Presented 1 July, 2014 as a presentation at Microsoft Research.
With the increasing scale and complexity of quantum information processing experiments, new methods are required to characterize and control quantum devices, and to verify the correct operation of those devices. In particular, the costs of simulating quantum systems are often a limiting factor in characterizaton tasks. In this talk, we show how to integrate quantum simulation resources into sequential Monte Carlo, and how this can alleviate some scaling concerns that arise in purely classical approaches. We demonstrate the practicality of our semiquantum algorithm by showing robustness to errors introduced by finite sampling, and by excluded terms in the trusted simulator. Finally, we discuss how to use this robustness together with Lieb-Robinson bounds in order to bootstrap, using smaller quantum resources to characterize larger devices.