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The concept of random walk, in which particles or waves undergo multiple collisions with the microscopic constituents of a surrounding medium, is central to understanding diffusive transport across many research areas. However, this…

Consider a chaotic dynamical system generating Brownian motion-like diffusion. Consider a second, non-chaotic system in which all particles localize. Let a particle experience a random combination of both systems by sampling between them in…

Chaotic Dynamics · Physics 2019-05-01 Y. Sato , R. Klages

Non-Hermitian systems exhibit a distinctive type of wave propagation, due to the intricate interplay of non-Hermiticity and disorder. Here, we investigate the spreading dynamics in the archetypal non-Hermitian Aubry-Andr\'e model with…

Disordered Systems and Neural Networks · Physics 2024-12-03 Ze-Yu Xing , Shu Chen , Haiping Hu

We introduce a new universality class of one-dimensional iteration model giving rise to self-similar motion, in which the Feigenbaum constants are generalized as self-similar rates and can be predetermined. The curves of the mean-square…

Statistical Mechanics · Physics 2010-05-06 Zhifu Huang , Guozhen Su , Qiuping A Wang , Jincan Chen

In this paper Gaussian models of retarded and accelerated anomalous diffusion are considered. Stochastic differential equations of fractional order driven by single or multiple fractional Gaussian noise terms are introduced to describe…

Statistical Mechanics · Physics 2014-05-08 Chai Hok Eab , S. C. Lim

Recent progresses in single particle tracking have shown evidences of non-Gaussian distribution of displacements in living cells, both near the cellular membrane and inside the cytoskeleton. A similar behavior has also been observed in…

Biological Physics · Physics 2019-05-30 Yann Lanoiselée , Denis S. Grebenkov

Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion…

We present a Master Equation formulation based on a Markovian random walk model that exhibits sub-diffusion, classical diffusion and super-diffusion as a function of a single parameter. The non-classical diffusive behavior is generated by…

Statistical Mechanics · Physics 2013-09-19 James F. Lutsko , Jean Pierre Boon

Anomalous diffusion phenomenon is an intriguing process that tracer diffusion presents in numerous complex systems. Current experimental and theoretical investigations have reported the emergence of random diffusivity scenarios accompanied…

Statistical Mechanics · Physics 2022-10-19 M. A. F. dos Santos , L. Menon Junior , D. Cius

Fickian yet non-Gaussian diffusion is observed in several biological and soft matter systems, yet the underlying mechanisms behind the emergence of non-Gaussianity while retaining a linear mean square displacement remain speculative. Here,…

Soft Condensed Matter · Physics 2020-05-06 Indrani Chakraborty , Yael Roichman

Wang et al. [PNAS 106 (2009) 15160] have found that in several systems the linear time dependence of the mean-square displacement (MSD) of diffusing colloidal particles, typical of normal diffusion, is accompanied by a non-Gaussian…

Statistical Mechanics · Physics 2015-06-19 Mykyta V. Chubynsky , Gary W. Slater

The problem of eliminating fast-relaxing variables to obtain an effective drift-diffusion process in position is solved in a uniform and straightforward way for models with velocity a function jointly of position and fast variables. A more…

Statistical Mechanics · Physics 2019-11-13 Paul E. Lammert

We show through intensive simulations that the paradigmatic features of anomalous diffusion are indeed the features of a (continuous-time) random walk driven by two different Markovian hopping-trap mechanisms. If $p \in (0,1/2)$ and $1-p$…

Statistical Mechanics · Physics 2022-05-25 Silvia Vitali , Paolo Paradisi , Gianni Pagnini

We show analytically that there is anomalous diffusion when the diffusion constant depends on the concentration as a power law with a positive exponent or a negative exponent with absolute value less than one and the initial condition is a…

Statistical Mechanics · Physics 2019-12-13 Alex Hansen , Eirik G. Flekkøy

We demonstrate the controllable generation of distinct types of dispersive shock-waves emerging in a quantum droplet bearing environment with the aid of step-like initial conditions. Dispersive regularization of the ensuing hydrodynamic…

Pattern Formation and Solitons · Physics 2024-08-20 Sathyanarayanan Chandramouli , Simeon I. Mistakidis , Garyfallia C. Katsimiga , Panayotis G. Kevrekidis

Superslow diffusion, i.e., the long-time diffusion of particles whose mean-square displacement (variance) grows slower than any power of time, is studied in the framework of the decoupled continuous-time random walk model. We show that this…

Statistical Mechanics · Physics 2010-11-24 S. I. Denisov , H. Kantz

We study far from equilibrium transport of a periodically driven inertial Brownian particle moving in a periodic potential. As detected recently for a SQUID ratchet dynamics (Spiechowicz J. & Luczka J. Phys. Rev. E 91, 062104 (2015)), the…

Statistical Mechanics · Physics 2016-12-07 Jakub Spiechowicz , Peter Hänggi , Jerzy Łuczka

By analyzing two Kinetically Constrained Models of supercooled liquids we show that the anomalous transport of a driven tracer observed in supercooled liquids is another facet of the phenomenon of dynamical heterogeneity. We focus on the…

Statistical Mechanics · Physics 2016-07-06 Giacomo Gradenigo , Eric Bertin , Giulio Biroli

.Stochastic models based on random diffusivities, such as the diffusing-diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically focus on the moments…

Statistical Mechanics · Physics 2020-08-26 V. Sposini , D. S. Grebenkov , R. Metzler , G. Oshanin , F. Seno

Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNN) can efficiently…

Statistical Mechanics · Physics 2019-07-24 Stefano Bo , Falko Schmidt , Ralf Eichhorn , Giovanni Volpe