Structure identification and state initialization of spin networks with limited access

For reliable and consistent quantum information processing carried out on a quantum network, the network structure must be fully known and a desired initial state must be accurately prepared on it. In this paper, for a class of spin networks with only its single node accessible, we provide two continuous-measurement-based methods to achieve the above requirements; the first identifies the unknown network structure with a high probability, based on a continuous-time Bayesian update of the graph structure and the second is, with the use of an adaptive measurement technique, able to deterministically drive any mixed state to a spin coherent state for network initialization.