No Arabic abstract
Mozambique has been proposed as a host for one of the future Square Kilometre Array stations in Southern Africa. However, Mozambique does not possess a university astronomy department and only recently has there been interest in developing one. South Africa has been funding students at the MSc and PhD level, as well as researchers. Additionally, Mozambicans with Physics degrees have been funded at the MSc level. With the advent of the International Year of Astronomy, there has been a very strong drive, from these students, to establish a successful astronomy department in Mozambique. The launch of the commemorations during the 2008 World Space Week was very successful and Mozambique is to be used to motivate similar African countries who lack funds but are still trying to take part in the International Year of Astronomy. There hare been limited resources and funding, however there is a strong will to carry this momentum into 2009 and, with this, influence the Government to introduce Astronomy into its national curriculum and at University level. Mozambiques motto for the International Year of Astronomy is Descobre o teu Universo.
The HYDRO mini-application has been successfully used as a research vehicle in previous PRACE projects [6]. In this paper, we evaluate the benefits of the tasking model introduced in recent OpenMP standards [9]. We have developed a new version of HYDRO using the concept of OpenMP tasks and this implementation is compared to already existing and optimized Open
In this article we wonder what the next 100 years will bring for women in astronomy in the UK. After this year of looking back and celebrating 100 years of women in the Royal Astronomical Society (RAS), we now ask: what might the future hold? Extrapolating current trends, when might we expect equality in the genders of RAS members, speakers at meetings, award winners and more? Ultimately, when might we stop needing to talk about women in astronomy at all - when it will be as irrelevant to the conversation about astronomy as being a male astronomer is?
Astronomy is entering a new era of discovery, coincident with the establishment of new facilities for observation and simulation that will routinely generate petabytes of data. While an increasing reliance on automated data analysis is anticipated, a critical role will remain for visualization-based knowledge discovery. We have investigated scientific visualization applications in astronomy through an examination of the literature published during the last two decades. We identify the two most active fields for progress - visualization of large-N particle data and spectral data cubes - discuss open areas of research, and introduce a mapping between astronomical sources of data and data representations used in general purpose visualization tools. We discuss contributions using high performance computing architectures (e.g: distributed processing and GPUs), collaborative astronomy visualization, the use of workflow systems to store metadata about visualization parameters, and the use of advanced interaction devices. We examine a number of issues that may be limiting the spread of scientific visualization research in astronomy and identify six grand challenges for scientific visualization research in the Petascale Astronomy Era.
Astronomers in CANDELS outline changes for the academic system to promote a smooth transition for junior scientists from academia to industry.
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied statistics relevant to astronomical research are briefly discussed: nonparametric methods for use when little is known about the behavior of the astronomical populations or processes; data smoothing with kernel density estimation and nonparametric regression; unsupervised clustering and supervised classification procedures for multivariate problems; survival analysis for astronomical datasets with nondetections; time- and frequency-domain times series analysis for light curves; and spatial statistics to interpret the spatial distributions of points in low dimensions. Two types of resources are presented: about 40 recommended texts and monographs in various fields of statistics, and the public domain R software system for statistical analysis. Together with its sim 3500 (and growing) add-on CRAN packages, R implements a vast range of statistical procedures in a coherent high-level language with advanced graphics.