283 research outputs found

    Correlation between Penile Length and Anogenital Distance in Term Newborns, Gorgan, 2011

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    Background and purpose: Anogenital distance is an accepted indicator for endogenous or environmental effects of androgens on development of reproductive system in fetus and newborns. This study was done to determine the relationship between penile length and anogenital distance in Iranian newborns. Material and Methods: In this cross-sectional study stretched penile length (PL) and anogenital distance (AGD) were measured in 427 healthy male newborn infants born in a Teaching Hospital (in north of Iran). Other variables included the age of mothers, and weight, height, and head circumference of neonates. Normal distribution of variables was measured by Shapiro-Wilk and data was analyzed using Pearson Correlation tests Results: The mean of PL was 32.1±3.5 mm and the mean of AGD was 24.5±2.5mm. A weak correlation was observed between PL and AGD (r=0.097, p=0.046). Conclusion: The correlation between penile length and AGD showed that, AGD could be also used in assessing the genital system and even as a common indicator to assess the genital system in both sexes Keywords: penile length, anogenital, distance,term newborn, mal

    Recovering quantum information through partial access to the environment

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    We investigate the possibility of correcting errors occurring on a multipartite system through a feedback mechanism that acquires information from partial access to the environment. A partial control scheme of this kind might be useful when dealing with correlated errors. In fact, in such a case, it could be enough to gather local information to decide what kind of global recovery to perform. Then, we apply this scheme to the depolarizing and correlated errors, and quantify its performance by means of the entanglement fidelity

    Forgetfulness of continuous Markovian quantum channels

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    The notion of forgetfulness, used in discrete quantum memory channels, is slightly weakened in order to be applied to the case of continuous channels. This is done in the context of quantum memory channels with Markovian noise. As a case study, we apply the notion of weak-forgetfulness to a bosonic memory channel with additive noise. A suitable encoding and decoding unitary transformation allows us to unravel the effects of the memory, hence the channel capacities can be computed using known results from the memoryless setting.Comment: 6 pages, 2 figures, comments are welcome. Minor corrections and acknoledgment adde

    Equi-entangled bases in arbitrary dimensions

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    For the space of two identical systems of arbitrary dimensions, we introduce a continuous family of bases with the following properties: i) the bases are orthonormal, ii) in each basis, all the states have the same values of entanglement, and iii) they continuously interpolate between the product basis and the maximally entangled basis. The states thus constructed may find applications in many areas related to quantum information science including quantum cryptography, optimal Bell tests and investigation of enhancement of channel capacity due to entanglement.Comment: 10 pages, 2 figures, 1 table, Accepted for publication in Phys. Rev.

    New Phase Transitions in Optimal States for Memory Channels

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    We investigate the question of optimal input ensembles for memory channels and construct a rather large class of Pauli channels with correlated noise which can be studied analytically with regard to the entanglement of their optimal input ensembles. In a more detailed study of a subclass of these channels, the complete phase diagram of the two-qubit channel, which shows three distinct phases is obtained. While increasing the correlation generally changes the optimal state from separable to maximally entangled states, this is done via an intermediate region where both separable and maximally entangled states are optimal. A more concrete model, based on random rotations of the error operators which mimic the behavior of this subclass of channels is also presented.Comment: 13 pages, Late

    Characterization of qutrit channels in terms of their covariance and symmetry properties

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    We characterize the completely positive trace-preserving maps on qutrits (qutrit channels) according to their covariance and symmetry properties. Both discrete and continuous groups are considered. It is shown how each symmetry group restricts arbitrariness in the parameters of the channel to a very small set. Although the explicit examples are related to qutrit channels, the formalism is sufficiently general to be applied to qudit channels

    Transition behavior in the capacity of correlated-noisy channels in arbitrary dimensions

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    We construct a class of quantum channels in arbitrary dimensions for which entanglement improves the performance of the channel. The channels have correlated noise and when the level of correlation passes a critical value we see a sharp transition in the optimal input states (states which minimize the output entropy) from separable to maximally entangled states. We show that for a subclass of channels with some extra conditions, including the examples which we consider, the states which minimize the output entropy are the ones which maximize the mutual information.Comment: 11 pages, Latex, 4 figures, Accepted for publication in Physical Review

    Quantum information reclaiming after amplitude damping

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    We investigate the quantum information reclaim from the environment after amplitude damping has occurred. In particular we address the question of optimal measurement on the environment to perform the best possible correction on two and three dimensional quantum systems. Depending on the dimension we show that the entanglement fidelity (the measure quantifying the correction performance) is or is not the same for all possible measurements and uncover the optimal measurement leading to the maximum entanglement fidelity

    AI-aided exploration of lunar arch forms under in-plane seismic loading

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    Increasing computational power has led to the expansion of civil engi- neering research into using machine learning concepts for developing improved design strategies. These strategies are particularly useful for the design of extra-terrestrial habitats under uncertain environmental conditions. This paper focuses on building an unsupervised machine learning model (convolutional autoencoder) capable of detecting patterns in arch shapes and differentiating between their stress and displacement contours. Foremost, detailed discussions of the model’s architecture and input data are presented. The variation of arch shapes and con- tours between cluster centroids in the latent space is determined, proving the capability of optimisation by moving towards clusters with optimal contours. Finally, a regression model is built to investigate the rela- tionship between the input geometric variables and the latent space representation. We prove that the autoencoder and regression mod- els produce arch shapes with logical structural contours given a set of input geometric variables. The results presented in this paper provide essential tools for the development of an automated design strategy capable of finding optimal arch shapes for extra-terrestrial habitats
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