860 research outputs found

    qq-Classical orthogonal polynomials: A general difference calculus approach

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    It is well known that the classical families of orthogonal polynomials are characterized as eigenfunctions of a second order linear differential/difference operator. In this paper we present a study of classical orthogonal polynomials in a more general context by using the differential (or difference) calculus and Operator Theory. In such a way we obtain a unified representation of them. Furthermore, some well known results related to the Rodrigues operator are deduced. A more general characterization Theorem that the one given in [1] and [2] for the q-polynomials of the q-Askey and Hahn Tableaux, respectively, is established. Finally, the families of Askey-Wilson polynomials, q-Racah polynomials, Al-Salam & Carlitz I and II, and q-Meixner are considered. [1] R. Alvarez-Nodarse. On characterization of classical polynomials. J. Comput. Appl. Math., 196:320{337, 2006. [2] M. Alfaro and R. Alvarez-Nodarse. A characterization of the classical orthogonal discrete and q-polynomials. J. Comput. Appl. Math., 2006. In press.Comment: 18 page

    Mesoscopic proximity effect in double barrier Superconductor/Normal Metal junctions

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    We report transport measurements down to T=60mK of SININ and SNIN structures in the diffusive limit. We fabricated Al-AlOx/Cu/AlOx/Cu (SININ) and Al/Cu/AlOx/Cu (SNIN) vertical junctions. For the first time, a zero bias anomaly was observed in a metallic SININ structure. We attribute this peak of conductance to coherent multi-reflections of electrons between the two tunnel barriers. This conductance maximum is quantitatively fitted by the relevant theory of mesoscopic SININ structures. When the barrier at the SN interface is removed (SNIN structure), we observe a peak of conductance at finite voltage accompagnied by an excess of sub-gap conductance.Comment: 4 pages, 4 figures, editorially approved for publication in Phys. Rev. B Rapid Com

    Complete Hydrogen Storage System by ISRU

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    New technologies make it possible to build in space a complete hydrogen storage system using ISRU methods and techniques. Hydrogen can be stored in a solid-state form on the surface atoms of high surface area matrices such as those of porous silicon. Silicon is abundant in regolith and can be purified using a purely mechanical means which results in particulates in the scale range of tens of nanometers. Reagents used to porosify these nano-particles can be regenerated thermally to essentially eliminate the need for resupply from earth. Catalysts are needed to divide dihydrogen gas into atomic hydrogen for solid-state adsorption and to mediate the temperatures and pressures of charge and discharge into ranges easily achievable with simple equipment. Recent research has identified the utility of non-platinum group catalyst materials which are widespread on the moon. Rapid discharge, needed for propulsion, is possible with infra-red illumination at wavelengths which pass through pure silicon but are absorbed by the silicon-hydrogen bond. Such IR emitters can be fabricated by embossing of silica and additive manufacturing of metals. Control and power electronics can be fabricated using a patented process designed for space operations, and built on either silicon or silicon carbide substrates derived from regolith. Bringing these five technologies together for the first time allows a system which can be fed with moderate pressure gaseous hydrogen at moderate temperatures, stored for long durations with minimum loss, then released upon demand across a wide range of controllable rates. Such a system can displace the need for cryogenic hydrogen storage. Being suitable to bottom-up fabrication using only in-space materials makes this a “green” ISRU technology to store hydrogen for fuel cells, rocket engines, and chemical processes

    Global Search for New Physics with 2.0/fb at CDF

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    Data collected in Run II of the Fermilab Tevatron are searched for indications of new electroweak-scale physics. Rather than focusing on particular new physics scenarios, CDF data are analyzed for discrepancies with the standard model prediction. A model-independent approach (Vista) considers gross features of the data, and is sensitive to new large cross-section physics. Further sensitivity to new physics is provided by two additional algorithms: a Bump Hunter searches invariant mass distributions for "bumps" that could indicate resonant production of new particles; and the Sleuth procedure scans for data excesses at large summed transverse momentum. This combined global search for new physics in 2.0/fb of ppbar collisions at sqrt(s)=1.96 TeV reveals no indication of physics beyond the standard model.Comment: 8 pages, 7 figures. Final version which appeared in Physical Review D Rapid Communication

    Observation of Orbitally Excited B_s Mesons

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    We report the first observation of two narrow resonances consistent with states of orbitally excited (L=1) B_s mesons using 1 fb^{-1} of ppbar collisions at sqrt{s} = 1.96 TeV collected with the CDF II detector at the Fermilab Tevatron. We use two-body decays into K^- and B^+ mesons reconstructed as B^+ \to J/\psi K^+, J/\psi \to \mu^+ \mu^- or B^+ \to \bar{D}^0 \pi^+, \bar{D}^0 \to K^+ \pi^-. We deduce the masses of the two states to be m(B_{s1}) = 5829.4 +- 0.7 MeV/c^2 and m(B_{s2}^*) = 5839.7 +- 0.7 MeV/c^2.Comment: Version accepted and published by Phys. Rev. Let

    A FORTRAN code for γγZZ\gamma \gamma \to Z Z in SM and MSSM

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    Through the present paper, the code gamgamZZ is presented, which may be used to calculate all possible observables related to the process γγZZ\gamma \gamma \to ZZ, in either the Standard Model (SM), or the minimal sypersymmetric standard model (MSSM) with real parameters.Comment: 13 pages, 7 figures Revised according to the EPJC Referee suggestion

    Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

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    Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization
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