4,874 research outputs found

    Upgrade of the protection system for superconducting circuits in the LHC

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    Prior to the re-start of the Large Hadron Collider LHC in 2009 the protection system for superconducting magnets and bus-bars QPS will be substantially upgraded. The foreseen modifications will enhance the capability of the system in detecting problems related to the electrical interconnections between superconducting magnets as well as the detection of so-called aperture symmetric quenches in the LHC main magnets

    Competing Ultrafast Energy Relaxation Pathways in Photoexcited Graphene

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    For most optoelectronic applications of graphene a thorough understanding of the processes that govern energy relaxation of photoexcited carriers is essential. The ultrafast energy relaxation in graphene occurs through two competing pathways: carrier-carrier scattering -- creating an elevated carrier temperature -- and optical phonon emission. At present, it is not clear what determines the dominating relaxation pathway. Here we reach a unifying picture of the ultrafast energy relaxation by investigating the terahertz photoconductivity, while varying the Fermi energy, photon energy, and fluence over a wide range. We find that sufficiently low fluence (≲\lesssim 4 μ\muJ/cm2^2) in conjunction with sufficiently high Fermi energy (≳\gtrsim 0.1 eV) gives rise to energy relaxation that is dominated by carrier-carrier scattering, which leads to efficient carrier heating. Upon increasing the fluence or decreasing the Fermi energy, the carrier heating efficiency decreases, presumably due to energy relaxation that becomes increasingly dominated by phonon emission. Carrier heating through carrier-carrier scattering accounts for the negative photoconductivity for doped graphene observed at terahertz frequencies. We present a simple model that reproduces the data for a wide range of Fermi levels and excitation energies, and allows us to qualitatively assess how the branching ratio between the two distinct relaxation pathways depends on excitation fluence and Fermi energy.Comment: Nano Letters 201

    Photoconductivity of biased graphene

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    Graphene is a promising candidate for optoelectronic applications such as photodetectors, terahertz imagers, and plasmonic devices. The origin of photoresponse in graphene junctions has been studied extensively and is attributed to either thermoelectric or photovoltaic effects. In addition, hot carrier transport and carrier multiplication are thought to play an important role. Here we report the intrinsic photoresponse in biased but otherwise homogeneous graphene. In this classic photoconductivity experiment, the thermoelectric effects are insignificant. Instead, the photovoltaic and a photo-induced bolometric effect dominate the photoresponse due to hot photocarrier generation and subsequent lattice heating through electron-phonon cooling channels respectively. The measured photocurrent displays polarity reversal as it alternates between these two mechanisms in a backgate voltage sweep. Our analysis yields elevated electron and phonon temperatures, with the former an order higher than the latter, confirming that hot electrons drive the photovoltaic response of homogeneous graphene near the Dirac point

    Effect of low perceived social support on health outcomes in young patients with acute myocardial infarction: results from the VIRGO (variation in recovery: role of gender on outcomes of young AMI patients) study

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    Background: Social support is an important predictor of health outcomes after acute myocardial infarction (AMI), but social support varies by sex and age. Differences in social support could account for sex differences in outcomes of young patients with AMI. Methods and Results: Data from the Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients (VIRGO) study, an observational study of AMI patients aged ≤55 years in the United States and Spain, were used for this study. Patients were categorized as having low versus moderate/high perceived social support using the ENRICHD Social Support Inventory. Outcomes included health status (Short Form-12 physical and mental component scores), depressive symptoms (Patient Health Questionnaire), and angina-related quality of life (Seattle Angina Questionnaire) evaluated at baseline and 12 months. Among 3432 patients, 21.2% were classified as having low social support. Men and women had comparable levels of social support at baseline. On average, patients with low social support reported lower functional status and quality of life and more depressive symptoms at baseline and 12 months post-AMI. After multivariable adjustment, including baseline health status, low social support was associated with lower mental functioning, lower quality of life, and more depressive symptoms at 12 months (all P<0.001). The relationship between low social support and worse physical functioning was nonsignificant after adjustment (P=0.6). No interactions were observed between social support, sex, or country. Conclusion: Lower social support is associated with worse health status and more depressive symptoms 12 months after AMI in both young men and women. Sex did not modify the effect of social support.Emily M. Bucholz, Kelly M. Strait, Rachel P. Dreyer, Mary Geda, Erica S. Spatz, Hector Bueno, Judith H. Lichtman, Gail D'Onofrio, John A. Spertus, Harlan M. Krumhol

    Bayesian Learning of Gas Transport in Three-Dimensional Fracture Networks

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    Modeling gas flow through fractures of subsurface rock is a particularly challenging problem because of the heterogeneous nature of the material. High-fidelity simulations using discrete fracture network (DFN) models are one methodology for predicting gas particle breakthrough times at the surface, but are computationally demanding. We propose a Bayesian machine learning method that serves as an efficient surrogate model, or emulator, for these three-dimensional DFN simulations. Our model trains on a small quantity of simulation data and, using a graph/path-based decomposition of the fracture network, rapidly predicts quantiles of the breakthrough time distribution. The approach, based on Gaussian Process Regression (GPR), outputs predictions that are within 20-30% of high-fidelity DFN simulation results. Unlike previously proposed methods, it also provides uncertainty quantification, outputting confidence intervals that are essential given the uncertainty inherent in subsurface modeling. Our trained model runs within a fraction of a second, which is considerably faster than other methods with comparable accuracy and multiple orders of magnitude faster than high-fidelity simulations

    An improved measurement of muon antineutrino disappearance in MINOS

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    We report an improved measurement of muon anti-neutrino disappearance over a distance of 735km using the MINOS detectors and the Fermilab Main Injector neutrino beam in a muon anti-neutrino enhanced configuration. From a total exposure of 2.95e20 protons on target, of which 42% have not been previously analyzed, we make the most precise measurement of the anti-neutrino "atmospheric" delta-m squared = 2.62 +0.31/-0.28 (stat.) +/- 0.09 (syst.) and constrain the anti-neutrino atmospheric mixing angle >0.75 (90%CL). These values are in agreement with those measured for muon neutrinos, removing the tension reported previously.Comment: 5 pages, 4 figures. In submission to Phys.Rev.Let
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