Controlling Assembly and Encoding in Active Matter Using Light Patterns

The ability of active matter to assemble into reconfigurable nonequilibrium structures has garnered significant attention in recent years. A unique characteristic of active particles is the relationship between their steady-state density and local self-propulsion velocity. This provides a novel approach to facilitate self-assembly through spatial activity control. In experimental settings, this approach has enabled the triggering of synthetic self-propelled particle assembly through the application of specific light patterns, resulting in programmable, light-induced self-assembly of active rectification devices. In this study, we leverage simulations and data science to elucidate the interplay between active particle properties and light pattern features. We propose protocols to control smart templated assembly and motion in active matter and identify a metric to quantify the amount of information encoded in the active fluid post-application of the light pattern.