Memory and environment sensing in active systems

Memory and environment sensing in active systems
Seminar by MarcBESSE 
(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.