Presented 24 June, 2014 as a seminar at Sandia National Laboratories.
Slides: HTML IPython Notebook: download, view online
High-fidelity control of quantum systems is an essential component in the development of useful quantum information processing devices. Such control is predicated on a characterization of the system of interest, and the accuracy of control is then assessed through characterization. In this seminar, we discuss novel approaches for each, and show how our work addresses practical concerns in quantum information experiments.
In particular, we address the characterization of quantum devices by applying the sequential Monte Carlo (SMC) algorithm. This algorithm is shown to be robust, including to finite sampling and to errors in simulation. We demonstrate the practicality of our approach by showing examples in randomized benchmarking experiments and in learning properties of nitrogen vacancy centers.
We also show how models of electronic systems can be incorporated into optimal control algorithms such as gradient-ascent pulse engineering (GRAPE). Our work allows accurate control to be obtained, even in the presence of strongly non-linear control systems.
Our work thus provides methods for the characterization and control of quantum systems that address practical concerns in modern quantum information experiments.