occurs at very different scales in nature, from atomic systems to motions
in cell organelles, biological tissues or ecology, and also in artificial materials, such as …

Extreme learning machine for the characterization of anomalous diffusion from single trajectories (AnDi-ELM)

C Manzo - Journal of Physics A: Mathematical and Theoretical, 2021 - iopscience.iop.org
The study of the dynamics of natural and artificial systems has provided several examples of
deviations from Brownian behavior, generally defined as anomalous diffusion. The …

Unsupervised learning of anomalous diffusion data: an anomaly detection approach

G Muñoz-Gil, GG i Corominas… - Journal of Physics A …, 2021 - iopscience.iop.org
The characterization of diffusion processes is a keystone in our understanding of a variety of
physical phenomena. Many of these deviate from Brownian motion, giving rise to anomalous …

Preface: characterisation of physical processes from anomalous diffusion data

C Manzo, G Munoz-Gil, G Volpe… - arXiv preprint arXiv …, 2023 - arxiv.org
Preface to the special issue" Characterisation of Physical Processes from Anomalous
Diffusion Data" associated with the Anomalous Diffusion Challenge (https://andi-challenge …