Privacy in Networks of Quantum Sensors
We treat privacy in a network of quantum sensors where accessible information is limited to specific functions of the network parameters, and all other information remains private. We develop an analysis of privacy in terms of a manipulation of the quantum Fisher information matrix, and find the optimal state achieving maximum privacy in the estimation of linear combination of the unknown parameters in a network of quantum sensors. We also discuss the effect of uncorrelated noise on the privacy of the network. Moreover, we illustrate our results with an example where the goal is to estimate the average value of the unknown parameters in the network. In this example, we also introduce the notion of quasiprivacy (ε privacy), quantifying how close the state is to being private.
Authors
- Damian Markham (ORCID: https://orcid.org/0000-0003-3111-7976)
- Matteo G. A. Paris (ORCID: https://orcid.org/0000-0001-7523-7289)
- Majid Hassani (ORCID: https://orcid.org/0000-0002-4077-0769)
- Steve Scheiner (ORCID: https://orcid.org/0000-0003-0793-0369)
Institutions
- Leiden University (NL)
- University of Milan (IT)
- Sorbonne Université (FR)
- Computer Algorithms for Medicine (AT)
- LIP6 (FR)
- Laboratoire Médiations (FR)
Publication Details
- Journal
- Physical Review Letters
- Published
- 2025-01-23
- DOI
- https://doi.org/10.1103/physrevlett.134.030802
- Citations
- 8
- Primary Topic
- Quantum Information and Cryptography
- Type
- article
- Field-Weighted Citation Impact
- 19.85
Funders
- European Commission
- Agence Nationale de la Recherche
- Horizon 2020 Framework Programme
- Multidisciplinary University Research Initiative
- HORIZON EUROPE Framework Programme
- SINOPEC Petroleum Exploration and Production Research Institute
- HORIZON EUROPE Marie Sklodowska-Curie Actions