Convex combinations of bosonic pure-loss channels
Giuseppe Catalano, Marco Fanizza, Francesco Anna Mele, Giacomo De Palma, Vittorio Giovannetti

TL;DR
This paper explores the quantum information capacities of convex combinations of bosonic pure-loss channels, revealing that non-Gaussian states outperform Gaussian ones and that positive quantum communication rates are achievable despite fading noise.
Contribution
It provides the first comprehensive quantum Shannon theory analysis of fading channels, demonstrating the advantages of non-Gaussian states and developing optimization algorithms.
Findings
Entanglement and quantum key distribution are possible at positive rates over any fading channel.
Non-Gaussian Fock-diagonal states outperform Gaussian states in achieving channel capacities.
Analytical capacity results for binary fading models and iterative algorithms for general fading distributions.
Abstract
The pure-loss channel is a fundamental model for describing noise in bosonic quantum platforms. It is characterised by a single parameter, the transmissivity, which quantifies the fraction of the input energy that reaches the output of the channel. In realistic scenarios, however, such as free-space quantum communication, the transmissivity is not fixed but fluctuates from one channel use to another. In this setting, the overall channel is effectively described as a convex combination of pure-loss channels, known as a fading channel. Despite its practical relevance, the quantum Shannon theory of the fading channel has remained largely unexplored. Here, we address this gap, specifically investigating degradability, anti-degradability, entanglement breakingness, and capacities of the fading channel. Of particular relevance to practical quantum-internet applications, we prove that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
