Theoretical investigation of moir\'e patterns in quantum images

Moir\'e patterns are produced when two periodic structures with different spatial frequencies are superposed. The transmission of the resulting structure gives rise to spatial beatings which are called moir\'e fringes. In classical optics, the interest in moir\'e fringes comes from the fact that the spatial beating given by the frequency difference gives information about details(high spatial frequency) of a given spatial structure. We show that moir\'e fringes can also arise in the spatial distribution of the coincidence count rate of twin photons from the parametric down-conversion, when spatial structures with different frequencies are placed in the path of each one of the twin beams. In other words,we demonstrate how moir\'e fringes can arise from quantum images

Conservation of Orbital Angular Momentum in Stimulated Down-Conversion

We report on an experiment demonstrating the conservation of orbital angular momentum in stimulated down-conversion. The orbital angular momentum is not transferred to the individual beams of the spontaneous down-conversion, but it is conserved when twin photons are taken individually. We observe the conservation law for an individual beam of the down-conversion through cavity-free stimulated emission.Comment: Submitted for publication in Phys. Rev. Let

Topological phase for spin-orbit transformations on a laser beam

We investigate the topological phase associated with the double connectedness of the SO(3) representation in terms of maximally entangled states. An experimental demonstration is provided in the context of polarization and spatial mode transformations of a laser beam carrying orbital angular momentum. The topological phase is evidenced through interferometric measurements and a quantitative relationship between the concurrence and the fringes visibility is derived. Both the quantum and the classical regimes were investigated.Comment: 4 pages, 4 figure

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they actually expect to disclose, hence their privacy is threatened. To mitigate such threats, several privacy protection techniques based on location generalization have been proposed. Although the privacy implications of such techniques have been extensively studied, the utility implications are mostly unknown. In this paper, we propose a predictive model for quantifying the effect of a privacy-preserving technique (i.e., generalization) on the perceived utility of check-ins. We first study the users’ motivations behind their location check-ins, based on a study targeted at Foursquare users (N = 77). We propose a machine-learning method for determining the motivation behind each check-in, and we design a motivation-based predictive model for the utility implications of generalization. Based on the survey data, our results show that the model accurately predicts the fine-grained motivation behind a check-in in 43% of the cases and in 63% of the cases for the coarse-grained motivation. It also predicts, with a mean error of 0.52 (on a scale from 1 to 5), the loss of utility caused by semantic and geographical generalization. This model makes it possible to design of utility-aware, privacy-enhancing mechanisms in location-based online social networks. It also enables service providers to implement location-sharing mechanisms that preserve both the utility and privacy for their users