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 its single node only accessible, we provide two continuous-measurement-based methods to achieve the above requirements; the first one identifies the unknown network structure with high probability, based on continuous-time Bayesian update of the graph structure; the second one is, with the use of adaptive measurement technique, able to deterministically drive any mixed state to a spin coherent state for network initialization.