27,496 research outputs found

    Model Study of Three-Body Forces in the Three-Body Bound State

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    The Faddeev equations for the three-body bound state with two- and three-body forces are solved directly as three-dimensional integral equation. The numerical feasibility and stability of the algorithm, which does not employ partial wave decomposition is demonstrated. The three-body binding energy and the full wave function are calculated with Malfliet-Tjon-type two-body potentials and scalar Fujita-Miyazawa type three-body forces. The influence of the strength and range of the three-body force on the wave function, single particle momentum distributions and the two-body correlation functions are studied in detail. The extreme case of pure three-body forces is investigated as well.Comment: 25 pages, 15 postscript figure

    Three-Body Scattering without Partial Waves

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    The Faddeev equation for three-body scattering at arbitrary energies is formulated in momentum space and directly solved in terms of momentum vectors without employing a partial wave decomposition. In its simplest form the Faddeev equation for identical bosons is a three-dimensional integral equation in five variables, magnitudes of relative momenta and angles. The elastic differential cross section, semi-exclusive d(N,N') cross sections and total cross sections of both elastic and breakup processes in the intermediate energy range up to about 1 GeV are calculated based on a Malfliet-Tjon type potential, and the convergence of the multiple scattering series is investigated in every case. In general a truncation in the first or second order in the two-body t-matrix is quite insufficient.Comment: 3 pages, Oral Contribution to the 19th European Few-Body Conference, Groningen Aug. 23-27, 200

    Three-Body Elastic and Inelastic Scattering at Intermediate Energies

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    The Faddeev equation for three-body scattering at arbitrary energies is formulated in momentum space and directly solved in terms of momentum vectors without employing a partial wave decomposition. For identical bosons this results in a three-dimensional integral equation in five variables, magnitudes of relative momenta and angles. The cross sections for both elastic and breakup processes in the intermediate energy range up to about 1 GeV are calculated based on a Malfliet-Tjon type potential, and the convergence of the multiple scattering series is investigated.Comment: Talk at the 18th International IUPAP Conference on Few-Body Problems in Physics, Aug. 21-26, 2006, Santos, Brazi

    The Relativistic Rotation

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    The classical rotation is not self-consistent in the framework of the special theory of relativity. the Relativistic rotation is obtained, which takes the relativistic effect into account. It is demonstrated that the angular frequency of classical rotation is only valid in local approximation. The properties of the relativistic rotation and the relativistic transverse Doppler shift are discussed in this work

    Learning policies for Markov decision processes from data

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    We consider the problem of learning a policy for a Markov decision process consistent with data captured on the state-actions pairs followed by the policy. We assume that the policy belongs to a class of parameterized policies which are defined using features associated with the state-action pairs. The features are known a priori, however, only an unknown subset of them could be relevant. The policy parameters that correspond to an observed target policy are recovered using `1-regularized logistic regression that best fits the observed state-action samples. We establish bounds on the difference between the average reward of the estimated and the original policy (regret) in terms of the generalization error and the ergodic coefficient of the underlying Markov chain. To that end, we combine sample complexity theory and sensitivity analysis of the stationary distribution of Markov chains. Our analysis suggests that to achieve regret within order O( √ ), it suffices to use training sample size on the order of Ω(logn · poly(1/ )), where n is the number of the features. We demonstrate the effectiveness of our method on a synthetic robot navigation example

    Learning policies for Markov decision processes from data

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    We consider the problem of learning a policy for a Markov decision process consistent with data captured on the state-actions pairs followed by the policy. We assume that the policy belongs to a class of parameterized policies which are defined using features associated with the state-action pairs. The features are known a priori, however, only an unknown subset of them could be relevant. The policy parameters that correspond to an observed target policy are recovered using `1-regularized logistic regression that best fits the observed state-action samples. We establish bounds on the difference between the average reward of the estimated and the original policy (regret) in terms of the generalization error and the ergodic coefficient of the underlying Markov chain. To that end, we combine sample complexity theory and sensitivity analysis of the stationary distribution of Markov chains. Our analysis suggests that to achieve regret within order O( √ ), it suffices to use training sample size on the order of Ω(logn · poly(1/ )), where n is the number of the features. We demonstrate the effectiveness of our method on a synthetic robot navigation example

    A metal–organic framework/α-alumina composite with a novel geometry for enhanced adsorptive separation

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    The development of a metal–organic framework/α-alumina composite leads to a novel concept: efficient adsorption occurs within a plurality of radial micro-channels with no loss of the active adsorbents during the process. This composite can effectively remediate arsenic contaminated water producing potable water recovery, whereas the conventional fixed bed requires eight times the amount of active adsorbents to achieve a similar performance

    Pollutant dispersion over two-dimensional idealized street canyons: a large-eddy simulation approach

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    Session: H14-117A series of two-dimensional (2D) street canyon models with a wide range of building-height-to-street-width (aspect) ratios are employed in this study to elucidate the pollutant transport over idealized urban areas. The large-eddy simulation (LES) is used to resolve the turbulent flows and pollutant transport in the urban boundary layer (UBL) over the street canyons. An area source of uniform pollutant concentration is applied on the ground of the first street canyon to examine the pollutant plume dispersion behaviors over the downstream building roughness elements. The LES results show that, for the street canyon with the pollutant source, the pollutant removal is governed by atmospheric turbulence in both skimming flow and wake-interference regimes. Statistical analysis reveals that the turbulent kinetic energy (TKE) is peaked near the top of the building roughness elements that contributes most to turbulent pollutant removal. The roof-level TKE distribution also demonstrates that the turbulence production is not governed by local wind shear. Instead, the descending TKE from the UBL plays a more important role. In the UBL, the vertical pollutant profiles illustrate self-similarity behaviours in the downstream region. The pollutant disperses rapidly over the buildings, exhibiting a Gaussian-plume shape. Maximum vertical pollutant dispersion coefficient is observed at aspect ratio equal to 1/10. A strong correlation between friction factor and dispersion coefficient is found, implying that the downstream air quality could be improved by increasing the roughness of urban area.postprin
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