Shared randomness is the central ingredient for stabilizing symmetrizable communication systems against arbitrarily varying jammers. Given the presence of the jammer, however, the question arises how this precious resource could have been distributed. Several works discuss the use of external sources for this task. In this work, we show, based on the most standard optical communication model, how the sender and receiver can employ entangled two-mode squeezed states to counter the jamming attack of an energy-limited jammer during the distribution phase when both the sender and jammer are allowed to use binary phase shift keying and two-mode squeezed vacuum states.

Arbitrarily varying channels offer a powerful framework for analyzing the robustness of quantum communication systems, especially for classical-quantum models, where the analysis displays strengths or weaknesses of specific signal constellations under generic attacks. In this work, we provide a coding theorem for a large class of practically relevant arbitrarily varying channel models. Namely, we give an explicit capacity formula for the lossy bosonic channel subject to semi-classical attacks, where an adversary injects semi-classical states into the transmission line. Mathematically, this is modeled via a beam-splitter setup, with transmitter and jammer controlling different input ports and the receiver observing one output port. We show how a recently conjectured new quantum entropy power inequality relates to our capacity formula.

We study the problem of joint communication and detection of wiretapping on an optical fiber from a quantum perspective. Our system model describes a communication link that is capable of transmitting data under normal operating conditions and raising a warning at the transmitter side in case of eavesdropping. It contributes to a unified modelling approach, based on which established quantum communication paradigms like quantum key distribution can be compared to other approaches offering similar functionality.

Recent efforts in the design of communication systems have in addition to data rates embraced a focus on other metrics, such as round-trip latency. Data transmission over a channel is typically preceded by so-called pilot symbols, which let the receiver learn the channel conditions. Together with appropriate feedback, this allows for transmission at high data rates. Trading data rates for communication latency, a communication link may however avoid feedback and instead operate under channel uncertainty, in which case the accurate model is the compound channel. Further reductions of latency may be harnessed from quantum receiver design. In this work we focus in particular on the application of the sequential decoding approach to the bosonic compound channel with unknown phase rotations, loss parameters and thermal noise values. We show that sequential decoding is optimal.

The Aral Sea was the fourth largest lake of the world until the 1960s. Due to large-scale irrigation projects in the region, the lake started shrinking drastically [1],[6]. In this paper we estimate the volume change of water in the Aral Sea from geometrical remote sensing techniques (satellite altimetry and optical satellite images) in combination with a digital elevation model. The results are compared with observations of water storage changes from the dedicated satellite gravity field mission GRACE for the time frame between 2002 and 2011.