We introduce the notion of privacy in quantum estimation by considering an one-parameter family of isometries taking one input into two output systems. It stems on the separate and adversarial control of the two output systems as well as on the local minimization of the mean square error. Applications to two-qubit unitaries (with one qubit in a fixed input state) are presented.
Privacy in Quantum Estimation
Stefano Mancini
2019-01-01
Abstract
We introduce the notion of privacy in quantum estimation by considering an one-parameter family of isometries taking one input into two output systems. It stems on the separate and adversarial control of the two output systems as well as on the local minimization of the mean square error. Applications to two-qubit unitaries (with one qubit in a fixed input state) are presented.File in questo prodotto:
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