The influence of magnetic field geometry on magnetars X-ray spectra

Nowadays, the analysis of the X-ray spectra of magnetically powered neutron stars or magnetars is one of the most valuable tools to gain insight into the physical processes occurring in their interiors and magnetospheres. In particular, the magnetospheric plasma leaves a strong imprint on the observed X-ray spectrum by means of Compton up-scattering of the thermal radiation coming from the star surface. Motivated by the increased quality of the observational data, much theoretical work has been devoted to develop Monte Carlo (MC) codes that incorporate the effects of resonant Compton scattering (RCS) in the modeling of radiative transfer of photons through the magnetosphere. The two key ingredients in this simulations are the kinetic plasma properties and the magnetic field (MF) configuration. The MF geometry is expected to be complex, but up to now only mathematically simple solutions (self-similar solutions) have been employed. In this work, we discuss the effects of new, more realistic, MF geometries on synthetic spectra. We use new force-free solutions [14] in a previously developed MC code [9] to assess the influence of MF geometry on the emerging spectra. Our main result is that the shape of the final spectrum is mostly sensitive to uncertain parameters of the magnetospheric plasma, but the MF geometry plays an important role on the angle-dependence of the spectra.

Effects of high-color-discrimination capability spectra on color-deficient vision

Light sources with three spectral bands in specific spectral positions are known to have high-color-discrimination capability. W. A. Thornton hypothesized that they may also enhance color discrimination for color-deficient observers. This hypothesis was tested here by comparing the Rösch–MacAdam color volume for color-deficient observers rendered by three of these singular spectra, two reported previously and one derived in this paper by maximization of the Rösch–MacAdam color solid. It was found that all illuminants tested enhance discriminability for deuteranomalous observers, but their impact on other congenital deficiencies was variable. The best illuminant was the one derived here, as it was clearly advantageous for the two red–green anomalies and for tritanopes and almost neutral for red–green dichromats. We conclude that three-band spectra with high-color-discrimination capability for normal observers do not necessarily produce comparable enhancements for color-deficient observers, but suitable spectral optimization clearly enhances the vision of the color deficient.

SERS Active Surface in Two Steps, Patterning and Metallization

Robust and reproducible metallized nano/microstructured surfaces of polymeric surfaces have been successfully prepared by direct laser interference patterning (DLIP) of commercial polymeric films followed by sputtering of metallic thin films. The SERS spectra for 2-thioaniline adsorbed on a structured polycarbonate surfaces covered with a gold or platinum film showed a ca. three order of magnitude enhancement over a flat surface with the same metal film. The method here reported is suitable for mass production of substrates for SERS since large areas (several cm2) can be structured in ca. 1–5 s.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Identifying student and teacher difficulties in interpreting atomic spectra using a quantum model of emission and absorption of radiation

Our study sets out to identify the difficulties that high school students, teachers, and university students encounter when trying to explain atomic spectra. To do so, we identify the key concepts that any quantum model for the emission and absorption of electromagnetic radiation must include to account for the gas spectra and we then design two questionnaires, one for teachers and the other for students. By analyzing the responses, we conclude that (i) teachers lack a quantum model for the emission and absorption of electromagnetic radiation capable of explaining the spectra, (ii) teachers and students share the same difficulties, and (iii) these difficulties concern the model of the atom, the model of radiation, and the model of the interaction between them.