Memory and environment sensing in active systems

Seminar by Marc BESSE 
(GULLIVER Laboratory, ESPCI, Paris)

The behaviour of active  systems, such as living cells, is usually modeled by self-propelled particles driven by internal forces and noise. However, these models often assume memoryless dynamics and no coupling of internal active forces to the environment. Here, we introduce a general theoretical framework that goes beyond this paradigm by incorporating internal state dynamics and environmental sensing into active particle models.

We show that when the self-propulsion of a particle depends on internal variables with their own complex dynamics — modulated by local environmental cues — environmental memory emerges and gives rise to new classes of behaviours. These include memory-induced responses, controllable localization in complex landscapes, suppression of motility-induced phase separation, and enhanced jamming transitions. Our results demonstrate how minimal information processing capabilities, intrinsic to non-equilibrium systems with internal states like living cells, can profoundly influence both individual and collective behaviours. This framework bridges cell-scale activity and large-scale intelligent motion in active agents, and opens the way to the analysis or design of systems ranging from synthetic colloids to biological collectives and robotic swarms.