Unorthodox Parallelization for Bayesian Quantum State Estimation
Bayesian inference enables informationally efficient quantum state tomography (QST) yet is challenging to scale computationally. We demonstrate a parallelizable Bayesian QST method that, although unorthodox, proves remarkably practical, attaining significant speedups in multiqubit state estimation.
Authors
- Joseph M. Lukens (ORCID: https://orcid.org/0000-0001-9650-4462)
- Kody J. H. Law (ORCID: https://orcid.org/0000-0003-3133-2537)
- Hoa D. Nguyen (ORCID: https://orcid.org/0000-0003-2177-3478)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/cleo_at.2025.jps200_107
- Primary Topic
- Markov Chains and Monte Carlo Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00