333,113 research outputs found

    Semileptonic decays of the Higgs boson at the Tevatron

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    We examine the prospects for extending the Tevatron reach for a Standard Model Higgs boson by including the semileptonic Higgs boson decays h --> WW --> l nu jj for M_h >~ 2 M_W, and h --> W jj --> l nu jj for M_h <~ 2 M_W, where j is a hadronic jet. We employ a realistic simulation of the signal and backgrounds using the Sherpa Monte Carlo event generator. We find kinematic selections that enhance the signal over the dominant W+jets background. The resulting sensitivity could be an important addition to ongoing searches, especially in the mass range 120 <~ M_h <~ 150 GeV. The techniques described can be extended to Higgs boson searches at the Large Hadron Collider.Comment: 68 pages, 19 figure

    EPR-B correlations: a physically tenable local-real model

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    We propose a classical, i.e., local-real physical model of processes underlying EPR experiments. The model leads to the prediction, that the visibility of the output signal will exhibit increasing variation as the coincidence window is increased, thus providing a testable criteria for its validity. If it can be sustained, this model undermines the claim that Nature has a fundamentally nonlocal feature or that irreal entities are required by quantum theory.Comment: 10 pages; latex w/ 2 figure

    Towards the timely detection of toxicants

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    We address the problem of enhancing the sensitivity of biosensors to the influence of toxicants, with an entropy method of analysis, denoted as CASSANDRA, recently invented for the specific purpose of studying non-stationary time series. We study the specific case where the toxicant is tetrodotoxin. This is a very poisonous substance that yields an abrupt drop of the rate of spike production at t approximatively 170 minutes when the concentration of toxicant is 4 nanomoles. The CASSANDRA algorithm reveals the influence of toxicants thirty minutes prior to the drop in rate at a concentration of toxicant equal to 2 nanomoles. We argue that the success of this method of analysis rests on the adoption of a new perspective of complexity, interpreted as a condition intermediate between the dynamic and the thermodynamic state.Comment: 6 pages and 3 figures. Accepted for publication in the special issue of Chaos Solitons and Fractal dedicated to the conference "Non-stationary Time Series: A Theoretical, Computational and Practical Challenge", Center for Nonlinear Science at University of North Texas, from October 13 to October 19, 2002, Denton, TX (USA

    Melt homogenization and self-organization of chalcogenides glasses: evidence of sharp rigidity, stress and nanoscale phase separation transitions in the GexSe100-x binary

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    A Raman profiling method is used to monitor growth of GexSe100-x melts and reveals a two step process of homogenization. Resulting homogeneous glasses show the non-reversing enthalpy at Tg, {\Delta}Hnr(x), to show a square-well like variation with x, with a rigidity transition near xc(1) = 19.5(5)% and stress transition near xc(2) = 26.0(5)%) representing the boundaries of the rigid but stress-free Intermediate Phase (IP). The square-well like variation of {\Delta}Hnr(x) develops sloping walls, a triangular shape and eventually disappears in glasses having an increasing heterogeneity. The {\Delta}Hnr term ages over weeks outside the IP but not inside the IP. An optical analogue of the reversibility window is observed with Raman spectra of as-quenched melts and Tg cycled glasses being the same for glass compositions in the IP but different for compositions outside the IP. Variations of Molar volumes, display three regimes of behavior with a global minimum in the IP and a pronounced increase outside that phase. The intrinsic physical behavior of dry and homogeneous chalcogenides glasses can vary sharply with composition near elastic and chemical phase transitions, showing that the physics of network glasses requires homogeneous samples, and may be far more interesting than hitherto recognized

    An integrated packet/flow model for TCP performance analysis

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    Processor sharing (PS) models for TCP behavior nicely capture the bandwidth sharing and statistical multiplexing effect of TCP flows on the flow level. However, these ‘rough’ models do not provide insight into the impact of packet-level parameters (such as round trip time and buffer size) on, e.g., throughput and flow transfer times. This paper proposes an integrated packet/flow-level model: it exploits the advantages of PS approach on the flow level and, at the same time, it incorporates the most significant packet-level effects
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