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Modern energy systems in vehicles and built infrastructure are governed by high-dimensional dynamics spanning multiple physical domains (e.g., electrical, thermal, mechanical) and timescales. This tutorial paper presents a graph-based…

Classical cellular automata represent a class of explicit discrete spacetime lattice models in which complex large-scale phenomena emerge from simple deterministic rules. With the goal to uncover different physically distinct classes of…

Statistical Mechanics · Physics 2026-05-27 Rustem Sharipov , Matija Koterle , Sašo Grozdanov , Tomaž Prosen

A large number of models for pedestrian dynamics have been developed over the years. However, so far not much attention has been paid to their quantitative validation. Usually the focus is on the reproduction of empirically observed…

Physics and Society · Physics 2010-07-26 Andreas Schadschneider , Armin Seyfried

Spatial-temporal prediction is a critical problem for intelligent transportation, which is helpful for tasks such as traffic control and accident prevention. Previous studies rely on large-scale traffic data collected from sensors. However,…

Machine Learning · Computer Science 2021-08-24 Chung-Yi Lin , Hung-Ting Su , Shen-Lung Tung , Winston H. Hsu

A cellular automata model that describes as limit cases of his parameters the spread of contagious diseases modeled by systems of ordinary or partial differential equations is developed. Periodic features of the behavior of human settlement…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Ricardo Mansilla , Jose L. Gutierrez

We formalise and study multi-agent timed models MAPTs (Multi-Agent with timed Periodic Tasks), where each agent is associated to a regular timed schema upon which all possibles actions of the agent rely. MAPTs allow for an accelerated…

Multiagent Systems · Computer Science 2019-11-19 Johan Arcile , Raymond Devillers , Hanna Klaudel

Graphs are widespread data structures used to model a wide variety of problems. The sheer amount of data to be processed has prompted the creation of a myriad of systems that help us cope with massive scale graphs. The pressure to deliver…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-09 Luis M. Vaquero , Felix Cuadrado , Matei Ripeanu

The system of cellular automata, which expresses the process of dissemination and publication of the news among separate information resources, has been described. A bell-shaped dependence of news diffusion on internet-sources (web-sites)…

Information Theory · Computer Science 2008-12-18 D. V. Lande

This paper shows as the relativistic Doppler effect can be extended also to time and space associated to moving bodies. This extension derives from the analysis of the wave-fronts of the light emitted by a moving source in inertial motion…

General Physics · Physics 2012-08-31 Giovanni Zanella

We discuss how to characterize the behavior of a chaotic dynamical system depending on a parameter that varies periodically in time. In particular, we study the predictability time, the correlations and the mean responses, by defining a…

chao-dyn · Physics 2009-10-28 A Crisanti , M. Falcioni , G. Lacorata , R. Purini , A. Vulpiani

Quantum cellular automata consist in arrays of identical finite-dimensional quantum systems, evolving in discrete-time steps by iterating a unitary operator G. Moreover the global evolution G is required to be causal (it propagates…

Quantum Physics · Physics 2019-09-09 Pablo Arrighi

Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, traffic engineering, traffic prediction and urban planning. In this survey we review major characteristics of human mobility studies…

Social and Information Networks · Computer Science 2013-07-04 Fereshteh Asgari , Vincent Gauthier , Monique Becker

This article surveys the variety of ways in which a directed acyclic graph (DAG) can be used to represent a problem of probabilistic causality. For each of these we describe the relevant formal or informal semantics governing that…

Statistics Theory · Mathematics 2024-02-16 Philip Dawid

An analytical method for investigation of the evolution of dynamical systems {\it with independent on time accuracy} is developed for perturbed Hamiltonian systems. The error-free estimation using of computer algebra enables the application…

Instrumentation and Methods for Astrophysics · Physics 2016-12-13 A. V. Gurzadyan , A. A. Kocharyan

Controllable multimodal generation is commonly formulated as an inference-time conditioning problem using prompts, guidance, or auxiliary modules. While effective, such approaches do not explicitly structure how semantic attributes evolve,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jamuna S. Murthy , Amin Karimi Monsefi , Rajiv Ramnath

A model of discrete spacetime on a microscopic level is considered. It is a directed acyclic dyadic graph. This is the particular case of a causal set. The goal of this model is to describe particles as some repetitive symmetrical…

General Relativity and Quantum Cosmology · Physics 2014-06-05 Alexey L. Krugly

An emerging way of tackling the dimensionality issues arising in the modeling of a multivariate process is to assume that the inherent data structure can be captured by a graph. Nevertheless, though state-of-the-art graph-based methods have…

Machine Learning · Statistics 2016-07-13 Andreas Loukas , Nathanael Perraudin

Discretizing spacetime is often a natural step towards modelling physical systems. For quantum systems, if we also demand a strict bound on the speed of information propagation, we get quantum cellular automata (QCAs). These originally…

Quantum Physics · Physics 2020-12-02 Terry Farrelly

A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges. The network structure,…

Adaptation and Self-Organizing Systems · Physics 2012-10-10 Petter Holme , Jari Saramäki

Within many real-world networks the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different…

Machine Learning · Computer Science 2020-07-07 Vincent Froese , Brijnesh Jain , Rolf Niedermeier , Malte Renken