Majid Hassani | LIP6 - Équipe QI

Privacy in networks of quantum sensors

Wed, 01 Jan 2025 00:00:00 +0000

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 quasi-privacy ($\epsilon$-privacy), quantifying how close the state is to being private.

Private and Robust States for Distributed Quantum Sensing

Wed, 31 Jul 2024 00:00:00 +0000

Distributed quantum sensing enables the estimation of multiple parameters encoded in spatially separated probes. While traditional quantum sensing is often focused on estimating a single parameter with maximum precision, distributed quantum sensing seeks to estimate some function of multiple parameters that are only locally accessible for each party involved. In such settings it is natural to not want to give away more information than is necessary. To address this, we use the concept of privacy with respect to a function, ensuring that only information about the target function is available to all the parties, and no other information. We define a measure of privacy (essentially how close we are to this condition being satisfied), and show it satisfies a set of naturally desirable properties of such a measure. Using this privacy measure, we identify and construct entangled resources states that ensure privacy for a given function under different resource distributions and encoding dynamics, characterized by Hamiltonian evolution. For separable and parallel Hamiltonians, we prove that the GHZ state is the only private state for certain linear functions, with the minimum amount of required resources, up to SLOCC. Recognizing the vulnerability of this state to particle loss, we create families of private states, that remain robust even against loss of qubits, by incorporating additional resources. We then extend our findings to different resource distribution scenarios and Hamiltonians, resulting in a comprehensive set of private and robust states for distributed quantum estimation. These results advance the understanding of privacy and robustness in multi-parameter quantum sensing.

Private network parameter estimation with quantum sensors

Sat, 06 Aug 2022 00:00:00 +0000

Networks of quantum sensors are a central application of burgeoning quantum networks. A key question for the use of such networks will be their security, particularly against malicious participants of the network. We introduce a protocol to securely evaluate linear functions of parameters over a network of quantum sensors, ensuring that all parties only have access to the function value, and no access to the individual parameters. This has application to secure networks of clocks and opens the door to more general applications of secure multiparty computing to networks of quantum sensors.

Multi-parameter quantum metrology with discrete-time quantum walk

Fri, 29 Oct 2021 16:00:00 +0100