589 research outputs found

    L-band Microwave Remote Sensing and Land Data Assimilation Improve the Representation of Prestorm Soil Moisture Conditions for Hydrologic Forecasting

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    Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events

    Exploiting Soil Moisture, Precipitation and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

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    Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltrationexcess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturationexcess runoff generation processes

    Long-lived qubit memory using atomic ions

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    We demonstrate experimentally a robust quantum memory using a magnetic-field-independent hyperfine transition in 9Be+ atomic ion qubits at a magnetic field B ~= 0.01194 T. We observe that the single physical qubit memory coherence time is greater than 10 seconds, an improvement of approximately five orders of magnitude from previous experiments with 9Be+. We also observe long coherence times of decoherence-free subspace logical qubits comprising two entangled physical qubits and discuss the merits of each type of qubit.Comment: 5 pages, 4 figure

    Quantum control, quantum information processing, and quantum-limited metrology with trapped ions

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    We briefly discuss recent experiments on quantum information processing using trapped ions at NIST. A central theme of this work has been to increase our capabilities in terms of quantum computing protocols, but we have also applied the same concepts to improved metrology, particularly in the area of frequency standards and atomic clocks. Such work may eventually shed light on more fundamental issues, such as the quantum measurement problem.Comment: Proceedings of the International Conference on Laser Spectroscopy (ICOLS), 10 pages, 5 figure

    Path Selection for Quantum Repeater Networks

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    Quantum networks will support long-distance quantum key distribution (QKD) and distributed quantum computation, and are an active area of both experimental and theoretical research. Here, we present an analysis of topologically complex networks of quantum repeaters composed of heterogeneous links. Quantum networks have fundamental behavioral differences from classical networks; the delicacy of quantum states makes a practical path selection algorithm imperative, but classical notions of resource utilization are not directly applicable, rendering known path selection mechanisms inadequate. To adapt Dijkstra's algorithm for quantum repeater networks that generate entangled Bell pairs, we quantify the key differences and define a link cost metric, seconds per Bell pair of a particular fidelity, where a single Bell pair is the resource consumed to perform one quantum teleportation. Simulations that include both the physical interactions and the extensive classical messaging confirm that Dijkstra's algorithm works well in a quantum context. Simulating about three hundred heterogeneous paths, comparing our path cost and the total work along the path gives a coefficient of determination of 0.88 or better.Comment: 12 pages, 8 figure

    Principles of Modular Tumor Therapy

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    Nature is interwoven with communication and is represented and reproduced through communication acts. The central question is how may multimodal modularly acting and less toxic therapy approaches, defined as modular therapies, induce an objective response or even a continuous complete remission, although single stimulatory or inhibitingly acting drugs neither exert mono-activity in the respective metastatic tumor type nor are they directed to potentially ‘tumor-specific’ targets. Modularity in the present context is a formal pragmatic communicative systems concept, describing the degree to which systems objects (cells, pathways etc.) may be communicatively separated in a virtual continuum, and recombined and rededicated to alter validity and denotation of communication processes in the tumor. Intentional knowledge, discharging in reductionist therapies, disregards the risk-absorbing background knowledge of the tumor’s living world including the holistic communication processes, which we rely on in every therapy. At first, this knowledge constitutes the validity of informative intercellular processes, which is the prerequisite for therapeutic success. All communication-relevant steps, such as intentions, understandings, and the appreciation of messages, may be modulated simultaneously, even with a high grade of specificity. Thus, modular therapy approaches including risk-absorbing and validity-modifying background knowledge may overcome reductionist idealizations. Modular therapies show modular events assembled by the tumor’s living world as an additional evolution-constituting dimension. This way, modular knowledge may be acquired from the environment, either incidentally or constitutionally. The new communicatively defined modular coherency of environment, i.e. the tumor-associated microenvironment, and tumor cells open novel ways for the scientific community in ‘translational medicine’

    Raman spectroscopy of a single ion coupled to a high-finesse cavity

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    We describe an ion-based cavity-QED system in which the internal dynamics of an atom is coupled to the modes of an optical cavity by vacuum-stimulated Raman transitions. We observe Raman spectra for different excitation polarizations and find quantitative agreement with theoretical simulations. Residual motion of the ion introduces motional sidebands in the Raman spectrum and leads to ion delocalization. The system offers prospects for cavity-assisted resolved-sideband ground-state cooling and coherent manipulation of ions and photons.Comment: 8 pages, 6 figure

    Effects of syntactic context on eye movements during reading

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    Previous research has demonstrated that properties of a currently fixated word and of adjacent words influence eye movement control in reading. In contrast to such local effects, little is known about the global effects on eye movement control, for example global adjustments caused by processing difficulty of previous sentences. In the present study, participants read text passages in which voice (active vs. passive) and sentence structure (embedded vs. non-embedded) were manipulated. These passages were followed by identical target sentences. The results revealed effects of previous sentence structure on gaze durations in the target sentence, implying that syntactic properties of previously read sentences may lead to a global adjustment of eye movement control

    PEAT-CLSM : A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model

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    Peatlands are poorly represented in global Earth system modeling frameworks. Here we add a peatland-specific land surface hydrology module (PEAT-CLSM) to the Catchment Land Surface Model (CLSM) of the NASA Goddard Earth Observing System (GEOS) framework. The amended TOPMODEL approach of the original CLSM that uses topography characteristics to model catchment processes is discarded, and a peatland-specific model concept is realized in its place. To facilitate its utilization in operational GEOS efforts, PEAT-CLSM uses the basic structure of CLSM and the same global input data. Parameters used in PEAT-CLSM are based on literature data. A suite of CLSM and PEAT-CLSM simulations for peatland areas between 40 degrees N and 75 degrees N is presented and evaluated against a newly compiled data set of groundwater table depth and eddy covariance observations of latent and sensible heat fluxes in natural and seminatural peatlands. CLSM's simulated groundwater tables are too deep and variable, whereas PEAT-CLSM simulates a mean groundwater table depth of -0.20 m (snow-free unfrozen period) with moderate temporal fluctuations (standard deviation of 0.10 m), in significantly better agreement with in situ observations. Relative to an operational CLSM version that simply includes peat as a soil class, the temporal correlation coefficient is increased on average by 0.16 and reaches 0.64 for bogs and 0.66 for fens when driven with global atmospheric forcing data. In PEAT-CLSM, runoff is increased on average by 38% and evapotranspiration is reduced by 19%. The evapotranspiration reduction constitutes a significant improvement relative to eddy covariance measurements.Peer reviewe
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