Collective dynamics of active matter
This course provides an overview of active matter, an interdisciplinary field focused on systems composed of self-propelled particles. Including basic concepts, stochastic and macroscopic descriptions, emphasizing the interactions between active particles and their collective dynamics. The course explores the relation between microscopic rules and macroscopic equations, such as the Fokker-Planck equation, to understand phase transitions and emergent behaviors in active systems. It also covers data-driven approaches for discovering these behaviors and inferring interaction laws, alongside computational modeling techniques.
Lecturer
Date
5th March ~ 21st May, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Tuesday | 13:00 - 16:25 | A3-1-103 | ZOOM 01 | 928 682 9093 | BIMSA |
Syllabus
1.Introduction of active matter
2.Stochastic description of active matter
3.Interaction between active particles
4.Macroscopic description of active matter
5.From stochastic dynamics to macroscopic equations (Fokker-Planck equation)
6.Phase transitions of active matter
7.Data-driven discovery of emergent behaviors in collective dynamics
8.Inference of interaction laws in collective dynamics
9.Computational models for active matter
10.Application in Machine learning
2.Stochastic description of active matter
3.Interaction between active particles
4.Macroscopic description of active matter
5.From stochastic dynamics to macroscopic equations (Fokker-Planck equation)
6.Phase transitions of active matter
7.Data-driven discovery of emergent behaviors in collective dynamics
8.Inference of interaction laws in collective dynamics
9.Computational models for active matter
10.Application in Machine learning
Reference
References:
1.Marchetti, M. Cristina, et al. "Hydrodynamics of soft active matter." Reviews of modern physics 85.3 (2013): 1143.
2.Zhong, Ming, Jason Miller, and Mauro Maggioni. "Data-driven discovery of emergent behaviors in collective dynamics." Physica D: Nonlinear Phenomena 411 (2020): 132542.
3.Supekar, Rohit, et al. "Learning hydrodynamic equations for active matter from particle simulations and experiments." Proceedings of the National Academy of Sciences 120.7 (2023): e2206994120.
4.Shaebani, M. Reza, et al. "Computational models for active matter." Nature Reviews Physics 2.4 (2020): 181-199.
5.[Book] van Saarloos, Wim, Vincenzo Vitelli, and Zorana Zeravcic. Soft Matter: Concepts, Phenomena, and Applications. Princeton University Press, 2024. https://softmatterbook.online/
1.Marchetti, M. Cristina, et al. "Hydrodynamics of soft active matter." Reviews of modern physics 85.3 (2013): 1143.
2.Zhong, Ming, Jason Miller, and Mauro Maggioni. "Data-driven discovery of emergent behaviors in collective dynamics." Physica D: Nonlinear Phenomena 411 (2020): 132542.
3.Supekar, Rohit, et al. "Learning hydrodynamic equations for active matter from particle simulations and experiments." Proceedings of the National Academy of Sciences 120.7 (2023): e2206994120.
4.Shaebani, M. Reza, et al. "Computational models for active matter." Nature Reviews Physics 2.4 (2020): 181-199.
5.[Book] van Saarloos, Wim, Vincenzo Vitelli, and Zorana Zeravcic. Soft Matter: Concepts, Phenomena, and Applications. Princeton University Press, 2024. https://softmatterbook.online/
Audience
Undergraduate
, Advanced Undergraduate
, Graduate
, Postdoc
, Researcher
Video Public
No
Notes Public
No
Language
Chinese
, English