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Mathematical models of motility are often based on random-walk descriptions of discrete individuals that can move according to certain rules. It is usually the case that large masses concentrated in small regions of space have a great…

Physics and Society · Physics 2022-11-23 Carles Falcó

We present a novel hybrid computational method to simulate accurately dendritic solidification in the low undercooling limit where the dendrite tip radius is one or more orders of magnitude smaller than the characteristic spatial scale of…

Materials Science · Physics 2009-10-31 Mathis Plapp , Alain Karma

A novel mechanism of reaction-induced active molecular motion, not involving any kind of self-propulsion, is proposed and analyzed. Because of the momentum exchange with the surrounding solvent, conformational transitions in…

Soft Condensed Matter · Physics 2023-04-19 Hiroyuki Kitahata , Alexander S. Mikhailov

Legged locomotion demands controllers that are both robust and adaptable, while remaining compatible with task and safety considerations. However, model-free reinforcement learning (RL) methods often yield a fixed policy that can be…

Robotics · Computer Science 2025-10-07 Runhan Huang , Haldun Balim , Heng Yang , Yilun Du

In this paper we develop a random walk model on lattice for coordinate dependent diffusion at constant temperature in contact with a heat bath. We employ here a coordinate dependent waiting time of the random walker to make the diffusivity…

Statistical Mechanics · Physics 2020-08-27 Rohan Maniar , A. Bhattacharyay

We construct path integrals for stochastic hybrid reaction-diffusion (RD) processes, in which the reaction terms depend on the discrete state of a randomly switching environment. We proceed by spatially discretizing a given RD system and…

Statistical Mechanics · Physics 2021-10-15 Paul C. Bressloff

Morphogenesis is central to biology but remains largely unexplored in chemistry. Reaction-diffusion (RD) mechanisms are, however, essential to understand how shape emerges in the living world. While numerical methods confirm the incredible…

Pattern Formation and Solitons · Physics 2014-07-17 Anton S. Zadorin , Yannick Rondelez , Jean-Christophe Galas , André Estevez-Torres

The role of memory and cognition in the movement of individuals (e.g. animals) within a population, is thought to play an important role in population dispersal. In response, there has been increasing interest in incorporating spatial…

Populations and Evolution · Quantitative Biology 2024-11-15 Yifei Li , Matthew J Simpson , Chuncheng Wang

The recent development of the lattice gas automata method and its extension to the lattice Boltzmann method have provided new computational schemes for solving a variety of partial differential equations and modeling chemically reacting…

comp-gas · Physics 2008-02-03 S. Chen , S. P. Dawson , G. D. Doolen , D. R. Janecky , A. Lawniczak

Space and time scales are not independent in diffusion. In fact, numerical simulations show that different patterns are obtained when space and time steps ($\Delta x$ and $\Delta t$) are varied independently. On the other hand, anisotropy…

patt-sol · Physics 2015-06-26 Rui Dilao , Joaquim Sainhas

An analytical method based on the classical ruin problem is developed to compute the mean reaction time between two walkers undergoing a generalized random walk on a 1d lattice. At each time step, either both walkers diffuse simultaneously…

Statistical Mechanics · Physics 2009-11-10 E. Abad , Jonathan L. Bentz , G. Nicolis , John J. Kozak

Adaptive lattice Boltzmann methods (LBMs) are based on velocity discretizations that self-adjust to local macroscopic conditions such as velocity and temperature. While this feature improves the accuracy and the stability of LBMs for large…

Computational Physics · Physics 2020-11-04 C. Coreixas , J. Latt

The influence of nearest-neighbor diffusion on the decay of a metastable low-coverage phase (monolayer adsorption) in a square lattice-gas model of electrochemical metal deposition is investigated by kinetic Monte Carlo simulations. The…

Materials Science · Physics 2009-11-10 Stefan Frank , Daniel E. Roberts , Per Arne Rikvold

Methane adsorption and its effect on fluid flow in shale matrix are investigated through multi-scale simulation scheme by using molecular dynamics (MD) and lattice Boltzmann (LB) methods. Equilibrium MD simulations are conducted to study…

Chemical Physics · Physics 2015-03-26 ZhongZhen Li , Ting Min , Li Chen , Qinjun Kangd , Ya-Ling He , Wen-Quan Tao

Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These interactions span large length and time scales, making them…

Understanding the asymptotic behavior of reaction-diffusion (RD) systems is crucial for modeling processes ranging from species coexistence in ecology to biochemical interactions within cells. In this work, we analyze RD systems in which…

Dynamical Systems · Mathematics 2025-02-18 Carlos Barajas , Jean-Jacques Slotine , Domitilla Del Vecchio

The multi-grid reaction-diffusion master equation (mgRDME) provides a generalization of stochastic compartment-based reaction-diffusion modelling described by the standard reaction-diffusion master equation (RDME). By enabling different…

Quantitative Methods · Quantitative Biology 2024-05-06 Radek Erban , Stefanie Winkelmann

Background: Monte Carlo simulations of diffusion are commonly used as a model validation tool as they are especially suitable for generating the diffusion MRI signal in complicated tissue microgeometries. New method: Here we describe the…

Medical Physics · Physics 2021-04-13 Hong-Hsi Lee , Els Fieremans , Dmitry S Novikov

This paper deals with the formulation, calibration, and validation of a Lattice Discrete Particle Model (LDPM) for the simulation of the pressure-dependent inelastic response of granular rocks. LDPM is formulated in the framework of…

Materials Science · Physics 2016-05-23 Shiva Esna Ashari , Giuseppe Buscarnera , Gianluca Cusatis

This tutorial provides a comprehensive survey of methods for fine-tuning diffusion models to optimize downstream reward functions. While diffusion models are widely known to provide excellent generative modeling capability, practical…

Machine Learning · Computer Science 2024-07-19 Masatoshi Uehara , Yulai Zhao , Tommaso Biancalani , Sergey Levine
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