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Title
Active particles. Volume 3, Advances in theory, models, and applications / Nicola Bellomo, José Antonio Carrillo, Eitan Tadmor, editors.
ISBN
9783030933029 (electronic bk.)
3030933024 (electronic bk.)
9783030933012 (print)
3030933016
Published
Cham, Switzerland : Birkhäuser, 2022.
Language
English
Description
1 online resource (vii, 226 pages) : illustrations (some color).
Other Standard Identifiers
10.1007/978-3-030-93302-9 doi
Call Number
QA401
Dewey Decimal Classification
511/.8
Summary
This edited volume collects six surveys that present state-of-the-art results on modeling, qualitative analysis, and simulation of active matter, focusing on specific applications in the natural sciences. Following the previously published Active Particles volumes, these chapters are written by leading experts in the field and reflect the diversity of subject matter in theory and applications within an interdisciplinary framework. Topics covered include: Variability and heterogeneity in natural swarms Multiscale aspects of the dynamics of human crowds Mathematical modeling of cell collective motion triggered by self-generated gradients Clustering dynamics on graphs Random Batch Methods for classical and quantum interacting particle systems The consensus-based global optimization algorithm and its recent variants Mathematicians and other members of the scientific community interested in active matter and its many applications will find this volume to be a timely, authoritative, and valuable resource.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 5, 2022).
Series
Modeling and simulation in science, engineering & technology, 2164-3725
Available in Other Form
Print version: 9783030933012
G. Ariel, A. Ayali, A. Be'er, D. Knebel, Variability and Heterogeneity in Natural Swarms: Experiments and Modeling
M. Bruna, M. Burger, J.-F. Pietschmann, M.-T. Wolfram, Active Crowds
V. Calvez, M. Demircigil, R. Sublet, Mathematical Modeling of Cell Collective Motion Triggered by Self-Generated Gradients
K. Craig, N. Garcia Trillos, D. Slepcev, Clustering Dynamics on Graphs: From Spectral Clustering to Mean Shift Through Fokker-Planck Interpolation
S. Jin, L. Li, Random Batch Methods for Classical and Quantum Interacting Particle Systems and Statistical Samplings
C. Totzeck, Trends in Consensus-Based Optimization.
