Generation of entangled coherent states via cross phase modulation in a double electromagnetically induced transparency regime

The generation of an entangled coherent state is one of the most important ingredients of quantum information processing using coherent states. Recently, numerous schemes to achieve this task have been proposed. In order to generate travelling-wave entangled coherent states, cross phase modulation, optimized by optical Kerr effect enhancement in a dense medium in an electromagnetically induced transparency (EIT) regime, seems to be very promising. In this scenario, we propose a fully quantized model of a double-EIT scheme recently proposed [D. Petrosyan and G. Kurizki, {\sl Phys. Rev. A} {\bf 65}, 33833 (2002)]: the quantization step is performed adopting a fully Hamiltonian approach. This allows us to write effective equations of motion for two interacting quantum fields of light that show how the dynamics of one field depends on the photon-number operator of the other. The preparation of a Schr\"odinger cat state, which is a superposition of two distinct coherent states, is briefly exposed. This is based on non-linear interaction via double-EIT of two light fields (initially prepared in coherent states) and on a detection step performed using a $50:50$ beam splitter and two photodetectors. In order to show the entanglement of a generated entangled coherent state, we suggest to measure the joint quadrature variance of the field. We show that the entangled coherent states satisfy the sufficient condition for entanglement based on quadrature variance measurement. We also show how robust our scheme is against a low detection efficiency of homodyne detectors.Comment: 15 pages, 9 figures; extensively revised version; added Section

Finished genome of the fungal wheat pathogen Mycosphaerella graminicola Reveals dispensome structure, chromosome plasticity, and stealth pathogenesis.

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Randomized Clinical Trial of Laparoscopic Versus Open Repair of the Perforated Peptic Ulcer: The LAMA Trial

Background: Laparoscopic surgery has become popular during the last decade, mainly because it is associated with fewer postoperative complications than the conventional open appr

Ethnic Minority–Majority Unions in Estonia

Ethnic minority–majority unions—also referred to as mixed ethnic unions—are often seen as the ultimate evidence of the integration of ethnic minorities into their host societies. We investigated minority–majority unions in Estonia, where ethnic minorities account for one-third of the total population (Russians 26%, followed by Ukrainians, Byelorussians, Finns and other smaller groups). Using data from the 2000 Estonian census and regression models, we found that Slavic women are less likely to be in minority–majority unions than are members of other minority groups, with Russians being the least likely. Finns, who are culturally most similar to the Estonian majority population, are the most likely to form a union with an Estonian. For ethnic minority women, the likelihood of being in minority–majority unions is highest in rural areas and increases over generations, with third-generation immigrants being the most likely. Estonian women are most likely to have a minority partner when they or their parents were born abroad and when they live in urban areas. Our findings suggest that both the opportunity to meet potential partners and openness to other ethnic groups are important factors for understanding the dynamics of minority–majority unions

The State of the Art in Multilayer Network Visualization

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization there are many systems which visualize datasets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks, and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them