11,410 research outputs found

    Extended Variational Cluster Approximation

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    The variational cluster approximation (VCA) proposed by M. Potthoff {\it et al.} [Phys. Rev. Lett. {\bf 91}, 206402 (2003)] is extended to electron or spin systems with nonlocal interactions. By introducing more than one source field in the action and employing the Legendre transformation, we derive a generalized self-energy functional with stationary properties. Applying this functional to a proper reference system, we construct the extended VCA (EVCA). In the limit of continuous degrees of freedom for the reference system, EVCA can recover the cluster extension of the extended dynamical mean-field theory (EDMFT). For a system with correlated hopping, the EVCA recovers the cluster extension of the dynamical mean-field theory for correlated hopping. Using a discrete reference system composed of decoupled three-site single impurities, we test the theory for the extended Hubbard model. Quantitatively good results as compared with EDMFT are obtained. We also propose VCA (EVCA) based on clusters with periodic boundary conditions. It has the (extended) dynamical cluster approximation as the continuous limit. A number of related issues are discussed.Comment: 23 pages, 5 figures, statements about DCA corrected; published versio

    Superconductivity Near a Quantum Critical Point in Ba(Fe,Co)2As2

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    We will examine the possible link between spin fluctuations and the superconducting mechanism in the iron-based high temperature superconductor Ba(Fe,Co)2As2 based on NMR and high pressure transport measurements.Comment: Invited paper to m2s-IX (2009

    Adjusted Empirical Likelihood for Long-memory Time Series Models

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    Empirical likelihood method has been applied to short-memory time series models by Monti (1997) through the Whittle's estimation method. Yau (2012) extended this idea to long-memory time series models. Asymptotic distributions of the empirical likelihood ratio statistic for short and long-memory time series have been derived to construct confidence regions for the corresponding model parameters. However, computing profile empirical likelihood function involving constrained maximization does not always have a solution which leads to several drawbacks. In this paper, we propose an adjusted empirical likelihood procedure to modify the one proposed by Yau (2012) for autoregressive fractionally integrated moving average (ARFIMA) model. It guarantees the existence of a solution to the required maximization problem as well as maintains same asymptotic properties obtained by Yau (2012). Simulations have been carried out to illustrate that the adjusted empirical likelihood method for different long-time series models provides better confidence regions and coverage probabilities than the unadjusted ones, especially for small sample sizes

    Equivalence of glass transition and colloidal glass transition in the hard-sphere limit

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    We show that the slowing of the dynamics in simulations of several model glass-forming liquids is equivalent to the hard-sphere glass transition in the low-pressure limit. In this limit, we find universal behavior of the relaxation time by collapsing molecular-dynamics data for all systems studied onto a single curve as a function of T/pT/p, the ratio of the temperature to the pressure. At higher pressures, there are deviations from this universal behavior that depend on the inter-particle potential, implying that additional physical processes must enter into the dynamics of glass-formation.Comment: 4 pages, 4 figure


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    A computing device (e.g. mobile phone, smartphone, tablet computer, etc.) with multiple network connectivities may be configured to display a user interface with an indication of network quality to a user. For example, the displayed user interface may include an icon indicating the network quality (e.g., data transmission speeds, of a selected network connection) in a status bar. The computing device may also generate a network report detailing various performance metrics (e.g. an amount of data used, network speed, network reliability) of a selected network connection for a user-specified or pre-defined time period. The computing device may also provide a user with network usage suggestions based on the user’s network connection patterns. The computing device may also monitor changes in the network connection report and suggest a user take actions to correct, improve, or otherwise change network connectivity quality
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