No Arabic abstract
The energy spectral density $E(k)$, where $k$ is the spatial wave number, is a well-known diagnostic of homogeneous turbulence and magnetohydrodynamic turbulence. However in most of the curves plotted by different authors, some systematic kinks can be observed at $k=9$, $k=15$ and $k=19$. We claim that these kinks have no physical meaning, and are in fact the signature of the method which is used to estimate $E(k)$ from a 3D spatial grid. In this paper we give another method, in order to get rid of the spurious kinks and to estimate $E(k)$ much more accurately.
This paper discusses the benefits of object-oriented programming to scientific computing, using our recent calculations of exciton binding energies with time-dependent density-functional theory (arXiv: 1302.6972) as a case study. We find that an object-oriented approach greatly facilitates the development, the debugging, and the future extension of the code by promoting code reusing. We show that parallelism is added easily in our code in a object-oriented fashion with ScaLAPACK, Boost::MPI and OpenMP.
ISICS, originally a C language program for calculating K-, L- and M-shell ionization and X-ray production cross sections from ECPSSR and PWBA theory, has been reengineered into a C++ language class, named ISICSoo. The new software design enables the use of ISICS functionality in other software systems. The code, originally developed for Microsoft Windows operating systems, has been ported to Linux and Mac OS platforms to facilitate its use in a wider scientific environment. The reengineered software also includes some fixes to the original implementation, which ensure more robust computational results and a review of some physics parameters used in the computation. The paper describes the software design and the modifications to the implementation with respect to the previous version; it also documents the test process and provides some indications about the software performance.
Since the initial work by Ashenfelter and Card in 1985, the use of difference-in-differences (DID) study design has become widespread. However, as pointed out in the literature, this popular quasi-experimental design also suffers estimation bias and inference bias, which could be very serious in some circumstances. In this study, we start by investigating potential sources of systemic bias from the DID design. Via analyzing their impact on statistical estimation and inference, we propose a remedy -- a permutational detrending (PD) strategy -- to overcome the challenges in both the estimation bias and the inference bias. We prove that the proposed PD DID method provides unbiased point estimates, confidence interval estimates, and significance tests. We illustrate its statistical proprieties using simulation experiments. We demonstrate its practical utility by applying it to the clinical data EASE (Elder-Friendly Approaches to the Surgical Environment) and the social-economical data CPS (Current Population Survey). We discuss the strengths and limitations of the proposed approach.
Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently and reconstruct the free energy landscape. In methods like metadynamics, the quality of these collective variables plays a key role in convergence efficiency. Unfortunately in many systems of interest it is not possible to identify an optimal collective variable, and one must deal with the non-ideal situation of a system in which some slow modes are not accelerated. We propose a two-step approach in which, by taking into account the residual multiscale nature of the problem, one is able to significantly speed up convergence. To do so, we combine an exploratory metadynamics run with an optimization of the free energy difference between metastable states, based on the recently proposed variationally enhanced sampling method. This new method is well parallelizable and is especially suited for complex systems, because of its simplicity and clear underlying physical picture.
A physical model is presented for a semiconductor electrode of a photoelectrochemical (PEC) cell, accounting for the potential drop in the Helmholtz layer. Hence both band edge pinning and unpinning are naturally included in our description. The model is based on the continuity equations for charge carriers and direct charge transfer from the energy bands to the electrolyte. A quantitative calculation of the position of the energy bands and the variation of the quasi-Fermi levels in the semiconductor with respect to the water reduction and oxidation potentials is presented. Calculated current-voltage curves are compared with established analytical models and measurement. Our model calculations are suitable to enhance understanding and improve properties of semiconductors for photoelectrochemical water splitting.