Southwest Quantum Information and Technology

Practical Bayesian tomography

Presenting Author: Christopher Granade, University of Sydney
Contributing Author(s): Joshua Combes, D. G. Cory

In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we solve all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby, and by Ferrie, to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first informative priors on quantum states and channels. Finally, we develop a method that allows online tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.

Read this article online: http://arxiv.org/abs/1509.03770

(Session 5 : Thursday from 5:00 - 7:00 pm)