Permanent link to this recordhttp://hdl.handle.net/10754/666658
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AbstractWe describe a method for Bayesian quantum state estimation combining efficient parameterization, a pseudo-likelihood, and advanced numerical sampling techniques. Examples reveal significant computational speedup, indicating the approach's promise in practical quantum state tomography.
CitationLukens, J. M., Law, K. J. H., Jasra, A., & Lougovski, P. (2020). Computationally efficient Bayesian quantum state tomography. 2020 IEEE Photonics Conference (IPC). doi:10.1109/ipc47351.2020.9252416
SponsorsWe thank R. S. Bennink and B. P. Williams for discussions. This work was performed in part at Oak Ridge National Laboratory, operated by UT-Battelle for the U.S. Department of Energy under contract no. DE-AC0500OR22725. Funding was provided by the U.S. Department of Energy, Office of Advanced Scientific Computing Research, through the Quantum Algorithm Teams and Early Career Research Programs.
Conference/Event name2020 IEEE Photonics Conference, IPC 2020