Strong-field approximation in photoionization

Abstract

The definition and characteristics of the strong-field environment for an atom in a laser field are specified in terms of the relevant intensity parameters. The limits of perturbation theory are set, and it is emphasized that this must be done in terms of laser field energy, not electric field strength. The formal basis and special features of the SFA (strong-field approximation) are reviewed, and it is pointed out that the three methods encompassed in the so-called KFR (Keldysh-Faisal-Reiss) technique are actually quite different. Validity conditions and some applications of the SFA are given.     

Resampling-based information criteria for best-subset regression

When a linear model is chosen by searching for the best subset among a set of candidate predictors, a fixed penalty such as that imposed by the Akaike information criterion may penalize model complexity inadequately, leading to biased model selection. We study resampling-based information criteria that aim to overcome this problem through improved estimation of the effective model dimension. The first proposed approach builds upon previous work on bootstrap-based model selection. We then propose a more novel approach based on cross-validation. Simulations and analyses of a functional neuroimaging data set illustrate the strong performance of our resampling-based methods, which are implemented in a new R package.     

Engineered inorganic core/shell nanoparticles

It has been for a long time recognized that nanoparticles are of great scientific interest as they are effectively a bridge between bulk materials and atomic structures. At first, size effects occurring in single elements have been studied. More recently, progress in chemical and physical synthesis routes permitted the preparation of more complex structures. Such structures take advantages of new adjustable parameters including stoichiometry, chemical ordering, shape and segregation opening new fields with tailored materials for biology, mechanics, optics magnetism, chemistry catalysis, solar cells and microelectronics. Among them, core/shell structures are a particular class of nanoparticles made with an inorganic core and one or several inorganic shell layer(s). In earlier work, the shell was merely used as a protective coating for the core. More recently, it has been shown that it is possible to tune the physical properties in a larger range than that of each material taken separately. The goal of the present review is to discuss the basic properties of the different types of core/shell nanoparticles including a large variety of heterostructures. We restrict ourselves on all inorganic (on inorganic/inorganic) core/shell structures. In the light of recent developments, the applications of inorganic core/shell particles are found in many fields including biology, chemistry, physics and engineering. In addition to a representative overview of the properties, general concepts based on solid state physics are considered for material selection and for identifying criteria linking the core/shell structure and its resulting properties. Chemical and physical routes for the synthesis and specific methods for the study of core/shell nanoparticle are briefly discussed.     

Conditioning exceedances on covariate processes

This article concerns the statistical inference for the upper tail of the conditional distribution of a response variable Y given a covariate X = x based on n random vectors within the parametric extreme value framework. Pioneering work in this field was done by Smith (Stat Sci 4:367–393, 1989) and Smith and Shively (Atmos Environ 29:3489–3499, 1995). We propose to base the inference on a conditional distribution of the point process of exceedances given the point process of covariates. It is of importance that the conditional distribution merely depends on the conditional distribution of the response variable given the covariates. In the special case of Poisson processes such a result may be found in Reiss (1993). Our results are valid within the broader model where the response variables are conditionally independent given the covariates. It is numerically exemplified that the maximum likelihood principle leads to more accurate estimators within the conditional approach than in the previous one.     

Tunneling magnetothermopower in magnetic tunnel junction nanopillars

We study tunneling magnetothermopower (TMTP) in CoFeB/MgO/CoFeB magnetic tunnel junction nanopillars. Thermal gradients across the junctions are generated by an electric heater line. Thermopower voltages up to a few tens of μV between the top and bottom contact of the nanopillars are measured which scale linearly with the applied heating power and hence the thermal gradient. The thermopower signal varies by up to 10 μV upon reversal of the relative magnetic configuration of the two CoFeB layers from parallel to antiparallel. This signal change corresponds to a large spin-dependent Seebeck coefficient of the order of 100 μV/K and a large TMTP change of the tunnel junction of up to 90%.     

Field programmable spin-logic based on magnetic tunnelling elements

Spin-dependent tunnelling elements are widely studied due to their possible application in electronic devices. Here we focus on field programmable logic devices. We introduce the concepts and demonstrate experimentally the functionality of reprogrammable logic gates based on spin-dependent tunnelling elements. We further extend this demonstration to logic gates consisting of micron-sized tunnelling elements.     

Strong convergence of multivariate point processes of exceedances

We study the asymptotic behavior of vectors of point processes of exceedances of random thresholds based on a triangular scheme of random vectors. Multivariate maxima w.r.t. marginal ordering may be regarded as a special case. It is proven that strong convergence—that is convergence of distributions w.r.t. the variational distance—of such multivariate point processes holds if, and only if, strong convergence of multivariate maxima is valid. The limiting process of multivariate point processes of exceedances is built by a certain Poisson process. Auxiliary results concerning upper bounds on the variational distance between vectors of point processes are of interest in its own right.The author was supported by the Deutsche Forschungsgemeinschaft.     

Learning to prove: The idea of heuristic examples

Proof is an important topic in the area of mathematics curriculum and an essential aspect of mathematical competence. However, recent studies have revealed wide gaps in student's understanding of proof. Furthermore, effective teaching to prove, for example, by Schoenfeld's approach, is a real challenge for teachers. A very powerful and empirically well founded method of learning mathematics, which is also relatively easy to implement in the classroom, is learning through worked-out examples. It is, however, primarily suited for algorithmic content areas. We propose the concept of using heuristic worked-out examples, which do not provide an algorithmic problem solution but offer instead heuristic steps that lead towards finding a proof. We rely on Boero's model of proving in designing the single sub-steps of a heuristic example. We illustrate our instructional idea by presenting an heuristic example for proving that the interior angles in any triangle add up to 180°.     

MAD: practical implementation of MCAO concepts

The European Southern Observatory (ESO) together with external research institutes have built a Multi-Conjugate Adaptive Optics (MCAO) Demonstrator (MAD) to perform wide field-of-view adaptive optics correction (2′ in K band). The aim of MAD is to demonstrate the on-sky feasibility of the MCAO technique and to evaluate its critical aspects in the framework of both the 2nd generation instrumentation for the Very Large Telescope (VLT) and the Overwhelmingly Large Telescope (OWL). The MAD module will be installed on the VLT to perform on-sky observations. MAD comprises two deformable mirrors and two different multi-reference wavefront sensors with natural guide stars. In this article we present the MAD design, some aspects of the MAD calibration and the first closed-loop results in the laboratory in Single Conjugated Adaptive Optics (SCAO) and Ground Layer Adaptive Optics (GLAO) configurations. To cite this article: E. Marchetti et al., C. R. Physique 6 (2005).