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Originating from the diffusion phenomenon in physics that describes particle movement, the diffusion generative models inherit the characteristics of stochastic random walk in the data space along the denoising trajectory. However, the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Ruoyu Wang , Yongqi Yang , Zhihao Qian , Ye Zhu , Yu Wu

There has been considerable recent study in "sub-diffusion" models that replace the standard parabolic equation model by a one with a fractional derivative in the time variable. There are many ways to look at this newer approach and one…

Analysis of PDEs · Mathematics 2019-04-08 William Rundell , Zhidong Zhang

We introduce a model of self-propelled particles carrying out a Brownian motion with a diffusion coefficient which depends on the local density of particles within a certain finite radius. Numerical simulations show that in a range of…

Statistical Mechanics · Physics 2009-11-11 Cristobal Lopez

We study diffusion processes in anomalous spacetimes regarded as models of quantum geometry. Several types of diffusion equation and their solutions are presented and the associated stochastic processes are identified. These results are…

High Energy Physics - Theory · Physics 2015-03-20 Gianluca Calcagni

Traditionally, systems governed by linear Partial Differential Equations (PDEs) are spatially discretized to exploit their algebraic structure and reduce the computational effort for controlling them. Due to beneficial insights of the PDEs,…

Systems and Control · Computer Science 2016-04-05 Saber Jafarizadeh

We consider the Anderson tight-binding model on $\mathbb{Z}^d$, $d\geq 2$, with Gaussian noise and at low disorder $\lambda>0$. We derive a diffusive scaling limit for the entries of the resolvent $R(z)$ at imaginary part…

Mathematical Physics · Physics 2025-11-10 Adam Black , Reuben Drogin , Felipe Hernández

A stochastic representation of the dynamics of open quantum systems, suitable for non-perturbative system-reservoir interaction, non-Markovian effects and arbitrarily driven systems is presented. It includes the case of driving on…

Statistical Mechanics · Physics 2016-10-05 Jürgen T. Stockburger

In this paper we revisit the issue of the propagation of warps in thin and viscous accretion discs. In this regime warps are know to propagate diffusively, with a diffusion coefficient approximately inversely proportional to the disc…

High Energy Astrophysical Phenomena · Physics 2015-05-18 G. Lodato , D. Price

A new approach to Brownian motion of atomic clusters on solid surfaces is developed. The main topic discussed is the dependence of the diffusion coefficient on the fit between the surface static potential and the internal cluster…

Statistical Mechanics · Physics 2011-04-12 Roumen Tsekov

Score-based diffusion models have demonstrated remarkable empirical success in learning high-dimensional distributions, particularly those exhibiting low-dimensional and multi-modal structures. However, theoretical understanding of their…

Machine Learning · Statistics 2026-05-29 Jingda Wu , Changxiao Cai

Diffusion tensor imaging (DTI) is a prevalent neuroimaging tool in analyzing the anatomical structure. The distinguishing feature of DTI is that the voxel-wise variable is a 3x3 positive definite matrix other than a scalar, describing the…

Methodology · Statistics 2021-03-30 Zhou Lan

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the…

Statistical Mechanics · Physics 2021-03-25 Yi Liao , Xiao-Bo Gong

The concept of diffusion in collisionless space plasmas like those near the magnetopause and in the geomagnetic tail is reexamined from a fundamental statistical point of view making use of the division of particle orbits into waiting…

Space Physics · Physics 2014-06-25 R. A. Treumann , W. Baumjohann

This paper uses dynamical invariants to describe the evolution of collisionless systems subject to time-dependent gravitational forces without resorting to maximum-entropy probabilities. We show that collisionless relaxation can be viewed…

Astrophysics of Galaxies · Physics 2015-06-03 Jorge Peñarrubia

This paper presents a homogenisation-based constitutive model to describe the effective tran- sient diffusion behaviour in heterogeneous media in which there is a large contrast between the phase diffusivities. In this case mobile species…

Computational Physics · Physics 2019-03-19 Laurence Brassart , Laurent Stainier

The strongly interacting matter created in relativistic heavy-ion collisions possesses several conserved quantum numbers, such as baryon number, strangeness, and electric charge. The diffusion process of these charges can be characterized…

High Energy Physics - Phenomenology · Physics 2024-11-06 Sourav Dey , Amaresh Jaiswal , Hiranmaya Mishra

In slowly evolving spherical potentials, $\Phi(r,t)$, radial actions are typically assumed to remain constant. Here, we construct dynamical invariants that allow us to derive the evolution of radial actions in spherical central potentials…

Astrophysics of Galaxies · Physics 2021-09-14 Jan D. Burger , Jorge Peñarrubia , Jesús Zavala

We apply the macroscopic fluctuation theory (MFT) to study the large-scale dynamical properties of Brownian particles with arbitrary pairwise interaction. By combining it with standard results of equilibrium statistical mechanics for the…

Statistical Mechanics · Physics 2026-05-19 Aurélien Grabsch , Davide Venturelli , Olivier Bénichou

Here, an approach in terms of shot noise is proposed to study and characterize surface diffusion and low vibrational motion when having interacting adsorbates on surfaces. In what we call statistical limit, that is, at long times and high…

Statistical Mechanics · Physics 2007-06-13 R. Martinez-Casado , J. L. Vega , A. S. Sanz , S. Miret-Artes

Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples. They implement a diffusion process whose endpoint is a…

Machine Learning · Computer Science 2025-09-03 Andrea Montanari