Tunable non-Gaussian resources for continuous-variable quantum technologies

Continuous-variable quantum cryptography is secure against non-Gaussian attacks.

A general study of arbitrary finite-size coherent attacks against continuous-variable quantum cryptographic schemes is presented. It is shown that, if the size of the blocks that can be coherently attacked by an eavesdropper is fixed and much smaller than the key size, then the optimal attack for a given signal-to-noise ratio in the transmission line is an individual Gaussian attack. Consequent...

Quantum Key Distribution using Continuous-variable non-Gaussian States

In this work we present a quantum key distribution protocol using continuous-variable nonGaussian states, homodyne detection and post-selection. The employed signal states are the Photon Added then Subtracted Coherent States (PASCS) in which one photon is added and subsequently one photon is subtracted. We analyze the performance of our protocol, compared to a coherent state based protocol, for...

Gaussian states in continuous variable quantum information

ISBN 88-7088-483-X (Bibliopolis, Napoli, 2005) http://www.bibliopolis.it These notes originated out of a set of lectures in Quantum Optics and Quantum Information given by one of us (MGAP) at the University of Napoli and the University of Milano. A quite broad set of issues are covered, ranging from elementary concepts to current research topics, and from fundamental concepts to applications. A...

Gaussian Quadrature Inference for Multicarrier Continuous-Variable Quantum Key Distribution

We propose the Gaussian quadrature inference (GQI) method for multicarrier continuousvariable quantum key distribution (CVQKD). A multicarrier CVQKD protocol utilizes Gaussian subcarrier quantum continuous variables (CV) for information transmission. The GQI framework provides a minimal error estimate of the quadratures of the CV quantum states from the discrete, measured noisy subcarrier varia...

Continuous Variable Teleportation with Non-Gaussian Resources in the Characteristic Function Representation