153,357 research outputs found

    Quark Model Study of The eta Photoproduction: Evidence for a New S11 Resonance?

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    An extensive and systematic study of the recent eta photoproduction data up to 1.2 GeV is presented within a chiral constituent quark model. A model embodying all known nucleonic resonances shows clear need for a yet undiscovered third S11 resonance in the second resonance region, for which we determine the mass (1.729 GeV) and the total width (183 MeV). Furthermore, we extract the configuration mixing angles, an important property of the quark-quark interaction in the quark model, for the resonances S11(1535) and S11(1650), as well as for the resonances D13(1520) and D13(1700). Our results agree well with the quark model predictions. In addition, the partial eta N decay widths and/or the photo-excitation helicity amplitudes for the nucleonic resonances S11(1535), S11(1650), P11(1710), P13(1720), D13(1520), D13(1700), D15(1675), and F15(1680) are also obtained in this approach.Comment: 25 pages, 5 figures, submitted to Eur. Phys.

    Critical exponents of the two-layer Ising model

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    The symmetric two-layer Ising model (TLIM) is studied by the corner transfer matrix renormalisation group method. The critical points and critical exponents are calculated. It is found that the TLIM belongs to the same universality class as the Ising model. The shift exponent is calculated to be 1.773, which is consistent with the theoretical prediction 1.75 with 1.3% deviation.Comment: 7 pages, with 10 figures include

    Dynamic Monte Carlo Study of the Two-Dimensional Quantum XY Model

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    We present a dynamic Monte Carlo study of the Kosterlitz-Thouless phase transition for the spin-1/2 quantum XY model in two dimensions. The short-time dynamic scaling behaviour is found and the dynamical exponent θ\theta, zz and the static exponent η\eta are determined at the transition temperature.Comment: 6 pages with 3 figure

    Probability-dependent gain-scheduled filtering for stochastic systems with missing measurements

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    Copyright @ 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This brief addresses the gain-scheduled filtering problem for a class of discrete-time systems with missing measurements, nonlinear disturbances, and external stochastic noise. The missing-measurement phenomenon is assumed to occur in a random way, and the missing probability is time-varying with securable upper and lower bounds that can be measured in real time. The multiplicative noise is a state-dependent scalar Gaussian white-noise sequence with known variance. The addressed gain-scheduled filtering problem is concerned with the design of a filter such that, for the admissible random missing measurements, nonlinear parameters, and external noise disturbances, the error dynamics is exponentially mean-square stable. The desired filter is equipped with time-varying gains based primarily on the time-varying missing probability and is therefore less conservative than the traditional filter with fixed gains. It is shown that the filter parameters can be derived in terms of the measurable probability via the semidefinite program method.This work was supported in part by the Leverhulme Trust of the U.K., the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the National Natural Science Foundation of China under Grants 61028008, 61074016 and 60974030, the Shanghai Natural Science Foundation of China under Grant 10ZR1421200, and the Alexander von Humboldt Foundation of Germany
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