<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Matteo G. A. Paris | LIP6 - Équipe QI</title><link>https://qi.lip6.fr/fr/people/matteo-g.-a.-paris/</link><atom:link href="https://qi.lip6.fr/fr/people/matteo-g.-a.-paris/index.xml" rel="self" type="application/rss+xml"/><description>Matteo G. A. Paris</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>fr</language><copyright>© 2022 LIP6 Quantum Information Team</copyright><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://qi.lip6.fr/media/icon_hu_bdeccd9e706ea09d.png</url><title>Matteo G. A. Paris</title><link>https://qi.lip6.fr/fr/people/matteo-g.-a.-paris/</link></image><item><title>Privacy in networks of quantum sensors</title><link>https://qi.lip6.fr/fr/publication/4803645-privacy-in-networks-of-quantum-sensors/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://qi.lip6.fr/fr/publication/4803645-privacy-in-networks-of-quantum-sensors/</guid><description>&lt;p&gt;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.&lt;/p&gt;</description></item></channel></rss>