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The mean-squared displacement (MSD) is an averaged quantity widely used to assess anomalous diffusion. In many cases, such as molecular motors with finite processivity, dynamics of the system of interest produce trajectories of varying…

Statistical Mechanics · Physics 2020-10-07 Chapin S. Korosec , David A. Sivak , Nancy R. Forde

We investigate the occurrence of anomalous diffusive transport associated with acoustic wave fields propagating through highly-scattering periodic media. Previous studies had correlated the occurrence of anomalous diffusion to either the…

Disordered Systems and Neural Networks · Physics 2019-03-27 Salvatore Buonocore , Mihir Sen , Fabio Semperlotti

We study the Brownian motion of a classical particle in one-dimensional inhomogeneous environments where the transition probabilities follow quasiperiodic or aperiodic distributions. Exploiting an exact correspondence with the…

Statistical Mechanics · Physics 2009-10-31 F. Igloi , L. Turban , H. Rieger

Anomalous diffusion is the fundamental ansatz of phenomenological theories of passive scalar turbulence, and has been confirmed numerically and experimentally to an extraordinary extent. The purpose of this survey is to discuss our recent…

Analysis of PDEs · Mathematics 2025-09-05 Scott Armstrong , Vlad Vicol

Standard and anomalous transport in incompressible flow is investigated using multiscale techniques. Eddy-diffusivities emerge from the multiscale analysis through the solution of an auxiliary equation. From the latter it is derived an…

Condensed Matter · Physics 2009-10-22 L. Biferale , A. Crisanti , M. Vergassola , A. Vulpiani

Diffusion models have shown superior performance on unsupervised anomaly detection tasks. Since trained with normal data only, diffusion models tend to reconstruct normal counterparts of test images with certain noises added. However, these…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Hang Yao , Ming Liu , Haolin Wang , Zhicun Yin , Zifei Yan , Xiaopeng Hong , Wangmeng Zuo

Human motion generation is a challenging task due to its high dimensionality and the difficulty of generating fine-grained motions. Diffusion methods have been proposed due to their high sample quality and expressiveness. Early approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mirgahney Mohamed , Harry Jake Cunningham , Marc P. Deisenroth , Lourdes Agapito

Normal and anomalous diffusion are ubiquitous in many complex systems [1] . Here, we define a time and space generalized diffusion equation (GDE), which uses fractional-time derivatives and transformed d-path Laplacian operators on…

Physics and Society · Physics 2022-02-02 Fernando Diaz-Diaz , Ernesto Estrada

A number of results for reactions involving subdiffusive species all with the same anomalous exponent gamma have recently appeared in the literature and can often be understood in terms of a subordination principle whereby time t in…

Statistical Mechanics · Physics 2009-11-11 S. B. Yuste , Katja Lindenberg

We propose a practical empirical fitting function to characterize the non-Gaussian displacement distribution functions (DispD) often observed for heterogeneous diffusion problems. We first test this fitting function with the problem of a…

Soft Condensed Matter · Physics 2022-07-20 Le Qiao , Nicholas Ilow , Maxime Ignacio , Gary W. Slater

Far from equilibrium, neural systems self-organize across multiple scales. Exploiting multiscale self-organization in neuroscience and artificial intelligence requires a computational framework for modeling the effective non-equilibrium…

Neurons and Cognition · Quantitative Biology 2025-10-09 Nathan X. Kodama

We considered diffusion-driven processes on small-world networks with distance-dependent random links. The study of diffusion on such networks is motivated by transport on randomly folded polymer chains, synchronization problems in…

Statistical Mechanics · Physics 2007-09-05 Balazs Kozma , Matthew B. Hastings , G. Korniss

We study reinforcement learning for controlled diffusion processes with unbounded continuous state spaces, bounded continuous actions, and polynomially growing rewards: settings that arise naturally in finance, economics, and operations…

Machine Learning · Computer Science 2025-12-18 Hanqing Jin , Renyuan Xu , Yanzhao Yang

The silo discharge process is studied by molecular dynamics simulations. The development of the velocity profile and the probability density function for the displacements in the horizontal and vertical axis are obtained. The PDFs obtained…

Statistical Mechanics · Physics 2009-11-11 R. Arevalo , A. Garcimartin , D. Maza

In network embedding, random walks play a fundamental role in preserving network structures. However, random walk based embedding methods have two limitations. First, random walk methods are fragile when the sampling frequency or the number…

Machine Learning · Computer Science 2018-05-14 Yong Shi , Minglong Lei , Peng Zhang , Lingfeng Niu

We demonstrate that 2D Fermi liquids can support peculiar excitations that are not subject to Landau's $T^2$ dissipation. The long-lived excitations relax through correlated angular dynamics involving "lock-step" angular displacements along…

Mesoscale and Nanoscale Physics · Physics 2019-10-11 Patrick Ledwith , Haoyu Guo , Leonid Levitov

The most common way of estimating the anomalous diffusion exponent from single-particle trajectories consists in a linear fitting of the dependence of the time averaged mean square displacement on the lag time at the log-log scale. However,…

Data Analysis, Statistics and Probability · Physics 2019-01-02 Yann Lanoiselée , Denis S. Grebenkov , Grzegorz Sikora , Aleksandra Grzesiek , Agnieszka Wyłomańska

A generalization of the Drude model is studied. On the one hand, the free motion of the particles is allowed to be sub- or superdiffusive; on the other hand, the distribution of the time delay between collisions is allowed to have a long…

Condensed Matter · Physics 2009-10-30 Hermann Schulz-Baldes

This is an easy-to-read introduction to foundations of deterministic chaos, deterministic diffusion and anomalous diffusion. The first part introduces to deterministic chaos in one-dimensional maps in form of Ljapunov exponents and…

Chaotic Dynamics · Physics 2010-01-27 R. Klages

When particles/molecules diffuse in systems that contain obstacles, the steady-state regime (during which the mean-square displacement scales linearly with time, $\left< r^2 \right> \sim t$) is preceded by a transient regime. It is common…

Biological Physics · Physics 2021-08-12 Nicholas Ilow , Gary W. Slater