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When we focus on finite dynamical systems from both the computability/complexity and the modelling standpoints, automata networks seem to be a particularly appropriate mathematical model on which theory shall be developed. In this paper,…

Discrete Mathematics · Computer Science 2023-04-20 Kévin Perrot , Sylvain Sené , Léah Tapin

Constructing robots to accomplish long-horizon tasks is a long-standing challenge within artificial intelligence. Approaches using generative methods, particularly Diffusion Models, have gained attention due to their ability to model…

Robotics · Computer Science 2026-04-30 Sigmund Hennum Høeg , Aksel Vaaler , Chaoqi Liu , Olav Egeland , Yilun Du

The Bak-Tang-Wiesenfeld (BTW) sandpile model is a cellular automaton which has been intensively studied during the last years as a paradigm for self-organized criticality. In this paper, we reconsider a deterministic version of the BTW…

Statistical Mechanics · Physics 2009-10-31 S. Lubeck , N. Rajewsky , D. E. Wolf

Graph bootstrap percolation is a deterministic cellular automaton which was introduced by Bollob\'as in 1968, and is defined as follows. Given a graph $H$, and a set $G \subset E(K_n)$ of initially `infected' edges, we infect, at each time…

Combinatorics · Mathematics 2012-11-27 József Balogh , Béla Bollobás , Robert Morris

A ``sandpile'' cellular automaton achieves complex temporal correlations, like a $1/f$ spectrum, if the position where it is perturbed diffuses slowly rather than changing completely at random, showing that the spatial correlations of the…

Statistical Mechanics · Physics 2009-11-11 Marco Baiesi , Christian Maes

Random diffusions are a popular tool in Monte-Carlo estimations, with well established algorithms such as Walk-on-Spheres (WoS) going back several decades. In this work, we introduce diffusion estimators for the problems of angular…

Probability · Mathematics 2024-10-15 Hugo Jaquard , Pierre-Olivier Amblard , Simon Barthelmé , Nicolas Tremblay

Diffusion models provide expressive priors for forecasting trajectories of dynamical systems, but are typically unreliable in the sparse data regime. Physics-informed machine learning (PIML) improves reliability in such settings; however,…

Machine Learning · Computer Science 2026-01-30 Kaiyuan Tan , Kendra Givens , Peilun Li , Thomas Beckers

Motivated by targeted drug delivery, we investigate the gathering of particles in the full tilt model of externally controlled motion planning: A set of particles is located at the tiles of a polyomino with all particles reacting uniformly…

Computational Geometry · Computer Science 2026-03-04 Sándor P. Fekete , Jonas Friemel , Peter Kramer , Jan-Marc Reinhardt , Christian Rieck , Christian Scheffer

In this paper, we explore the two-dimensional behavior of cellular automata with shuffle updates. As a test case, we consider the evacuation of a square room by pedestrians modeled by a cellular automaton model with a static floor field.…

Cellular Automata and Lattice Gases · Physics 2015-10-23 Chikashi Arita , Julien Cividini , Cécile Appert-Rolland

We propose a probabilistic cellular automata model for the spread of innovations, rumors, news, etc. in a social system. The local rule used in the model is outertotalistic, and the range of interaction can vary. When the range R of the…

adap-org · Physics 2008-02-03 Henryk Fuks , Nino Boccara

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense…

Soft Condensed Matter · Physics 2017-09-06 Shuanhu Qi , Friederike Schmid

Image completion is a challenging task, particularly when ensuring that generated content seamlessly integrates with existing parts of an image. While recent diffusion models have shown promise, they often struggle with maintaining…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Pourya Shamsolmoali , Masoumeh Zareapoor , Huiyu Zhou , Michael Felsberg , Dacheng Tao , Xuelong Li

Optimal control problems are inherently hard to solve as the optimization must be performed simultaneously with updating the underlying system. Starting from an initial guess, Howard's policy improvement algorithm separates the step of…

Optimization and Control · Mathematics 2020-05-25 B. Kerimkulov , D. Šiška , Ł. Szpruch

The use of adaptive spatial resolution to simulate flows of practical interest using Smoothed Particle Hydrodynamics (SPH) is of considerable importance. Recently, Muta and Ramachandran [1] have proposed an efficient adaptive SPH method…

Fluid Dynamics · Physics 2022-05-17 Asmelash Haftu , Abhinav Muta , Prabhu Ramachandran

We describe a novel approach to statistical learning from particles tracked while moving in a random environment. The problem consists in inferring properties of the environment from recorded snapshots. We consider here the case of a fluid…

Information Theory · Computer Science 2008-06-09 Michael Chertkov , Lukas Kroc , Massimo Vergassola

Fungal simulation and control are considered crucial techniques in Bio-Art creation. However, coding algorithms for reliable fungal simulations have posed significant challenges for artists. This study equates fungal morphology simulation…

Graphics · Computer Science 2024-09-10 Kexin Wang , Ivy He , Jinke Li , Ali Asadipour , Yitong Sun

In this paper, a diffusion-aggregation equation with delta potential is introduced. Based on the global existence and uniform estimates of solutions to the diffusion-aggregation equation, we also provide the rigorous derivation from a…

Analysis of PDEs · Mathematics 2019-12-13 Li Chen , Simone Göttlich , Stephan Knapp

We provide a numerical algorithm for the model characterizing anomalous diffusion in expanding media, which is derived in [F. Le Vot, E. Abad, and S. B. Yuste, Phys. Rev. E {\bf96} (2017) 032117]. The Sobolev regularity for the equation is…

Numerical Analysis · Mathematics 2020-11-13 Daxin Nie , Jing Sun , Weihua Deng

This paper considers particle propagation in a cylindrical molecular communication channel, e.g. a simplified model of a blood vessel. Emitted particles are influenced by diffusion, flow, and a vertical force induced e.g. by gravity or…

Computational Physics · Physics 2019-02-26 Maximilian Schäfer , Wayan Wicke , Rudolf Rabenstein , Robert Schober

Physical models with uncertain inputs are commonly represented as parametric partial differential equations (PDEs). That is, PDEs with inputs that are expressed as functions of parameters with an associated probability distribution.…

Numerical Analysis · Mathematics 2023-05-15 Benjamin M. Kent , Catherine E. Powell , David J. Silvester , Małgorzata J. Zimoń