  Active materials take advantage of their internal sources of energy to
self-organize in an automated manner. This feature provides a novel opportunity
to design micron-scale machines with minimal required control. However,
self-organization goes hand in hand with predetermined dynamics that are hardly
susceptible to environmental perturbations. Therefore utilizing this feature of
active systems requires harnessing and directing the macroscopic dynamics to
achieve specific functions; which in turn necessitates understanding the
underlying mechanisms of active forces. Here we devise an optical control
protocol to engineer the dynamics of active networks composed of microtubules
and light-activatable motor proteins. The protocol enables carving activated
networks of different shapes, and isolating them from the embedding solution.
Studying a large set of shapes, we observe that the active networks contract in
a shape-preserving manner that persists over the course of contraction. We
formulate a coarse-grained theory and demonstrate that self-similarity of
contraction is associated with viscous-like active stresses. These findings
help us program the dynamics of the network through manipulating the light
intensity in space and time, and maneuver the network into bending in specific
directions, as well as temporally alternating directions. Our work improves
understanding the active dynamics in contractile networks, and paves a new path
towards engineering the dynamics of a large class of active materials.
