11 research outputs found

    Entanglement Sharing in the Two-Atom Tavis-Cummings Model

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    Individual members of an ensemble of identical systems coupled to a common probe can become entangled with one another, even when they do not interact directly. We investigate how this type of multipartite entanglement is generated in the context of a system consisting of two two-level atoms resonantly coupled to a single mode of the electromagnetic field. The dynamical evolution is studied in terms of the entanglements in the different bipartite partitions of the system, as quantified by the I-tangle. We also propose a generalization of the so-called residual tangle that quantifies the inherent three-body correlations in our tripartite system. This enables us to completely characterize the phenomenon of entanglement sharing in the case of the two-atom Tavis-Cummings model, a system of both theoretical and experimental interest.Comment: 11 pages, 4 figures, submitted to PRA, v3 contains corrections to small error

    A New Strategy of Quantum-State Estimation for Achieving the Cramer-Rao Bound

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    We experimentally analyzed the statistical errors in quantum-state estimation and examined whether their lower bound, which is derived from the Cramer-Rao inequality, can be truly attained or not. In the experiments, polarization states of bi-photons produced via spontaneous parametric down-conversion were estimated employing tomographic measurements. Using a new estimation strategy based on Akaike's information criterion, we demonstrated that the errors actually approach the lower bound, while they fail to approach it using the conventional estimation strategy.Comment: 4 pages, 2 figure

    Local asymptotic normality for finite dimensional quantum systems

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    We extend our previous results on local asymptotic normality (LAN) for qubits, to quantum systems of arbitrary finite dimension dd. LAN means that the quantum statistical model consisting of nn identically prepared dd-dimensional systems with joint state ρn\rho^{\otimes n} converges as nn\to\infty to a statistical model consisting of classical and quantum Gaussian variables with fixed and known covariance matrix, and unknown means related to the parameters of the density matrix ρ\rho. Remarkably, the limit model splits into a product of a classical Gaussian with mean equal to the diagonal parameters, and independent harmonic oscillators prepared in thermal equilibrium states displaced by an amount proportional to the off-diagonal elements. As in the qubits case, LAN is the main ingredient in devising a general two step adaptive procedure for the optimal estimation of completely unknown dd-dimensional quantum states. This measurement strategy shall be described in a forthcoming paper.Comment: 64 page

    Composition and Potential Health Benefits of Pomegranate: A Review

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    Background: Pomegranate (Punica granatum L.) fruits are widely consumed and used as preventive and therapeutic agents since ancient times. Pomegranate is a rich source of a variety of phytochemicals, which are responsible for its strong antioxidative and anti-inflammatory potential. Objective: The aim of this review is to provide an up-to-date overview of the current knowledge of chemical structure and potential health benefits of pomegranate. Methods: A comprehensive search of available literature. Results: The review of the literature confirms that juice and extracts obtained from different parts of this plant, including fruit peel, seeds, and leaves exert health benefits in both in vitro and in vivo studies. The antidiabetic, antihypertensive, antimicrobial and anti-tumour effects of pomegranate fruit are of particular scientific and clinical interest. Conclusion: Further investigations are required to clarify the mechanism of action of the bioactive ingredients and to reveal full potential of pomegranate as both preventive and therapeutic agent

    Molecular Dynamics Studies on Amyloidogenic Proteins

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    Molecular dynamics simulations of hydrated unsaturated lipid bilayers in the liquid-crystal phase and comparison to self-consistent field modeling

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