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Diffusion models are loosely modelled based on non-equilibrium thermodynamics, where \textit{diffusion} refers to particles flowing from high-concentration regions towards low-concentration regions. In statistics, the meaning is quite…

Machine Learning · Computer Science 2023-12-19 Inga Strümke , Helge Langseth

The Keller-Segel system has been widely proposed as a model for bacterial waves driven by chemotactic processes. Current experiments on {\em E. coli} have shown precise structure of traveling pulses. We present here an alternative…

The propagation of gradient flow structures from microscopic to macroscopic models is a topic of high current interest. In this paper we discuss this propagation in a model for the diffusion of particles interacting via hard-core exclusion…

Analysis of PDEs · Mathematics 2020-08-18 Maria Bruna , Martin Burger , José Antonio Carrillo

Although coarse-grained models have been widely used to explain exotic phenomena in complex fluids, such as droplet formation in living cells, these conventional approaches often fail to capture the intricate microscopic degrees of freedom…

Soft Condensed Matter · Physics 2025-06-13 Masanari Shimada , Tetsuya J. Kobayashi

The capability of cells to form surface extensions to non-locally probe the surrounding environment plays a key role in cell migration. The existing mathematical models for migration of cell populations driven by this non-local form of…

Cell Behavior · Quantitative Biology 2025-12-24 Tommaso Lorenzi , Nadia Loy , Chiara Villa

When very small particles are suspended in a fluid in motion, they tend to follow the flow. How such tracer particles are mixed, transported, and dispersed by turbulent flow has been successfully described by statistical models. Heavy…

Fluid Dynamics · Physics 2023-12-21 J. Bec , K. Gustavsson , B. Mehlig

We discuss a kinetically constrained model in which real-valued local densities fluctuate in time, as introduced recently by Bertin, Bouchaud and Lequeux. We show how the phenomenology of this model can be reproduced by an effective theory…

Statistical Mechanics · Physics 2009-09-05 Robert L. Jack , Peter Sollich , Peter Mayer

This paper presents a novel theoretical framework for understanding how diffusion models can learn disentangled representations. Within this framework, we establish identifiability conditions for general disentangled latent variable models,…

The hindered diffusion model is introduced. It is a continuum model giving the dynamics of a conserved density. Similar to the spin-facilitated models, the kinetics are hindered by a fluctuating diffusion coefficient that decreases as the…

Statistical Mechanics · Physics 2007-05-23 Gene F Mazenko

We study a system of self-propelled particles which interact with their neighbors via alignment and repulsion. The particle velocities result from self-propulsion and repulsion by close neighbors. The direction of self-propulsion is…

Mathematical Physics · Physics 2014-04-22 Pierre Degond , Giacomo Dimarco , Thi Bich Ngoc Mac , Nan Wang

The last two decades have seen a surge in kinetic and macroscopic models derived to investigate the multi-scale aspects of self-organised biological aggregations. Because the individual-level details incorporated into the kinetic models…

Populations and Evolution · Quantitative Biology 2014-07-09 José A. Carrillo , Raluca Eftimie , Franca K. O. Hoffmann

Models which allow an explicit application to structurally modulated substances are reviewed within the frame of a symmetry-based approach starting from discrete lattice theory. Focus is set on models formulated in terms of local variables…

Condensed Matter · Physics 2007-05-23 Boris Neubert , Michel Pleimling , Rolf Siems

We investigate the dynamics of kinetically constrained models of glass formers by analysing the statistics of trajectories of the dynamics, or histories, using large deviation function methods. We show that, in general, these models exhibit…

Statistical Mechanics · Physics 2009-01-21 J. P. Garrahan , R. L. Jack , V. Lecomte , E. Pitard , K. van Duijvendijk , F. van Wijland

We consider a sequence of successively more restrictive definitions of abstraction for causal models, starting with a notion introduced by Rubenstein et al. (2017) called exact transformation that applies to probabilistic causal models,…

Artificial Intelligence · Computer Science 2019-07-11 Sander Beckers , Joseph Y. Halpern

Herein an alternative model to reptation to describe concentrated polymer dynamics is developed. The model assumes that the chains act as blobs that are able to diffuse past each other in a compressed state. Allowing that the local…

Soft Condensed Matter · Physics 2022-02-25 Dave E. Dunstan

The formulation of combinatorial differential forms, proposed by Forman for analysis of topological properties of discrete complexes, is extended by defining the operators required for analysis of physical processes dependent on scalar…

Mathematical Physics · Physics 2026-05-22 Kiprian Berbatov , Pieter D. Boom , Andrew L. Hazel , Andrey P. Jivkov

Reaction-diffusion processes are the foundational model for a diverse range of complex systems, ranging from biochemical reactions to social agent-based phenomena. The underlying dynamics of these systems occur at the individual…

Statistical Mechanics · Physics 2025-10-15 Mauricio J. del Razo , Margarita Kostré

Aerodynamic models are developed to describe coherent structures and transport processes in hurricanes moving over open seas. The models consist of the lower boundary layer and upper adiabatic layer. Except friction at the air/sea…

Atmospheric and Oceanic Physics · Physics 2008-12-18 Arkady I. Leonov

Dynamical two-particle susceptibilites are important for a wide range of different experiments in condensed-matter physics and beyond. Nevertheless, most textbooks avoid describing how to derive such response functions, perhaps because they…

Quantum Physics · Physics 2021-04-13 R. D. Nesselrodt , J. K. Freericks

With recent advances in structural biology, including experimental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large biomolecular systems are required. Current…

Biological Physics · Physics 2022-06-24 Tim Hempel , Simon Olsson , Frank Noé