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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

Dynamics of two particles with short range repulsive or attractive interaction is studied numerically in the Harper model. It is shown that interaction leads to appearance of localized states and pure-point spectrum component in the case…

Condensed Matter · Physics 2009-10-28 D. L. Shepelyansky

We propose a stochastic model for intracellular transport processes associated with the activity of molecular motors. This out-of-equilibrium model, based on a generalized Langevin equation, considers a particle immersed in a viscoelastic…

Biological Physics · Physics 2009-04-15 L. Bruno , M. A. Despósito

Temporal-network models have provided key insights into how time-varying connectivity shapes dynamical processes such as spreading. Among them, the activity-driven model is a widely used, analytically tractable benchmark. Yet many temporal…

Physics and Society · Physics 2025-11-20 Zsófia Simon , Jari Saramäki

In this paper we deal with pedestrian modeling, aiming at simulating crowd behavior in normal and emergency scenarios, including highly congested mass events. We are specifically concerned with a new agent-based, continuous-in-space,…

Adaptation and Self-Organizing Systems · Physics 2023-11-23 E. Cristiani , M. Menci , A. Malagnino , G. G. Amaro

In this paper we present a network model to study the impact of spatial distribution of constituents, coupling between them and diffusive processes in the context of biological situations. The model is in terms of network of mobile elements…

Molecular Networks · Quantitative Biology 2007-05-23 Kanchan Thadani , Ashutosh

The migration of active particles in slowly moving, crowded, and heterogeneous media is fundamental to various biological processes and technological applications, such as cargo transport. In this study, we numerically investigate the…

Soft Condensed Matter · Physics 2024-12-04 Meng-Yuan Li , Ning Zheng , Yan-Wei Li

Current artificial intelligence systems show near-human-level capabilities when deployed in isolation. Systems of a few collaborating intelligent agents are being engineered to perform tasks collectively. This raises the question of whether…

Soft Condensed Matter · Physics 2025-10-08 Onurcan Bektas , Adolfo Alsina , Steffen Rulands

We study analytically the dynamics and the micro-structural changes of a host medium caused by a driven tracer particle moving in a confined, quiescent molecular crowding environment. Imitating typical settings of active micro-rheology…

Statistical Mechanics · Physics 2016-03-17 O. Bénichou , P. Illien , G. Oshanin , A. Sarracino , R. Voituriez

Consider a particle diffusing in a confined volume which is divided into two equal regions. In one region the diffusion coefficient is twice the value of the diffusion coefficient in the other region. Will the particle spend equal…

Dynamical Systems · Mathematics 2015-06-04 P. F. Tupper , Xin Yang

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

Agent-Based Models (ABMs) are powerful tools for studying emergent properties in complex systems. In ABMs, agent behaviors are governed by local interactions and stochastic rules. However, these rules are, in general, non-differentiable,…

Artificial Intelligence · Computer Science 2025-11-27 Francesco Cozzi , Marco Pangallo , Alan Perotti , André Panisson , Corrado Monti

In cell membranes, proteins and lipids diffuse in a highly crowded and heterogeneous landscape, where aggregates and dense domains of proteins or lipids obstruct the path of diffusing molecules. In general, hindered motion gives rise to…

Soft Condensed Matter · Physics 2010-06-16 Margaret R. Horton , Felix Höfling , Joachim O. Rädler , Thomas Franosch

Real physical systems are only understood, experimentally or theoretically, to a finite resolution so in their analysis there is generally an ignorance of possible short-range phenomena. It is also well-known that the boundary conditions of…

High Energy Physics - Theory · Physics 2016-06-17 David M. Jacobs

Diffusion of colloidal particles in a complex environment such as polymer networks or biological cells is a topic of high complexity with significant biological and medical relevance. In such situations, the interaction between the…

Statistical Mechanics · Physics 2015-11-10 Andreas M. Menzel

Swarm robotics has potential for a wide variety of applications, but real-world deployments remain rare due to the difficulty of predicting emergent behaviors arising from simple local interactions. Traditional engineering approaches design…

Robotics · Computer Science 2025-10-28 Ricardo Vega , Connor Mattson , Kevin Zhu , Daniel S. Brown , Cameron Nowzari

In equilibrium, the collective behaviour of particles interacting via steep, short-ranged potentials is well captured by the virial expansion of the free energy at low density. Here, we extend this approach beyond equilibrium to the case of…

Soft Condensed Matter · Physics 2023-06-21 Yuting Irene Li , Rosalba Garcia-Millan , Michael E. Cates , Étienne Fodor

Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality…

Physics and Society · Physics 2016-07-13 Michele Starnini , Andrea Baronchelli , Romualdo Pastor-Satorras

We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention within a framework designed to enforce certain scientifically-motivated…

Machine Learning · Computer Science 2023-06-22 Kai Lagemann , Christian Lagemann , Sach Mukherjee

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning…

Machine Learning · Computer Science 2024-10-31 David Lüdke , Enric Rabasseda Raventós , Marcel Kollovieh , Stephan Günnemann
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