Alcatel-Lucent

About: Alcatel-Lucent is a based out in Stuttgart, Germany. It is known for research contribution in the topics: Signal & Network packet. The organization has 37003 authors who have published 53332 publications receiving 1430547 citations. The organization is also known as: Alcatel-Lucent S.A. & Alcatel.

Patterned colloidal deposition controlled by electrostatic and capillary forces.

Abstract: We use substrates chemically micropatterned with anionic and cationic regions to govern the deposition of charged colloidal particles. The direct observation of the colloidal assembly suggests that this process includes two steps: an initial patterned attachment of colloids to the substrate and an additional ordering of the structure upon drying. The driving forces of the process, i.e., screened electrostatic and lateral capillary interactions, are discussed. This approach makes it possible to fabricate complex, high-resolution two-dimensional arrays of colloidal particles.

Interfacial Chemistries for Nanoscale Transfer Printing

Abstract: We describe a patterning technique that uses self-assembled monolayers and other surface chemistries for guiding the transfer of material from relief features on a stamp to a substrate. This purely additive contact printing technique is capable of nanometer resolution. Pattern transfer is fast and it occurs at ambient conditions. We illustrate the versatility of this method by printing single-layer metal patterns with feature sizes from a few tens of microns to a few tens of nanometers. We also demonstrate its use for patterning, in a single step, metal/dielectric/metal multilayers for functional thin film capacitors on plastic substrates.

Evidence for an Anisotropic State of Two-Dimensional Electrons in High Landau Levels

Abstract: Magnetotransport experiments on high mobility two-dimensional electron gases in GaAs/AlGaAs heterostructures have revealed striking anomalies near half filling of several spin-resolved, yet highly excited, Landau levels. These anomalies include strong anisotropies and nonlinearities of the longitudinal resistivity ρxx which commence only below about 150 mK. These phenomena are not seen in the ground state or first excited Landau level but begin abruptly in the third level. Although their origin remains unclear, we speculate that they reflect the spontaneous development of a generic anisotropic many-electron state.

Laser action from two-dimensional distributed feedback in photonic crystals

Abstract: We report an analysis of the operation of a new type of laser resonator with two-dimensional distributed feedback from a photonic crystal. The gain medium consists of a 2-(4-biphenylyl)-5(4-tert-butylphenyl)-1,3,4-oxadiazole host doped with Coumarin 490 and DCM and is deposited on lithographically patterned Si/SiO2 structures. Bragg reflections caused by the grating diminish the group velocity of photons along some directions of crystallographic symmetry to zero, and the resulting feedback gives rise to laser oscillations. Dispersion relations for photons were calculated analytically and are used to interpret the laser emission spectra.

Improving the Accuracy and Speed of Support Vector Machines

Abstract: Support Vector Learning Machines (SVM) are finding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very general backdrop, any methods for improving the generalization performance, or for improving the speed in test phase, of SVMs are of increasing interest. In this paper we combine two such techniques on a pattern recognition problem. The method for improving generalization performance (the "virtual support vector" method) does so by incorporating known invariances of the problem. This method achieves a drop in the error rate on 10,000 NIST test digit images of 1.4% to 1.0%. The method for improving the speed (the "reduced set" method) does so by approximating the support vector decision surface. We apply this method to achieve a factor of fifty speedup in test phase over the virtual support vector machine. The combined approach yields a machine which is both 22 times faster than the original machine, and which has better generalization performance, achieving 1.1 % error. The virtual support vector method is applicable to any SVM problem with known invariances. The reduced set method is applicable to any support vector machine.