87 resultados para Hybrid spin-photon qubits


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We have succeeded in the preparation of electrospun fibers of polystyrene incorporating a metallo-organic polymer of [Fe (II) (4-octadecyl-1,2,4-triazole)3(ClO4)2]n. The obtained fibers have diameters in the range 2–4 µm and show the characteristic spin-crossover transition associated with the metallo-organic polymer. The structure of both, polystyrene and the metallo-organic polymer, in the fibers was also studied.

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In contrast with recent claims that the Heyd-Scuseria-Ernzerhof (HSE) screened hybrid functional can provide a good description of the electronic and magnetic structures of VO2 phases [Eyert, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.016401 107, 016401 (2011)], we show here that the HSE lowest-energy solutions for both the low-temperature monoclinic (M1) phase and the high-temperature rutile (R) phase, which are obtained upon inclusion of spin polarization, are at odds with experimental observations. For the M1 phase the ground state is (but should not be) magnetic, while the ground state of the R phase, which is also spin polarized, is not (but should be) metallic. The energy difference between the low-temperature and high-temperature phases has strong discrepancies with the experimental latent heat.

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The metal–insulator transition of VO2 so far has evaded an accurate description by density functional theory. The screened hybrid functional of Heyd, Scuseria and Ernzerhof leads to reasonable solutions for both the low-temperature monoclinic and high-temperature rutile phases only if spin polarization is excluded from the calculations. We explore whether a satisfactory agreement with experiment can be achieved by tuning the fraction of Hartree Fock exchange (a) in the density functional. It is found that two branches of locally stable solutions exist for the rutile phase for 12:5% 6 a 6 20%. One is metallic and has the correct stability as compared to the monoclinic phase, the other is insulating with lower energy than the metallic branch. We discuss these observations based on the V 3d orbital occupations and conclude that a ¼ 10% is the best possible choice for spin-polarized VO2 calculations.

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Data assimilation – the set of techniques whereby information from observing systems and models is combined optimally – is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal interpolation, three-dimensional and four-dimensional variational methods, the Kalman Filter), together with the approximations that are often necessary to make them practicable. After pointing out a variety of benefits of data assimilation, the paper then outlines some practical applications of the exploitation of Earth Observation by data assimilation in the areas of operational oceanography, chemical weather forecasting and carbon cycle modelling. Finally, some challenges for the future are noted.

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The research presented in this article centres on an under-researched demographic group of young return migrants, namely, second-generation Barbadians, or 'Bajan-Brits', who have decided to 'return' to the birthplace of their parents. Based on 51 in-depth interviews, the essay examines the experiences of second-generation return migrants from an interpretative perspective framed within post-colonial discourse. The article first considers the Bajan-Brits and issues of race in the UK before their decision to migrate. It is then demonstrated that on 'return', in certain respects, these young, black English migrants occupy a liminal position of cultural, racial and economic privilege, based on their 'symbolic' or 'token' whiteness within the post-colonial context of Barbados. But this very hybridity and inbetweeness means that they also face difficulties and associated feelings of social alienation and discrimination. The ambivalent status of this transnational group of migrants serves to challenge traditional notions of Barbadian racial identity.

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Across Europe, elevated phosphorus (P) concentrations in lowland rivers have made them particularly susceptible to eutrophication. This is compounded in southern and central UK by increasing pressures on water resources, which may be further enhanced by the potential effects of climate change. The EU Water Framework Directive requires an integrated approach to water resources management at the catchment scale and highlights the need for modelling tools that can distinguish relative contributions from multiple nutrient sources and are consistent with the information content of the available data. Two such models are introduced and evaluated within a stochastic framework using daily flow and total phosphorus concentrations recorded in a clay catchment typical of many areas of the lowland UK. Both models disaggregate empirical annual load estimates, derived from land use data, as a function of surface/near surface runoff, generated using a simple conceptual rainfall-runoff model. Estimates of the daily load from agricultural land, together with those from baseflow and point sources, feed into an in-stream routing algorithm. The first model assumes constant concentrations in runoff via surface/near surface pathways and incorporates an additional P store in the river-bed sediments, depleted above a critical discharge, to explicitly simulate resuspension. The second model, which is simpler, simulates P concentrations as a function of surface/near surface runoff, thus emphasising the influence of non-point source loads during flow peaks and mixing of baseflow and point sources during low flows. The temporal consistency of parameter estimates and thus the suitability of each approach is assessed dynamically following a new approach based on Monte-Carlo analysis. (c) 2004 Elsevier B.V. All rights reserved.

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Spin factors and generalizations are used to revisit positive generation of B(E, F), where E and F are ordered Banach spaces. Interior points of B(E, F)+ are discussed and in many cases it is seen that positive generation of B(E, F) is controlled by spin structure in F when F is a JBW-algebra.

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Space weather effects on technological systems originate with energy carried from the Sun to the terrestrial environment by the solar wind. In this study, we present results of modeling of solar corona-heliosphere processes to predict solar wind conditions at the L1 Lagrangian point upstream of Earth. In particular we calculate performance metrics for (1) empirical, (2) hybrid empirical/physics-based, and (3) full physics-based coupled corona-heliosphere models over an 8-year period (1995–2002). L1 measurements of the radial solar wind speed are the primary basis for validation of the coronal and heliosphere models studied, though other solar wind parameters are also considered. The models are from the Center for Integrated Space-Weather Modeling (CISM) which has developed a coupled model of the whole Sun-to-Earth system, from the solar photosphere to the terrestrial thermosphere. Simple point-by-point analysis techniques, such as mean-square-error and correlation coefficients, indicate that the empirical coronal-heliosphere model currently gives the best forecast of solar wind speed at 1 AU. A more detailed analysis shows that errors in the physics-based models are predominately the result of small timing offsets to solar wind structures and that the large-scale features of the solar wind are actually well modeled. We suggest that additional “tuning” of the coupling between the coronal and heliosphere models could lead to a significant improvement of their accuracy. Furthermore, we note that the physics-based models accurately capture dynamic effects at solar wind stream interaction regions, such as magnetic field compression, flow deflection, and density buildup, which the empirical scheme cannot.