News on PHOTOS Monte Carlo: gamma^* -> pi^+ pi^-(gamma) and K^\pm -> pi^+ pi^- e^\pm nu (gamma)

PHOTOS Monte Carlo is widely used for simulating QED effects in decay of intermediate particles and resonances. It can be easily connected to other main process generators. In this paper we consider decaying processes gamma^* -> pi^+ pi^-(gamma) and K^\pm -> pi^+ pi^- e^\pm nu (gamma) in the framework of Scalar QED. These two processes are interesting not only for the technical aspect of PHOTOS Monte Carlo, but also for precision measurement of alpha_{QED}(M_Z), g-2, as well as pi pi scattering lengths.Comment: 6 pages, 11 figures, proceedings of the PhiPsi09, Oct. 13-16, 2009, Beijing, Chin

Classification of Arbitrary Multipartite Entangled States under Local Unitary Equivalence

We propose a practical method for finding the canonical forms of arbitrary dimensional multipartite entangled states, either pure or mixed. By extending the technique developed in one of our recent works, the canonical forms for the mixed $N$-partite entangled states are constructed where they have inherited local unitary symmetries from their corresponding $N+1$ pure state counterparts. A systematic scheme to express the local symmetries of the canonical form is also presented, which provides a feasible way of verifying the local unitary equivalence for two multipartite entangled states.Comment: 22 pages; published in J. Phys. A: Math. Theo

Quantum Transport Simulation of III-V TFETs with Reduced-Order K.P Method

III-V tunneling field-effect transistors (TFETs) offer great potentials in future low-power electronics application due to their steep subthreshold slope and large "on" current. Their 3D quantum transport study using non-equilibrium Green's function method is computationally very intensive, in particular when combined with multiband approaches such as the eight-band K.P method. To reduce the numerical cost, an efficient reduced-order method is developed in this article and applied to study homojunction InAs and heterojunction GaSb-InAs nanowire TFETs. Device performances are obtained for various channel widths, channel lengths, crystal orientations, doping densities, source pocket lengths, and strain conditions

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS478 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Electrically Tunable Polarizer Based on Graphene-loaded Plasmonic Cross Antenna

The unique gate-voltage dependent optical properties of graphene make it a promising electrically-tunable plasmonic material. In this work, we proposed in-situ control of the polarization of nanoantennas by combining plasmonic structures with an electrostatically tunable graphene monolayer. The tunable polarizer is designed based on an asymmetric cross nanoantenna comprising two orthogonal metallic dipoles sharing the same feed gap. Graphene monolayer is deposited on a Si/SiO2 substrate, and inserted beneath the nanoantenna. Our modelling demonstrates that as the chemical potential is incremented up to 1 eV by electrostatic doping, resonant wavelength for the longer graphene-loaded dipole is blue shifted for 500 nm (~ 10% of the resonance) in the mid-infrared range, whereas the shorter dipole experiences much smaller influences due to the unique wavelength-dependent optical properties of graphene. In this way, the relative field amplitude and phase between the two dipole nanoantennas are electrically adjusted, and the polarization state of the reflected wave can be electrically tuned from the circular into near-linear states with the axial ratio changing over 8 dB. Our study thus confirms the strong light-graphene interaction with metallic nanostructures, and illuminates promises for high-speed electrically controllable optoelectronic devices.Comment: 11 pages, 7 figure

Slow Adaptive OFDMA Systems Through Chance Constrained Programming

Adaptive OFDMA has recently been recognized as a promising technique for providing high spectral efficiency in future broadband wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the instantaneous channel conditions of all users. However, such "fast" adaptation requires high computational complexity and excessive signaling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints for the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signaling overhead when compared with the conventional fast adaptive OFDMA. Our work can be viewed as an initial attempt to apply the chance constrained programming methodology to wireless system designs. Given that most wireless systems can tolerate an occasional dip in the quality of service, we hope that the proposed methodology will find further applications in wireless communications