113 research outputs found

    Aerodynamic Sensing for a Fixed Wing UAS Operating at High Angles of Attack

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97104/1/AIAA2012-4416.pd

    A self-consistent phase-space distribution function for the anisotropic dark matter halo of the Milky Way

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    Dark Matter (DM) direct detection experiments usually assume the simplest possible ‘Standard Halo Model’ for the Milky Way (MW) halo in which the velocity distribution is Maxwellian. This model assumes that the MW halo is an isotropic, isothermal sphere, hypotheses that are unlikely to be valid in reality. An alternative approach is to derive a self-consistent solution for a particular mass model of the MW (i.e. obtained from its gravitational potential) using the Eddington formalism, which assumes isotropy. In this paper we extend this approach to incorporate an anisotropic phase-space distribution function. We perform Bayesian scans over the parameters defining the mass model of the MW and parameterising the phase-space density, implementing constraints from a wide range of astronomical observations. The scans allow us to estimate the precision reached in the reconstruction of the velocity distribution (for different DM halo profiles). As expected, allowing for an anisotropic velocity tensor increases the uncertainty in the reconstruction of f (v), but the distribution can still be determined with a precision of a factor of 4-5. The mean velocity distribution resembles the isotropic case, however the amplitude of the high-velocity tail is up to a factor of 2 larger. Our results agree with the phenomenological parametrization proposed in Mao et al. (2013) as a good fit to N-body simulations (with or without baryons), since their velocity distribution is contained in our 68% credible interval

    Event Texture Search for Phase Transitions in Pb+Pb Collisions

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    NA44 uses a 512 channel Si pad array covering 1.5<η<3.31.5 <\eta < 3.3 to study charged hadron production in 158 A GeV Pb+Pb collisions at the CERN SPS. We apply a multiresolution analysis, based on a Discrete Wavelet Transformation, to probe the texture of particle distributions event-by-event, allowing simultaneous localization of features in space and scale. Scanning a broad range of multiplicities, we search for signals of clustering and of critical behavior in the power spectra of local density fluctuations. The data are compared with detailed simulations of detector response, using heavy ion event generators, and with a reference sample created via event mixing. An upper limit is set on the probability and magnitude of dynamical fluctuations
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