To investigate the binary hypothesis in the formation of planetary nebulae, we have been doing long-term photometry and radial velocity (RV) monitoring of bright post-AGB stars which possess bipolar or ellipsoidal nebulae but no indication of a disk in their spectral energy distribution, indicative of a binary companion. RV’s are determined by cross correlating high-resolution spectra with a line mask. Stellar variability and companions both deform the cross correlation function (CCF) and induce periodic variations in the RV. To uniformly quantify the asymmetry of the CCF from a Gaussian, we propose to fit the CCF profile with a Gauss-Hermite series and determine all CCF parameters (RV, skewness, FWHM, and depth) in one single fit. We analyze the correlation and time series of these CCF parameters for V448 Lac and conclude that its RV variability is most likely due to stellar pulsation and not to an orbiting body.

Direct detection of the Epoch of Reionization via the redshifted 21-cm line will have unprecedented implications on the study of structure formation in the early Universe. To fulfill this promise current and future 21-cm experiments will need to detect the weak 21-cm signal over foregrounds several order of magnitude greater. This requires accurate modeling of the galactic and extragalactic emission and of its contaminants due to instrument chromaticity, ionosphere and imperfect calibration. To solve for this complex modeling, we propose a new method based on Gaussian Process Regression (GPR) which is able to cleanly separate the cosmological signal from most of the foregrounds contaminants. We also propose a new imaging method based on a maximum likelihood framework which solves for the interferometric equation directly on the sphere. Using this method, chromatic effects causing the so-called “wedge” are effectively eliminated (i.e. deconvolved) in the cylindrical (k⊥, k∥) power spectrum.

As we move ever closer to the Square Kilometre Array era, support for real-time, interactive visualisation and analysis of tera-scale (and beyond) data cubes will be crucial for on-going knowledge discovery. However, the data-on-the-desktop approach to analysis and visualisation that most astronomers are comfortable with will no longer be feasible: tera-scale data volumes exceed the memory and processing capabilities of standard desktop computing environments. Instead, there will be an increasing need for astronomers to utilise remote high performance computing (HPC) resources. In recent years, the graphics processing unit (GPU) has emerged as a credible, low cost option for HPC. A growing number of supercomputing centres are now investing heavily in GPU technologies to provide O(100) Teraflop/s processing. I describe how a GPU-powered computing cluster allows us to overcome the analysis and visualisation challenges of tera-scale data. With a GPU-based architecture, we have moved the bottleneck from processing-limited to bandwidth-limited, achieving exceptional real-time performance for common visualisation and data analysis tasks.

Magnetic helicity (volume integral of the product of the magnetic field vector B and the vector potential A), or its proxy, the current helicity at the surface (surface integral of B·J or BzJz), is an important quantity which characterizes the helical nature of solar magnetic fields. The current helicity on the Sun shows a tendency, though with large dispersion, that it is positive in the southern hemisphere and negative in the northern hemisphere (the helicity sign rule). However, there are indications that the helicity sign rule may be reversed at activity minimum periods. We will discuss the significance of this property by focusing on the statistical distributions of helicity whether its dispersion follows Gaussian distribution or not.

We present a brief technical outline of the newly-formed project, “Detection of Spectroscopic Differences over Time” (DS/DT). Our collaboration is using individual exposures from the SDSS spectroscopic archive to produce a uniformly-processed set of time-resolved spectra. Here we provide an overview of the properties and processing of the available data, and highlight the wide range of time base-lines present in the archive.

Spectral surveys in the past were a hobby of a few, usually restricted to strong, line-rich and close-by sources which were considered templates for source classes, e.g. Orion KL for hot cores, IRC+10216 for AGB stars, and CRL618 for protoplanetary nebulae. Not any more, since with the large bandwidths and high sensitivities of modern instruments, notably ALMA, all but a few sources will show many lines from many molecules at every observations. So (involuntary) line surveys will be the norm rather than the exception. A common strategy is to ignore all lines but the few one is interested in. Since all data will be available through the archive, this does not mean that the data are lost, since eventually the information will be extracted. Another strategy is to take the bull by the horns, and try to analyze all or at least a large portion of the spectrum. This includes the steps of line identification, source modeling and linking to physical and chemical models. With the data volumes at hand doing it the traditional, pedestrian, way is somewhere between impractical and impossible, semi-automatic methods need to be employed.