184,460 research outputs found

    Power Spectrum of Cosmic Momentum Field Measured from the SFI Galaxy Sample

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    We have measured the cosmic momentum power spectrum from the peculiar velocities of galaxies in the SFI sample. The SFI catalog contains field spiral galaxies with radial peculiar velocities derived from the I-band Tully-Fisher relation. As a natural measure of the large-scale peculiar velocity field, we use the cosmic momentum field that is defined as the peculiar velocity field weighted by local number of galaxies. We have shown that the momentum power spectrum can be derived from the density power spectrum for the constant linear biasing of galaxy formation, which makes it possible to estimate \beta_S = \Omega_m^{0.6} / b_S parameter precisely where \Omega_m is the matter density parameter and b_S is the bias factor for optical spiral galaxies. At each wavenumber k we estimate \beta_S(k) as the ratio of the measured to the derived momentum power over a wide range of scales (0.026 h^{-1}Mpc <~ k <~ 0.157 h^{-1}Mpc) that spans the linear to the quasi-linear regimes. The estimated \beta_S(k)'s have stable values around 0.5, which demonstrates the constancy of \beta_S parameter at scales down to 40 h^{-1}Mpc. We have obtained \beta_S=0.49_{-0.05}^{+0.08} or \Omega_m = 0.30_{-0.05}^{+0.09} b_S^{5/3}, and the amplitude of mass fluctuation as \sigma_8\Omega_m^{0.6}=0.56_{-0.21}^{+0.27}. The 68% confidence limits include the cosmic variance. We have also estimated the mass density power spectrum. For example, at k=0.1047 h Mpc^{-1} (\lambda=60 h^{-1}Mpc) we measure \Omega_m^{1.2} P_{\delta}(k)=(2.51_{-0.94}^{+0.91})\times 10^3 (h^{-1}Mpc)^3, which is lower compared to the high-amplitude power spectra found from the previous maximum likelihood analyses of peculiar velocity samples like Mark III, SFI, and ENEAR.Comment: 12 pages, 9 figures, accepted for publication in Ap

    Will anyone vote? Prospects for turnout in the general election

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    One of the most notable features of the last two general elections was the low level of turnout. Before 2001 turnout at general elections was always at least 70% (and often far higher). But in 2001 it fell to just 59% and, at 61%, the figure in 2005 was little better. Over 17 million people eligible to vote that year chose not to do so, seven million more than voted for the winning Labour party. Britain found itself almost at the bottom of the turnout league among established European democracies. The failure of large sections of the public to go to the polls has led to considerable concern about the health of Britainā€™s democracy and stimulated many a suggestion as to how the countryā€™s politicians might be able to reconnect with the electorate

    Herding and Contrarian Behavior in Financial Markets: An Experimental Analysis

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    We are the first paper to analyse and confirm the existence and extent of rational informational herding and rational informational contrarianism in a financial market experiment, and to compare and contrast these with the equivalent irrational phenomena. In our study, subjects generally behaved according to benchmark rationality. Moreover, traders who should herd or be contrarian in theory are the significant source of both. Behavioural modifications or allowing risk aversion add little to performance and insight. JEL Classification: C91, D82, G14

    Fermi Gamma Ray Line at 130 GeV from Axion-Mediated Dark Matter

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    We consider a singlet Dirac fermion with Peccei-Quinn(PQ) symmetry as dark matter. A singlet complex scalar is introduced to mediate between dark matter and the SM through Higgs portal interaction and electroweak PQ anomalies. We show that a resonant annihilation of dark matter with axion mediation can explain the monochromatic photon line of the Fermi LAT data at 130 GeV by anomaly interactions while the annihilation cross section with Higgs portal interaction is p-wave suppressed. We discuss the interplay between the direct detection of the fermion dark matter and the collider search of Higgs-like scalars. We also present a ultra-violet completion of the dark matter model into the NMSSM with PQ symmetry.Comment: 22 pages, 9 figures, To be published in Phys. Rev.

    Spinning strings in AdS_5 x S^5: one-loop correction to energy in SL(2) sector

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    We consider a circular string with spin SS in AdS5AdS_5 wrapped around big circle of S5S^5 and carrying also momentum JJ. The corresponding N=4 SYM operator belongs to the SL(2) sector, i.e. has tr(DSZJ)+...(D^S Z^J)+... structure. The leading large JJ term in its 1-loop anomalous dimension can be computed using Bethe ansatz for the SL(2) spin chain and was previously found to match the leading term in the classical string energy. The string solution is stable at large JJ, and the Lagrangian for string fluctuations has constant coefficients, so that the 1-loop string correction to the energy E1E_1 is given simply by the sum of characteristic frequencies. Curiously, we find that the leading term in the zero-mode part of E1E_1 is the same as a 1/J correction to the one-loop anomalous dimension on the gauge theory (spin chain) side that was found in hep-th/0410105. However, the contribution of non-zero string modes does not vanish. We also discuss the ``fast string'' expansion of the classical string action which coincides with the coherent state action of the SL(2) spin chain at the first order in \l, and extend this expansion to higher orders clarifying the role of the S5S^5 winding number.Comment: 31 pages, 1 figure, latex; v3: minor changes and correction

    FORECAST EVALUATION FOR MULTIVARIATE TIME-SERIES MODELS: THE U.S. CATTLE MARKET

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    A set of rigorous diagnostic techniques is used to evaluate the forecasting performance of five multivariate time-series models for the U.S. cattle sector. The root-mean-squared-error criterion along with an evaluation of the rankings of forecast errors reveals that the Bayesian vector autoregression (BVAR) and the unrestricted VAR (UVAR) models generate forecasts which are superior to both a restricted VAR (RVAR) and a vector autoregressive moving-average (VARMA) model. Two methods for calculating a test evaluating the ability to forecast directional changes are implemented. The BVAR models and the UVAR model unambiguously outperform the VARMA model in the forecasting directional changeLivestock Production/Industries,
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