1,891 research outputs found

    Statistics of level spacing of geometric resonances in random binary composites

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    We study the statistics of level spacing of geometric resonances in the disordered binary networks. For a definite concentration pp within the interval [0.2,0.7][0.2,0.7], numerical calculations indicate that the unfolded level spacing distribution P(t)P(t) and level number variance Σ2(L)\Sigma^2(L) have the general features. It is also shown that the short-range fluctuation P(t)P(t) and long-range spectral correlation Σ2(L)\Sigma^2(L) lie between the profiles of the Poisson ensemble and Gaussion orthogonal ensemble (GOE). At the percolation threshold pcp_c, crossover behavior of functions P(t)P(t) and % \Sigma^2(L) is obtained, giving the finite size scaling of mean level spacing δ\delta and mean level number nn, which obey the scaling laws, % \delta=1.032 L ^{-1.952} and n=0.911L1.970n=0.911L^{1.970}.Comment: 11 pages, 7 figures,submitted to Phys. Rev.

    Screening of Dirac flavor structure in the seesaw and neutrino mixing

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    We consider the mechanism of screening of the Dirac flavor structure in the context of the double seesaw mechanism. As a consequence of screening, the structure of the light neutrino mass matrix, m_\nu, is determined essentially by the structure of the (Majorana) mass matrix, M_S, of new super-heavy (Planck scale) neutral fermions S. We calculate effects of the renormalization group running in order to investigate the stability of the screening mechanism with respect to radiative corrections. We find that screening is stable in the supersymmetric case, whereas in the standard model it is unstable for certain structures of M_S. The screening mechanism allows us to reconcile the (approximate) quark-lepton symmetry and the strong difference of the mixing patterns in the quark and lepton sectors. It opens new possibilities to explain a quasi-degenerate neutrino mass spectrum, special ``neutrino'' symmetries and quark-lepton complementarity. Screening can emerge from certain flavor symmetries or Grand Unification.Comment: 27 pages, 3 figures; references added, discussion of the E6 model modifie

    The Three Families from SU(4)ASU(3)CSU(2)LU(1)XSU(4)_A\otimes SU(3)_C\otimes SU(2)_L\otimes U(1)_X SM-like Chiral Models

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    We give a detailed description of the model construction procedures about our new approach to the family structure of the standard model. SM-like chiral fermion spectra, largely "derivable" from the gauge anomaly constraints, are formulated in a SU(N)SU(3)SU(2)U(1)SU(N)\otimes SU(3)\otimes SU(2)\otimes U(1) symmetry framework as an extension of the SM symmetry. The N=4N=4 case gives naturally three families as a result, with U(1)YU(1)_Y nontrivially embedded into the SU(4)AU(1)XSU(4)_A\otimes U(1)_X. Such a spectrum has extra vector-like quarks and leptons. We illustrate how an acceptable symmetry breaking pattern can be obtained through a relatively simple scalar sector which gives naturally hierarchical quark mass matrices. Compatibility with various FCNC constraints and some interesting aspects of the possible phenomenological features are discussed, from a non-model specific perspective. The question of incorporating supersymmetry without putting in the Higgses as extra supermultiplet is also addressed.Comment: 43 pages RevTex, including 9 tables and 3 figure

    The effects of the bacterial interaction with visible-light responsive titania photocatalyst on the bactericidal performance

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    Bactericidal activity of traditional titanium dioxide (TiO2) photocatalyst is effective only upon irradiation by ultraviolet light, which restricts the potential applications of TiO2 for use in our living environments. Recently carbon-containing TiO2 was found to be photoactive at visible-light illumination that affords the potential to overcome this problem; although, the bactericidal activity of these photocatalysts is relatively lower than conventional disinfectants. Evidenced from scanning electron microscopy and confocal Raman spectral mapping analysis, we found the interaction with bacteria was significantly enhanced in these anatase/rutile mixed-phase carbon-containing TiO2. Bacteria-killing experiments indicate that a significantly higher proportion of all tested pathogens including Staphylococcus aureus, Shigella flexneri and Acinetobacter baumannii, were eliminated by the new nanoparticle with higher bacterial interaction property. These findings suggest the created materials with high bacterial interaction ability might be a useful strategy to improve the antimicrobial activity of visible-light-activated TiO2

    Effects of decoherence and errors on Bell-inequality violation

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    We study optimal conditions for violation of the Clauser-Horne-Shimony-Holt form of the Bell inequality in the presence of decoherence and measurement errors. We obtain all detector configurations providing the maximal Bell inequality violation for a general (pure or mixed) state. We consider local decoherence which includes energy relaxation at the zero temperature and arbitrary dephasing. Conditions for the maximal Bell-inequality violation in the presence of decoherence are analyzed both analytically and numerically for the general case and for a number of important special cases. Combined effects of measurement errors and decoherence are also discussed.Comment: 18 pages, 5 figure

    Deconfining Phase Transition as a Matrix Model of Renormalized Polyakov Loops

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    We discuss how to extract renormalized from bare Polyakov loops in SU(N) lattice gauge theories at nonzero temperature in four spacetime dimensions. Single loops in an irreducible representation are multiplicatively renormalized without mixing, through a renormalization constant which depends upon both representation and temperature. The values of renormalized loops in the four lowest representations of SU(3) were measured numerically on small, coarse lattices. We find that in magnitude, condensates for the sextet and octet loops are approximately the square of the triplet loop. This agrees with a large NN expansion, where factorization implies that the expectation values of loops in adjoint and higher representations are just powers of fundamental and anti-fundamental loops. For three colors, numerically the corrections to the large NN relations are greatest for the sextet loop, 25\leq 25%; these represent corrections of 1/N\sim 1/N for N=3. The values of the renormalized triplet loop can be described by an SU(3) matrix model, with an effective action dominated by the triplet loop. In several ways, the deconfining phase transition for N=3 appears to be like that in the N=N=\infty matrix model of Gross and Witten.Comment: 24 pages, 7 figures; v2, 27 pages, 12 figures, extended discussion for clarity, results unchange

    Predictive ability of logistic regression, auto-logistic regression and neural network models in empirical land-use change modeling: a case study

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    The objective of this study is to compare the abilities of logistic, auto-logistic and artificial neural network (ANN) models for quantifying the relationships between land uses and their drivers. In addition, the application of the results obtained by the three techniques is tested in a dynamic land-use change model (CLUE-s) for the Paochiao watershed region in Taiwan. Relative operating characteristic curves (ROCs), kappa statistics, multiple resolution validation and landscape metrics were used to assess the ability of the three techniques in estimating the relationship between driving factors and land use and its subsequent application in land-use change models. The validation results illustrate that for this case study ANNs constitute a powerful alternative for the use of logistic regression in empirical modeling of spatial land-use change processes. ANNs provide in this case a better fit between driving factors and land-use pattern. In addition, auto-logistic regression performs better than logistic regression and nearly as well as ANNs. Auto-logistic regression and ANNs are considered especially useful when the performance of more conventional models is not satisfactory or the underlying data relationships are unknown. The results indicate that an evaluation of alternative techniques to specify relationships between driving factors and land use can improve the performance of land-use change models
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