Regularizing least squares quantum state tomography with classical shadows
Classical shadows herald remarkable opportunities for resource-efficient quantum estimation. Although superficially disconnected from traditional inference methods, we show how classical shadows fit under a larger umbrella of least squares regularization, revealing tradeoffs with related methods.
Authors
- Zhihui Zhu (ORCID: https://orcid.org/0000-0002-3856-0375)
- Joseph M. Lukens (ORCID: https://orcid.org/0000-0001-9650-4462)
- Brian T. Kirby (ORCID: https://orcid.org/0000-0002-2698-9887)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/cleo_fs.2025.ff120_6
- Primary Topic
- Quantum Information and Cryptography
- Type
- article
- Field-Weighted Citation Impact
- 0.00