Self-Learning Active Metamaterials: A Local Learning Framework for Non-reciprocal Linear Flow Networks

We present a framework for physical local learning in metamaterials based on a linear flow network with symmetric and antisymmetric components. This model extends previous work on steady-state networks, incorporating asymmetric interactions to broaden the scope and potential applications of local learning procedures.