X-ray magneto-optics of lanthanide materials: principles and applications

Lanthanide metals are a particular class of magnetic materials in which the magnetic moments are carried mainly by the localized electrons of the 4f shell. They are frequently found in technically relevant systems, to achieve, e.g., high magnetic anisotropy. Magneto-optical methods in the x-ray range are well suited to study complex magnetic materials in an element-specific way. In this work, we report on recent progress on the quantitative determination of magneto-optical constants of several lanthanides in the soft x-ray region and we show some examples of applications of magneto-optics to hard-magnetic interfaces and exchange-coupled layered structures containing lanthanide elements.Comment: 7 pages, 6 figures, invited contribution to the Symposium "X-ray magneto-optics" of the Spring Meeting of the German Physical Society held in Regensburg, Germany, 8-12 March 2004. Revised version, minor change

Critical Susceptibility Exponent Measured from Fe/W(110) Bilayers

The critical phase transition in ferromagnetic ultrathin Fe/W(110) films has been studied using the magnetic ac susceptibility. A statistically objective, unconstrained fitting of the susceptibility is used to extract values for the critical exponent (gamma), the critical temperature Tc, the critical amplitude (chi_o) and the range of temperature that exhibits power-law behaviour. A fitting algorithm was used to simultaneously minimize the statistical variance of a power law fit to individual experimental measurements of chi(T). This avoids systematic errors and generates objective fitting results. An ensemble of 25 measurements on many different films are analyzed. Those which permit an extended fitting range in reduced temperature lower than approximately .00475 give an average value gamma=1.76+-0.01. Bilayer films give a weighted average value of gamma = 1.75+-0.02. These results are in agreement with the -dimensional Ising exponent gamma= 7/4. Measurements that do not exhibit power-law scaling as close to Tc (especially films of thickness 1.75ML) show a value of gamma higher than the Ising value. Several possibilities are considered to account for this behaviour.Comment: -Submitted to Phys. Rev. B -Revtex4 Format -6 postscript figure

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas

Coverage, Continuity and Visual Cortical Architecture

The primary visual cortex of many mammals contains a continuous representation of visual space, with a roughly repetitive aperiodic map of orientation preferences superimposed. It was recently found that orientation preference maps (OPMs) obey statistical laws which are apparently invariant among species widely separated in eutherian evolution. Here, we examine whether one of the most prominent models for the optimization of cortical maps, the elastic net (EN) model, can reproduce this common design. The EN model generates representations which optimally trade of stimulus space coverage and map continuity. While this model has been used in numerous studies, no analytical results about the precise layout of the predicted OPMs have been obtained so far. We present a mathematical approach to analytically calculate the cortical representations predicted by the EN model for the joint mapping of stimulus position and orientation. We find that in all previously studied regimes, predicted OPM layouts are perfectly periodic. An unbiased search through the EN parameter space identifies a novel regime of aperiodic OPMs with pinwheel densities lower than found in experiments. In an extreme limit, aperiodic OPMs quantitatively resembling experimental observations emerge. Stabilization of these layouts results from strong nonlocal interactions rather than from a coverage-continuity-compromise. Our results demonstrate that optimization models for stimulus representations dominated by nonlocal suppressive interactions are in principle capable of correctly predicting the common OPM design. They question that visual cortical feature representations can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure

Generalized Romberg methods for integrals of derivatives

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46316/1/211_2005_Article_BF02165095.pd