Reciprocity can halve what a mechanical network can learn

Tunable mechanical networks are being developed as materials that learn in place.

Tunable mechanical networks are being developed as materials that learn in place. Capacity is estimated by counting tunable parameters against target constraints, ignoring Maxwell-Betti reciprocity, the symmetry every passive, linear elastic network obeys by construction. When p…