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A particle driven by deterministic chaos and moving in a spatially extended environment can exhibit normal diffusion, with its mean square displacement growing proportional to the time. Here we consider the dependence of the diffusion…

Mathematical Physics · Physics 2017-06-29 Georgie Knight , Orestis Georgiou , Carl P. Dettmann , Rainer Klages

Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a…

Machine Learning · Statistics 2020-03-10 Lenore Cowen , Kapil Devkota , Xiaozhe Hu , James M. Murphy , Kaiyi Wu

Static or frozen disorder, characterised by spatial heterogeneities, influences diverse complex systems, encompassing many-body systems, equilibrium and nonequilibrium states of matter, intricate network topologies, biological systems, and…

Disordered Systems and Neural Networks · Physics 2025-03-24 M. Ahumada , L. Trujillo , J. F. Marín

The role of disorder on physical systems has been widely studied in the macroscopic and microscopic world. While static disorder is well understood in many cases, the impact of time-dependent disorder on quantum gases is still poorly…

Quantum Gases · Physics 2024-01-26 Silvia Hiebel , Benjamin Nagler , Sian Barbosa , Jennifer Koch , Artur Widera

We study the effect of a random Flory-Huggins parameter in a symmetric diblock copolymer melt which is expected to occur in a copolymer where one block is near its structural glass transition. In the clean limit the microphase segregation…

Soft Condensed Matter · Physics 2009-11-11 Harry Westfahl , Joerg Schmalian

We consider a sequence of idealized measurements of time-separation $\Delta t$ onto a discrete one-dimensional disordered system. A connection with Markov chains is found. For a rapid sequence of measurements, a diffusive regime occurs and…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. C. Flores

Motivated by an application to empirical Bayes learning in high-dimensional regression, we study a class of Langevin diffusions in a system with random disorder, where the drift coefficient is driven by a parameter that continuously adapts…

Statistics Theory · Mathematics 2025-11-04 Zhou Fan , Justin Ko , Bruno Loureiro , Yue M. Lu , Yandi Shen

We consider a system of diffusion processes interacting through their empirical distribution. Assuming that the empirical average of a given observable can be observed at any time, we derive regularity and quantitative stability results for…

Optimization and Control · Mathematics 2025-01-08 Louis-Pierre Chaintron , Giovanni Conforti

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce.…

Machine Learning · Statistics 2025-03-04 Antonio Sclocchi , Alessandro Favero , Noam Itzhak Levi , Matthieu Wyart

We study the statistics of quantum transmission through a one-dimensional disordered system modelled by a sequence of independent scattering units. Each unit is characterized by its length and by its action, which is proportional to the…

Statistical Mechanics · Physics 2007-11-06 D. Boose , J. M. Luck

This paper investigates the robustness of stochastic optimal control for controlled regime switching diffusions. We consider systems driven by both continuous fluctuations and discrete regime changes, allowing for model misspecification in…

Optimization and Control · Mathematics 2025-11-24 Somnath Pradhan , Dinesh Rathia

Motivated by a number of recent experimental and computational studies of the dynamics of fluids plunged in quenched-disordered external fields, we report on a theoretical investigation of this topic within the framework of the…

Soft Condensed Matter · Physics 2018-10-05 Thomas Konincks , Vincent Krakoviack

We consider Langevin equation with dichotomously fluctuating diffusivity, where the diffusion coefficient changes dichotomously in time, in order to study fluctuations of time-averaged observables in temporary heterogeneous diffusion…

Statistical Mechanics · Physics 2016-06-15 Takuma Akimoto , Eiji Yamamoto

We investigate the ensemble and time averaged mean squared displacements for particle diffusion in a simple model for disordered media by assuming that the local diffusivity is both fluctuating in time and has a deterministic average growth…

Statistical Mechanics · Physics 2016-10-05 A. G. Cherstvy , R. Metzler

Strong anomalous diffusion is characterized by asymptotic power-law growth of the moments of displacement, with exponents that do not depend linearly on the order of the moment. The exponents concerning small-order moments are dominated by…

Statistical Mechanics · Physics 2021-01-27 Jürgen Vollmer , Lamberto Rondoni , Muhammad Tayyab , Claudio Giberti , Carlos Mejía-Monasterio

Diffusion models have emerged as powerful generative priors for solving inverse imaging problems. However, their practical deployment is hindered by the substantial computational cost of slow, multi-step sampling. Although Consistency…

Image and Video Processing · Electrical Eng. & Systems 2025-12-04 Amirreza Tanevardi , Pooria Abbas Rad Moghadam , Seyed Mohammad Eshtehardian , Sajjad Amini , Babak Khalaj

We study the dimensional dependence of the interplay between correlation and disorder in two dimension at half filling using 2D $t-t'$ disordered Hubbard model with deterministic disorder both at zero and finite temperatures. Inclusion of…

Strongly Correlated Electrons · Physics 2015-05-13 Tribikram Gupta , Sanjay Gupta

A layered system of charges with logarithmic interaction parallel to the layers and random dipoles in each layer is studied via a variational method and an energy rationale. These methods reproduce the known phase diagram for a single layer…

Disordered Systems and Neural Networks · Physics 2009-11-10 Baruch Horovitz , Pierre Le Doussal

The premise of independence among subjects in the same cluster/group often fails in practice, and models that rely on such untenable assumption can produce misleading results. To overcome this severe deficiency, we introduce a new…

Methodology · Statistics 2022-02-22 Jussiane Nader Gonçalves , Wagner Barreto-Souza , Hernando Ombao

We study the effects of spatially inhomogeneous diffusion on the non-equilibrium phase transition in the contact process. The directed-percolation critical point in the contact process is known to be stable against the addition of a…

Statistical Mechanics · Physics 2026-03-06 Valentin Anfray , Manisha Dhayal , Hong-Yan Shih , Thomas Vojta
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