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

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 Elastic and Inelastic Scattering at Intermediate Energies

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

Three-Body Scattering without Partial Waves

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

The Relativistic Rotation

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

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

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

Numerical modeling of flows and pollutant dispersion within and above urban street canyons under unstable thermal stratification by large-eddy simulation

Recently, with the ever increasing urban areas in developing countries, the problem of air pollution due to vehicular exhaust arouses the concern of different groups of people. Understanding how different factors, such as urban morphology, meteorological conditions and human activities, affect the characteristics of street canyon ventilation, pollutant dispersion above urban areas and pollutant re-entrainment from the shear layer can help us improve air pollution control strategies. Among the factors mentioned above, thermal stratification is a significant one determining the pollutant transport behaviors in certain situation, e.g. when the urban surface is heated by strong solar radiation, which, however, is still not widely explored. The objective of this study is to gain an in-depth understanding of the effects of unstable thermal stratification on the flows and pollutant dispersion within and above urban street canyons through numerical modeling using large-...published_or_final_versio

Effect of roughness on vertical dispersion coefficient over idealized urban street canyons under neutral stratification

Ground-level pollutants (e.g. vehicular emission) are the primary pollutant sources affecting the public health and living quality in many modern compact cities. Thus, it is necessary to estimate the pollutant concentration and distribution in urban areas in a fast and reliable manner for better urban planning. Gaussian plume dispersion model is commonly used in practice. However, one of its major parameters, dispersion coefficient, often overlooks the effect of surface roughness so its accuracy in urban application is in doubt. In the existence of large-scale roughness element, the calculation of pollutant distribution in the urban boundary layer (UBL) would be prone to error. Our previous studies, using ...published_or_final_versio