Contribution of Scalar Loops to the Three-Photon Decay of the Z

I corrected 3 mistakes from the first version: that were an omitted Feynman integration in the function f^3_{ij}, a factor of 2 in front of log f^3_{ij} in eq.2 and an overall factor of 2 in Fig.1 c). The final result is changed drastically. Doing an expansion in the Higgs mass I show that the matrix element is identically 0 in the order (MZ/MH)^2, which is due to gauge invariance. Left with an amplitude of the order (MZ/MH)^4 the final result is that the scalar contribution to this decay rate is several orders of magnitude smaller than those of the W boson and fermions.Comment: 6 pages, plain Tex, 1 figure available under request via fax or mail, OCIP/C-93-5, UQAM-PHE-93/0

Numerical simulations of negative-index refraction in wedge-shaped metamaterials

A wedge-shaped structure made of split-ring resonators (SRR) and wires is numerically simulated to evaluate its refraction behavior. Four frequency bands, namely, the stop band, left-handed band, ultralow-index band, and positive-index band, are distinguished according to the refracted field distributions. Negative phase velocity inside the wedge is demonstrated in the left-handed band and the Snell's law is conformed in terms of its refraction behaviors in different frequency bands. Our results confirmed that negative index of refraction indeed exists in such a composite metamaterial and also provided a convincing support to the results of previous Snell's law experiments.Comment: 18 pages, 6 figure

Systematic analysis of group identification in stock markets

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the marketwide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowledge of the stocks by the optimization of the matrix representation and the percolation approach to the correlation-based network of stocks. These methods drastically reduce the ambiguities while finding stock groups using the eigenvectors of the correlation matrix.Comment: 9 pages, 7 figure

Automated System for Early Breast Cancer Detection in Mammograms

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed

Phase Diagram of Rydberg atoms in a nonequilibrium optical lattice

We study the quantum nonequilibrium dynamics of ultracold three-level atoms trapped in an optical lattice, which are excited to their Rydberg states via a two-photon excitation with nonnegligible spontaneous emission. Rich quantum phases including uniform phase, antiferromagnetic phase and oscillatory phase are identified. We map out the phase diagram and find these phases can be controlled by adjusting the ratio of intensity of the pump light to the control light, and that of two-photon detuning to the Rydberg interaction strength. When the two-photon detuning is blue-shifted and the latter ratio is less than 1, bistability exists among the phases. Actually, this ratio controls the Rydberg-blockade and antiblockade effect, thus the phase transition in this system can be considered as a possible approach to study both effects.Comment: 5 pages,5 figure

Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

Depth estimation from a single image is a fundamental problem in computer vision. In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for depth prediction. Specifically, we adopt an efficient linear propagation model, where the propagation is performed with a manner of recurrent convolutional operation, and the affinity among neighboring pixels is learned through a deep convolutional neural network (CNN). We apply the designed CSPN to two depth estimation tasks given a single image: (1) To refine the depth output from state-of-the-art (SOTA) existing methods; and (2) to convert sparse depth samples to a dense depth map by embedding the depth samples within the propagation procedure. The second task is inspired by the availability of LIDARs that provides sparse but accurate depth measurements. We experimented the proposed CSPN over two popular benchmarks for depth estimation, i.e. NYU v2 and KITTI, where we show that our proposed approach improves in not only quality (e.g., 30% more reduction in depth error), but also speed (e.g., 2 to 5 times faster) than prior SOTA methods.Comment: 14 pages, 8 figures, ECCV 201

Superconductivity at 41 K and its competition with spin-density-wave instability in layered CeO1−x_{1-x}Fx_xFeAs

A series of layered CeO$_{1-x}$F$_x$FeAs compounds with x=0 to 0.20 are synthesized by solid state reaction method. Similar to the LaOFeAs, the pure CeOFeAs shows a strong resistivity anomaly near 145 K, which was ascribed to the spin-density-wave instability. F-doping suppresses this instability and leads to the superconducting ground state. Most surprisingly, the superconducting transition temperature could reach as high as 41 K. The very high superconducting transition temperature strongly challenges the classic BCS theory based on the electron-phonon interaction. The very closeness of the superconducting phase to the spin-density-wave instability suggests that the magnetic fluctuations play a key role in the superconducting paring mechanism. The study also reveals that the Ce 4f electrons form local moments and ordered antiferromagnetically below 4 K, which could coexist with superconductivity.Comment: 4 pages, 5 figure

Anomalous metallic state of Cu0.07_{0.07}TiSe2_2: an optical spectroscopy study

We report an optical spectroscopy study on the newly discovered superconductor Cu$_{0.07}$TiSe$_2$. Consistent with the development from a semimetal or semiconductor with a very small indirect energy gap upon doping TiSe$_2$, it is found that the compound has a low carrier density. Most remarkably, the study reveals a substantial shift of the "screened" plasma edge in reflectance towards high energy with decreasing temperature. This phenomenon, rarely seen in metals, indicates either a sizeable increase of the conducting carrier concentration or/and a decrease of the effective mass of carriers with reducing temperature. We attribute the shift primarily to the later effect.Comment: 4 figures, 4+ page

Nodeless superconductivity in Ca3Ir4Sn13: evidence from quasiparticle heat transport

We report resistivity $\rho$ and thermal conductivity $\kappa$ measurements on Ca$_3$Ir$_4$Sn$_{13}$ single crystals, in which superconductivity with $T_c \approx 7$ K was claimed to coexist with ferromagnetic spin-fluctuations. Among three crystals, only one crystal shows a small hump in resistivity near 20 K, which was previously attributed to the ferromagnetic spin-fluctuations. Other two crystals show the $\rho \sim T^2$ Fermi-liquid behavior at low temperature. For both single crystals with and without the resistivity anomaly, the residual linear term $\kappa_0/T$ is negligible in zero magnetic field. In low fields, $\kappa_0(H)/T$ shows a slow field dependence. These results demonstrate that the superconducting gap of Ca$_3$Ir$_4$Sn$_{13}$ is nodeless, thus rule out nodal gap caused by ferromagnetic spin-fluctuations.Comment: 5 pages, 4 figure