30,117 research outputs found
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
Anomalous metallic state of CuTiSe: an optical spectroscopy study
We report an optical spectroscopy study on the newly discovered
superconductor CuTiSe. Consistent with the development from a
semimetal or semiconductor with a very small indirect energy gap upon doping
TiSe, 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
Superconductivity at 41 K and its competition with spin-density-wave instability in layered CeOFFeAs
A series of layered CeOFFeAs 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
Nodeless superconductivity in Ca3Ir4Sn13: evidence from quasiparticle heat transport
We report resistivity and thermal conductivity measurements
on CaIrSn single crystals, in which superconductivity with 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 Fermi-liquid behavior at low temperature.
For both single crystals with and without the resistivity anomaly, the residual
linear term is negligible in zero magnetic field. In low fields,
shows a slow field dependence. These results demonstrate that
the superconducting gap of CaIrSn is nodeless, thus rule out
nodal gap caused by ferromagnetic spin-fluctuations.Comment: 5 pages, 4 figure
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