PhD project: Controlling space and time in active matter

Project description

Understanding and controlling how objects move through space and time is at the bedrock of physics, hearkening back to Newton. However, our basic understanding starts to break down when the objects under consideration are actively sustaining their own motion and behaviour, i.e., are far from thermal equilibrium. This departure from equilibrium naturally brings about an arrow of time for active systems: forward and reversed movies of their dynamics look different. Moreover, active matter systems—such as schools of fish, colonies of cells and bacteria, and even robots—interact in complex ways resulting in collective behaviours that are not seen at equilibrium, presenting further theoretical challenges. Despite these challenges, the eventual understanding and control of such rich behaviours opens the door to new “active” machines, actuators, and devices that perform functions beyond that of passive (equilibrium) technologies.

In this project, we will use theoretical frameworks such as stochastic thermodynamics, optimal control theory, and statistical geometry to understand how active constituents explore space and time. We will begin to consider simple active matter models, e.g., self-propelled hard spheres, and then tackle more realistic models. This project involves both mathematical and computational techniques, with scope to include the use of AI.

Reading material:

Entropy production of active particles and for particles in active baths. Pietzonka, P et al. J. Phys. A. (2017)

Automomous engines driven by active matter: Energetics and design principles Pietzonka, P et al. PRX (2019)

Insertion space in repulsive active matter. Davis, L et al. arXiv (2025)

Learning protocols for the fast and efficient control of active matter Casert, C et al. Nat. Comm. (2024)

Active matter under control. Davis, L.  et al. PRX (2024)

Project supervisors

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