44 research outputs found

    The Boundary Multiplet of N=4 SU(2)xU(1) Gauged Supergravity on Asymptotically-AdS_5

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    We consider N=4 SU(2)xU(1) gauged supergravity on asymptotically-AdS_5 backgrounds. By a near-boundary analysis we determine the boundary-dominant components of the bulk fields from their partially gauge-fixed field equations. Subdominant components are projected out in the boundary limit and we find a reduced set of boundary fields, constituting the N=2 Weyl multiplet. The residual bulk symmetries are found to act on the boundary fields as four-dimensional diffeomorphisms, N=2 supersymmetry and (super-)Weyl transformations. This shows that the on-shell N=4 supergravity multiplet yields the N=2 Weyl multiplet on the boundary with the appropriate local N=2 superconformal transformations. Building on these results we use the AdS/CFT conjecture to calculate the Weyl anomaly of the dual four-dimensional superconformal field theories in a generic bosonic N=2 conformal supergravity background.Comment: 23 pages; to appear in JHE

    Consistent truncations of supergravity and 1/2-BPS RG flows in 4d SCFTs

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    With the purpose of holographically describing flows from a large family of four dimensional N=1{\cal N}=1 and N=2{\cal N}=2 conformal field theories, we discuss truncations of seven dimensional supergravity to five dimensions. We write explicitly the reduced gauged supergravity and find BPS equations for simple configurations. Lifting these flows to eleven dimensions or Massive IIA supergravity, we present string duals to RG flows from strongly coupled conformal theories when deformed by marginal and/or relevant operators. We further discuss observables common to infinite families of N=1{\cal N}=1 and N=2{\cal N}=2 QFTs in this context.Comment: 28 pages plus appendixes. JHEP versio

    Geophysical Monitoring Shows that Spatial Heterogeneity in Thermohydrological Dynamics Reshapes a Transitional Permafrost System

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    Climate change is causing rapid changes of Arctic ecosystems. Yet, data needed to unravel complex subsurface processes are very rare. Using geophysical and in situ sensing, this study closes an observational gap associated with thermohydrological dynamics in discontinuous permafrost systems. It highlights the impact of vegetation and snow thickness distribution on subsurface thermohydrological properties and processes. Large snow accumulation near tall shrubs insulates the ground and allows for rapid and downward heat flow. Thinner snow pack above graminoid results in surficial freezing and prevents water from infiltrating into the subsurface. Analyzing short-term disturbances, we found that lateral flow could be a driving factor in talik formation. Interannual measurements show that deep permafrost temperatures increased by about 0.2°C over 2 years. The results, which suggest that snow-vegetation-subsurface processes are tightly coupled, will be useful for improving predictions of Arctic feedback to climate change, including how subsurface thermohydrology influences CO2 and CH4 fluxes

    A hybrid data-model approach to map soil thickness in mountain hillslopes

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    Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5ĝ€¯m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods - auger and cone penetrometer - are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches
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