Magnetism in electron-doped copper oxides

We report muon spin relaxation/rotation measurements on sintered powder samples of Nd_2−x Ce _x CuO_4−y and a large single crystal of Nd₂CuO_4−y . We find an electronic phase diagram which is quite similar to that of hole-doped superconductors such as La_2−x Sr _x CuO_4−y , although the doping of electrons into the system is less efficient in destroying the static moments on the copper spins. Static magnetic order in Nd₂CuO_4−y appears below about 250 K, and two spin reorientations are seen atT=75 K andT=35 K. Measurements of the magnetic field penetration depth have been unsuccessful due to the rare-earth paramagnetism of these materials.     

μSR studies of heavy fermion systems

We have performed both zero field and high transverse field measurements at dilution refrigerator temperatures on a number of heavy electron systems, examining the superconducting and magnetic properties of these interesting materials. Among the materials studied to date are UBe₁₃, URu₂Si₂ and U₆Fe. The magnetic field penetration depth in the superconducting state of UBe₁₃ is greater than 10000 Å, as no increase in the transverse field relaxation rate is observed belowT _c . A sharp increase in the precession frequency is seen, starting atT _c . This frequency shift shows little temperature dependence at low temperature; we found no clear evidence for unconventional superconductivity in this material. Zero field measurements in URu₂Si₂ show the weak antiferromagnetic transition at 17.5 K. Finally, we we found no clear evidence for unconventional superconductivity in this material. Zero field measurements in URu₂Si₂ show the weak antiferromagnetic transition at 17.5 K. Finally, we have observed relaxation in high transverse field due to the formation of a flux lattice in U₆Fe, a material where the electron effective mass is rather lighter than in other heavy fermion systems. The relaxation exhibits a sharp onset atT _c=3.9 K, and is flat at low temperatures as expected for a conventional superconductor.     

π π andK¯K channel coupling

We investigate the origin of the attraction in theK¯K channel around the threshold by introducing an additional channel to theππ andK¯K channels in a separable potential formalism assuming, in general, no direct interaction in theK¯K channel. To reproduce the features of the data, we find that the threshold of the additional channel is much above thef ₀(975) meson position. We show that this three-channel problem can be reduced to an effective two-channel problem where thef ₀(975) behaves as if it were aK¯K molecule bound by the coupling to the exotic channel. This picture is also supported by the fact that a single pole only, in the complexK¯K momentum plane, is associated to thef ₀(975) meson. Various physical observables, like the decay branching ratio and theK¯K scattering length, are then discussed in an effective two-channel framework.     

Optimum parameters for the generalized ADI method

Summary. In the context of the generalized ADI method, we are concerned with the problem of finding in the set of rational functions r with numerator degree m and denominator degree n an element that minimizes where E,F are disjoint real intervals. By extending a recent analysis by Levin and Saff, we present an explicit formula for choosing the pair (m,n) for given m +n. Furthermore, we provide a characterization of and a Remes type algorithm for its determination. Extensive numerical computations furnish some comparison of with asymptotically optimal solutions based on Fejér-Walsh and Leja-Bagby points. Received September 6, 1996 / revised version received June 30, 1997     

Thermal and chemical nanofractal relaxation

We studied shape relaxation of nano-fractal islands, during annealing, after their growth from antimony cluster deposition on graphite surface. Annealing at 180^°C shows evidence of an increase of the fractal branch width with time followed by branch fragmentation, without changing the fractal dimension. The time evolution of the width of the arm suggests the surface self-diffusion mechanism as the main relaxation process. With Monte Carlo simulations, we confirmed the observed behavior. Comparison is done with our previous results on fragmentation of nano-fractal silver islands when impurity added to the incident cluster promotes rapid fragmentation by surface self-diffusion enhancement [1].     

On bounding the effective conductivity of isotropic composite materials

In this paper inequalities for the effective conductivity of isotropic composite materials are derived. These inequalities depend on several coefficients characterizing the microstructure of composites. The obtained coefficients can be exactly calculated for models of a two-component aggregate of multisized, coated ellipsoidal inclusions, packed to fill all space. As a result, new bounds for effective conductivity, considerably narrower than those of Hashin-Shtrikman, are established for such models of composite materials.     

Ionic relaxation in nematic liquid crystal cells

We investigate the dependence of the relaxation time of the current flowing in a nematic cell submitted to an external dc voltage on the physical properties of the substrate. We show that previously presented analyses of the same problem are not very useful for practical applications. We compare our theoretical predictions with experimental data, and show that the agreement is rather good. The influence of the adsorption-desorption phenomenon on the relaxation time is also discussed.     

Du discret au continu pour des modèles de réseaux aléatoires d'atomes

We study in this Note the continuum (macroscopic) limit for some atomistic models for crystals. The purpose is to derive densities of mechanical energies from microscopic models. In contrast to the setting of a previous study, where the microscopic structure was assumed to be periodic, it is modelled here by a stochastic lattice, which enjoys some stationarity and ergodicity properties, following notions previously introduced elsewhere. To cite this article: X. Blanc et al., C. R. Acad. Sci. Paris, Ser. I 342 (2006).     

Feature Selection using Fuzzy Support Vector Machines

The feature selection consists of obtaining a subset of these features to optimally realize the task without the irrelevant ones. Since it can provide faster and cost-effective learning machines and also improve the prediction performance of the predictors, it is a crucial step in machine learning. The feature selection methods using support machines have obtained satisfactory results, but the noises and outliers often reduce the performance. In this paper, we propose a feature selection approach using fuzzy support vector machines and compare it with the previous work, the results of experiments on the UCI data sets show that feature selection using fuzzy SVM obtains better results than using SVM.