SU(3) mass-splittings of heavy-baryons in QCD

We extract directly (for the first time) the charmed (C = 1) and bottom (B = -1) heavy-baryons (spin 1/2 and 3/2) mass-splittings due to SU(3) breaking using double ratios of QCD spectral sum rules (QSSR) in full QCD, which are less sensitive to the exact value and definition of the heavy quark mass, to the perturbative radiative corrections and to the QCD continuum contributions than the simple ratios commonly used for determining the heavy baryon masses. Noticing that most of the mass-splittings are mainly controlled by the ratio kappa <(S) over bars >/<(d) over bard > of the condensate, we extract this ratio, by allowing 1 sigma deviation from the observed masses of the Xi(c.b) and of the Omega(c). We obtain: kappa = 0.74(3), which improves the existing estimates: kappa = 0.70(10) from light hadrons. Using this value, we deduce M(Omega b) = 6078.5(27.4) MeV which agrees with the recent CDF data but disagrees by 2.4 sigma with the one from D0. Predictions of the Xi(Q)` and of the spectra of spin 3/2 baryons containing one or two strange quark are given in Table 2. Predictions of the hyperfine splittings Omega(Q)* - Omega(Q) and Xi(Q)* - Xi(Q) are also given in Table 3. Starting for a general choice of the interpolating currents for the spin 1/2 baryons, our analysis favours the optimal value of the mixing angle b similar or equal to (-1/5-0) found from light and non-strange heavy baryons. (C) 2010 Elsevier B.V. All rights reserved.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.