Jul 2026· Mathematical Models and Methods in Applied Sciences· pp. 1-26· 0 citations
TL;DR
A Multiscale Kinetic Theory of Active Particles (MS-KTAP), in which a sub-microscopic scale of interacting entities is incorporated into the description of collective dynamics, is introduced, in which competition and cooperation are described across multiple levels of organization.
Abstract
This paper develops a conceptual extension of the Kinetic Theory of Active Particles, building upon the framework introduced in [N. Bellomo, D. Burini and J. Liao, New trends in kinetic theory toward the complexity of living systems, Math. Models Methods Appl. Sci. 36 (2026) 341–397]. Living systems cannot be adequately described within classical single-scale paradigms, even when refined. To overcome this limitation, we introduce a Multiscale Kinetic Theory of Active Particles (MS-KTAP), in which a sub-microscopic scale of interacting entities is incorporated into the description of collective dynamics. In this framework, the activity variable is interpreted as an emergent quantity arising from lower-scale regulatory mechanisms and influenced by interactions across higher scales. The proposed framework captures key features of living systems — heterogeneity, adaptive decision-making, nonlinear and non-conservative interactions, spatial dynamics, and cross-scale feedback — within a unified mathematical structure. Competition and cooperation are thus described across multiple levels of organization. The first part of the paper derives the mathematical framework, while the second shows how specific models can be obtained. The paper concludes with perspectives on further developments, including possible integrations with scientific machine learning.
Nonequilibrium flow and transport problems are inherently multiscale. Kinetic theory provides a fundamental physical basis for describing such phenomena, since it connects microscopic transport and interaction processes with emergent macroscopic behavior across regimes. In many situations, however, continuum descriptio...
We develop a continuum theory for proliferating active matter starting from a microscopic stochastic model of self-propelled particles undergoing birth, death, and nonlocal competition. Beginning from the master equation, we derive mean-field evolution equations for the particle density and polarization fields and clos...
Nathan O. Silvano, Emilio Hernández-García, Crist'obal L'opez· 1 citation
When does a collection of autonomous cells become a multicellular individual? We propose that coherence provides a physical description of this transition. Coherence is treated as a global property arising when distinguishable constituents admit a physically meaningful collective state-space description. Using the cent...
Artificial intelligence, integrated within physics-informed computational frameworks, provides a powerful tool for analyzing complex, high-dimensional, and heterogeneous datasets while preserving the dynamical structure of the underlying system.
Giovanna Zimatore, Piercesare Grimaldi, S. Hatzopoulos et al.· Frontiers of Physics· 1 citation
Collective motion in self-propelled particle systems has been widely studied using the Vicsek model, which relies on pairwise alignment interactions. We introduce a generalized Vicsek model that incorporates higher-order (triadic) alignment interactions. Using agent-based simulations and mean-field theory, we demonstra...
Maryam Masoumi, A. Kargaran, Reza Jafari· 0 citations
This work extends existing variational learning approaches to collective systems with both interaction kernels and environmental/intra-agent forces and introduces a model-selection procedure based on the nonparametric learning framework to identify models that optimally explain a given set of trajectory observations.
N. de Silva, Ming Zhong, James M. Greene· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.