A Nonlinear Multigrid Steady-State Solver for Microflow

We develop a nonlinear multigrid method to solve the steady state of microflow, which is modeled by the high order moment system derived recently for the steady-state Boltzmann equation with ES-BGK collision term. The solver adopts a symmetric Gauss-Seidel iterative scheme nested by a local Newton iteration on grid cell level as its smoother. Numerical examples show that the solver is insensitive to the parameters in the implementation thus is quite robust. It is demonstrated that expected efficiency improvement is achieved by the proposed method in comparison with the direct time-stepping scheme

Optical Studies of Radiation Damage and Impurities in RbCdF3

Physic

Quantum Hydrodynamic Model by Moment Closure of Wigner Equation

In this paper, we derive the quantum hydrodynamics models based on the moment closure of the Wigner equation. The moment expansion adopted is of the Grad type firstly proposed in \cite{Grad}. The Grad's moment method was originally developed for the Boltzmann equation. In \cite{Fan_new}, a regularization method for the Grad's moment system of the Boltzmann equation was proposed to achieve the globally hyperbolicity so that the local well-posedness of the moment system is attained. With the moment expansion of the Wigner function, the drift term in the Wigner equation has exactly the same moment representation as in the Boltzmann equation, thus the regularization in \cite{Fan_new} applies. The moment expansion of the nonlocal Wigner potential term in the Wigner equation is turned to be a linear source term, which can only induce very mild growth of the solution. As the result, the local well-posedness of the regularized moment system for the Wigner equation remains as for the Boltzmann equation

Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images

Despite the successful applications of probabilistic collaborative representation classification (PCRC) in pattern classification, it still suffers from two challenges when being applied on hyperspectral images (HSIs) classification: 1) ineffective feature extraction in HSIs under noisy situation; and 2) lack of prior information for HSIs classification. To tackle the first problem existed in PCRC, we impose the sparse representation to PCRC, i.e., to replace the 2-norm with 1-norm for effective feature extraction under noisy condition. In order to utilize the prior information in HSIs, we first introduce the Euclidean distance (ED) between the training samples and the testing samples for the PCRC to improve the performance of PCRC. Then, we bring the coordinate information (CI) of the HSIs into the proposed model, which finally leads to the proposed locality regularized robust PCRC (LRR-PCRC). Experimental results show the proposed LRR-PCRC outperformed PCRC and other state-of-the-art pattern recognition and machine learning algorithms

A multi-mesh adaptive finite element approximation to phase field models

In this work, we propose an efficient multi-mesh adaptive finite element method for simulating the dendritic growth in two- and three-dimensions. The governing equations used are the phase field model, where the regularity behaviors of the relevant dependent variables, namely the thermal field function and the phase field function, can be very different. To enhance the computational efficiency, we approximate these variables on different h-adaptive meshes. The coupled terms in the system are calculated based on the implementation of the multi-mesh h-adaptive algorithm proposed by Li (J. Sci. Comput., pp. 321-341, 24 (2005)). It is illustrated numerically that the multi-mesh technique is useful in solving phase field models and can save storage and the CPU time significantly

Experimental Test of Tracking the King Problem

In quantum theory, the retrodiction problem is not as clear as its classical counterpart because of the uncertainty principle of quantum mechanics. In classical physics, the measurement outcomes of the present state can be used directly for predicting the future events and inferring the past events which is known as retrodiction. However, as a probabilistic theory, quantum-mechanical retrodiction is a nontrivial problem that has been investigated for a long time, of which the Mean King Problem is one of the most extensively studied issues. Here, we present the first experimental test of a variant of the Mean King Problem, which has a more stringent regulation and is termed "Tracking the King". We demonstrate that Alice, by harnessing the shared entanglement and controlled-not gate, can successfully retrodict the choice of King's measurement without knowing any measurement outcome. Our results also provide a counterintuitive quantum communication to deliver information hidden in the choice of measurement.Comment: 16 pages, 5 figures, 2 table

Experimental realization of chiral Landau levels in two-dimensional Dirac cone systems with inhomogeneous effective mass

Chiral zeroth Landau levels are topologically protected bulk states that give rise to chiral anomaly. Previous discussions on such chiral Landau levels are based on three-dimensional Weyl degeneracies. Their realizations using two-dimensional Dirac point systems, being more promising for future applications, were never reported before. Here we propose a theoretical and experimental scheme for realizing chiral Landau levels in a photonic system. By introducing an inhomogeneous effective mass through breaking local parity inversion symmetries, the zeroth-order chiral Landau levels with one-way propagation characteristics are experimentally observed. In addition, the robust transport of the chiral zeroth mode against defects in the system is experimentally tested. Our system provides a new pathway for the realization of chiral Landau levels in two-dimensional Dirac systems, and may potentially be applied in device designs utilizing the transport robustness

Influence of substrate roughness on structure and mechanical property of TiAlN coating fabricated by cathodic arc evaporation

The aim of the present research was to investigate the influence of different substrate roughness on structure and mechanical properties of Titanium Aluminium Nitride (TiAlN) coatings. Tungsten carbide rectangular block was used as substrate. Different surface roughness was achieved by using grinding discs with different grain sizes and diamond polishing powder, and TiAlN coatings were deposited on these substrates under the same preparation technique and parameters. Morphologies of substrates and coatings, crystal structure, thickness and mechanical properties of coatings were investigated using optical microscope, AFM, XRD, CSM scratch tester and tribometer. It was shown that surface morphology of cathodic arc TiAlN coating was mainly affected by the morphology of the substrate surface and the coating growth process. The influence of substrate roughness on crystal structure and thickness of the coatings could be ignored. With the decreasing of the substrate roughness, the adhesion force between coating and substrate increased. Three stresses model was applied to interpret this result. The wear resistance of the coating was also improved with decreasing the substrate roughness. (C) 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of Selection and/or peer-review under responsibility of Lanzhou Institute of Physics, China