On the measurement of B(E2, 0+ -> 2+) using intermediate-energy Coulomb excitation

Coulomb excitation is a standard method used to extract quadrupole excitation strengths of even-even nuclei. In typical analyses the reaction is assumed to be one-step, Coulomb only, and is treated within a semi-classical model. In this work, fully-quantal coupled-channel calculations are performed for three test cases in order to determine the importance of multi-step effects, nuclear contributions, feeding from other states and corrections to the semi-classical approximation. We study the excitation of 30S, 58Ni and 78Kr on 197Au at ~ 50 AMeV. We find that nuclear effects may contribute more than 10% and that feeding contributions can be larger than 15%. These corrections do not alter significantly the published B(E2) values, however an additional theoretical error of up to 13% should be added to the experimental uncertainty if the semi-classical model is used. This theoretical error is reduced to less than 7% when performing a quantal coupled-channel analysis.Comment: 9 pages, accepted for publication in J. Phys. G: Nucl. Phy

X-ray powder diffraction of high-absorption materials at the XRD1 beamline off the best conditions: Application to (Gd,Nd)5Si4 compounds

Representative compounds of the new family of magnetic materials Gd5-xNdxSi4 were analyzed by X-ray diffraction at the XRD1 beamline at LNLS. To reduce X-ray absorption, thin layers of the powder samples were mounted outside the capillaries and measured in Debye-Scherrer geometry as usual. The X-ray diffraction analyses and the magnetometry results indicate that the behavior of the magnetic transition temperature as a function of Nd content may be directly related to the average of the four smallest interatomic distances between different rare earth sites of the majority phase of each compound. The quality and consistency of the results show that the XRD1 beamline is able to perform satisfactory X-ray diffraction experiments on high-absorption materials even off the best conditions.Comment: 12 pages, 3 figures, 3 table

A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation

Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC requires computations based on vectors of summary statistics, rather than full data sets, a central question is how to derive low-dimensional summary statistics from the observed data with minimal loss of information. In this article we provide a comprehensive review and comparison of the performance of the principal methods of dimension reduction proposed in the ABC literature. The methods are split into three nonmutually exclusive classes consisting of best subset selection methods, projection techniques and regularization. In addition, we introduce two new methods of dimension reduction. The first is a best subset selection method based on Akaike and Bayesian information criteria, and the second uses ridge regression as a regularization procedure. We illustrate the performance of these dimension reduction techniques through the analysis of three challenging models and data sets.Comment: Published in at http://dx.doi.org/10.1214/12-STS406 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org