Applied Bayesian Qubit State Tomography
Published in Proc. Korea Information and Communications Society (KICS) Summer Conference, 2020
Recommended citation: S. M. Kazim, A. Farooq, J. ur Rehman, and H. Shin, "Applied Bayesian Qubit State Tomography," Proc. Korea Information and Communications Society (KICS) Summer Conference, pp. 190-192 Korea, Aug. 2020.
Abstract – In this paper we present a simple Bayesian inference based single-stage quantum state tomography. Previous approaches such as maximum likelihood estimation are compared with Bayesian analysis and its advantages especially concerning error bars are highlighted. We describe the underpinnings of Monte Carlo based methods and show how they can be applied to reconstruct a valid density matrix representing a single qubit. We also demonstrate the formulation of qubit tomography as a problem such that statistical packages such as Stan can be accessed as a black-box and their results can be validated.