Squeezing-enhanced phase-shift-keyed binary communication in noisy channels

We address binary phase-shift-keyed communication channels based on Gaussian states and prove that squeezing improves state discrimination at fixed energy of the channel, also in the presence of phase diffusion. We then assess performances of homodyne detection against the ultimate quantum limits to discrimination, and show that homodyning achieves optimality in large noise regime. Finally, we consider noise in the preparation of the seed signal (before phase encoding) and show that also in this case squeezing may improve state discrimination in realistic conditions.Comment: 6 pages, 5 figure

Two exact properties of the perturbative expansion for the two-dimensional electron liquid with Rashba or Dresselhaus spin-orbit coupling

We have identified two useful exact properties of the perturbative expansion for the case of a two-dimensional electron liquid with Rashba or Dresselhaus spin-orbit interaction and in the absence of magnetic field. The results allow us to draw interesting conclusions regarding the dependence of the exchange and correlation energy and of the quasiparticle properties on the strength of the spin-orbit coupling which are valid to all orders in the electron-electron interaction.Comment: 6 pages, 1 figur

Exchange energy and generalized polarization in the presence of spin-orbit coupling in two dimensions

We discuss a general form of the exchange energy for a homogeneous system of interacting electrons in two spatial dimensions which is particularly suited in the presence of a generic spin-orbit interaction. The theory is best formulated in terms of a generalized fractional electronic polarization. Remarkably we find that a net generalized polarization does not necessarily translate into an increase in the magnitude of the exchange energy, a fact that in turn favors unpolarized states. Our results account qualitatively for the findings of recent experimental investigations

Asymmetries in extraction from nominal copular sentences: A challenging case study for NLP tools

In this paper we discuss two types of nominal copular sentences (Canonical and Inverse, Moro 1997) and we demonstrate how the peculiarities of these two configurations are hardly considered by standard NLP tools that are currently publicly available. Here we show that example-based MT tools (e.g. Google Translate) as well as other NLP tools (UDpipe, LinguA, Stanford Parser, and Google Cloud AI API) fail in capturing the critical distinctions between the two structures in the end producing both wrong analyses and, possibly as a consequence of a non-coherent (or missing) structural analysis, incorrect translations in the case of MT tools. To support the proposed analysis, we present also an empirical study showing that native speakers are indeed sensitive to the critical distinctions. This poses a sharp challenge for NLP tools that aim at being cognitively plausible or at least descriptively adequate (Chowdhury & Zamparelli 2018)