Structure identification and state initialization of spin networks with limited access

TL;DR

This paper presents two measurement-based methods for identifying the structure and initializing the state of spin networks with limited access, crucial for reliable quantum information processing.

Contribution

It introduces novel continuous-measurement techniques for network structure identification and state initialization in spin networks with single-node access.

Findings

High-probability network structure identification via Bayesian update

Deterministic spin state initialization using adaptive measurement

Applicable to networks with limited node accessibility

Abstract

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.