no code implementations • 26 Mar 2024 • Hao-Chung Cheng, Nilanjana Datta, Nana Liu, Theshani Nuradha, Robert Salzmann, Mark M. Wilde
By making use of the wealth of knowledge that already exists in the literature on quantum hypothesis testing, we characterize the sample complexity of binary quantum hypothesis testing in the symmetric and asymmetric settings, and we provide bounds on the sample complexity of multiple quantum hypothesis testing.
no code implementations • 22 Jun 2023 • Theshani Nuradha, Ziv Goldfeld, Mark M. Wilde
We propose a versatile privacy framework for quantum systems, termed quantum pufferfish privacy (QPP).
no code implementations • 17 Jun 2022 • Ziv Goldfeld, Kristjan Greenewald, Theshani Nuradha, Galen Reeves
However, a quantitative characterization of how SMI itself and estimation rates thereof depend on the ambient dimension, which is crucial to the understanding of scalability, remain obscure.