The Taipan galaxy survey (hereafter simply ‘Taipan’) is a multi-object spectroscopic survey starting in 2017 that will cover 2π steradians over the southern sky (δ ≲ 10°, |b| ≳ 10°), and obtain optical spectra for about two million galaxies out to z < 0.4. Taipan will use the newly refurbished 1.2-m UK Schmidt Telescope at Siding Spring Observatory with the new TAIPAN instrument, which includes an innovative ‘Starbugs’ positioning system capable of rapidly and simultaneously deploying up to 150 spectroscopic fibres (and up to 300 with a proposed upgrade) over the 6° diameter focal plane, and a purpose-built spectrograph operating in the range from 370 to 870 nm with resolving power R ≳ 2000. The main scientific goals of Taipan are (i) to measure the distance scale of the Universe (primarily governed by the local expansion rate, H0) to 1% precision, and the growth rate of structure to 5%; (ii) to make the most extensive map yet constructed of the total mass distribution and motions in the local Universe, using peculiar velocities based on improved Fundamental Plane distances, which will enable sensitive tests of gravitational physics; and (iii) to deliver a legacy sample of low-redshift galaxies as a unique laboratory for studying galaxy evolution as a function of dark matter halo and stellar mass and environment. The final survey, which will be completed within 5 yrs, will consist of a complete magnitude-limited sample (i ⩽ 17) of about 1.2 × 106 galaxies supplemented by an extension to higher redshifts and fainter magnitudes (i ⩽ 18.1) of a luminous red galaxy sample of about 0.8 × 106 galaxies. Observations and data processing will be carried out remotely and in a fully automated way, using a purpose-built automated ‘virtual observer’ software and an automated data reduction pipeline. The Taipan survey is deliberately designed to maximise its legacy value by complementing and enhancing current and planned surveys of the southern sky at wavelengths from the optical to the radio; it will become the primary redshift and optical spectroscopic reference catalogue for the local extragalactic Universe in the southern sky for the coming decade.

To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection algorithms. The procedures assess relative performances and characteristics of the processes in cosmic ray detection, rates of false detections of true objects, and the quality of image cleaning and reconstruction. The cosmic ray rejection algorithms developed by Rhoads (2000, PASP, 112, 703), van Dokkum (2001, PASP, 113, 1420), Pych (2004, PASP, 116, 148), and the IRAF task XZAP by Dickinson are tested using both simulated and real data. It is found that detection efficiency is independent of the density of cosmic rays in an image, being more strongly affected by the density of real objects in the field. As expected, spurious detections and alterations to real data in the cleaning process are also significantly increased by high object densities. We find the Rhoads' linear filtering method to produce the best performance in the detection of cosmic ray events; however, the popular van Dokkum algorithm exhibits the highest overall performance in terms of detection and cleaning.

We present an application of Mathematical Morphology (MM) for the classification of astronomical objects, both for star/galaxy differentiation and galaxy morphology classification. We demonstrate that, for CCD images, 99.3 ± 3.8% of galaxies can be separated from stars using MM, with 19.4 ± 7.9% of the stars being misclassified. We demonstrate that, for photographic plate images, the number of galaxies correctly separated from the stars can be increased using our MM diffraction spike tool, which allows 51.0 ± 6.0% of the high-brightness galaxies that are inseparable in current techniques to be correctly classified, with only 1.4 ± 0.5% of the high-brightness stars contaminating the population. We demonstrate that elliptical (E) and late-type spiral (Sc-Sd) galaxies can be classified using MM with an accuracy of 91.4 ± 7.8%. It is a method involving fewer ‘free parameters’ than current techniques, especially automated machine learning algorithms. The limitation of MM galaxy morphology classification based on seeing and distance is also presented. We examine various star/galaxy differentiation and galaxy morphology classification techniques commonly used today, and show that our MM techniques compare very favourably.

This article describes a method to turn astronomical imaging into a random number generator by using the positions of incident cosmic rays and hot pixels to generate bit streams. We subject the resultant bit streams to a battery of standard benchmark statistical tests for randomness and show that these bit streams are statistically the same as a perfect random bit stream. Strategies for improving and building upon this method are outlined.

In their study of the evolution of galaxies within clusters, Butcher and Oemler discovered evidence for a strong evolution in star-formation rate with redshift. Later studies confirmed this conclusion and uncovered several aspects of the effect: photometric, spectroscopic, and morphological. This article reviews a broad sample of these works and discusses selection effects, biases, and driving mechanisms that might be responsible for the changes in star-formation rate.

Filaments of galaxies are the dominant feature of modern large-scale redshift surveys. They can account for up to perhaps half of the baryonic mass budget of the Universe and their distribution and abundance can help constrain cosmological models. However, there remains no single, definitive way in which to detect, describe, and define what filaments are and their extent. This work examines a number of physically motivated, as well as statistical, methods that can be used to define filaments and examines their relative merits.

The Hirsch h-index is now widely used as a metric to compare individual researchers. To evaluate it in the context of Australian astronomy, the h-index for every member of the Astronomical Society of Australia (ASA) is found using NASA's Astrophysics Data System Bibliographic Services. Percentiles of the h-index distribution are detailed for a variety of categories of ASA members, including students. This enables a list of the top ten Australian researchers by h-index to be produced. These top researchers have h-index values in the range 53<h<77, which is less than that recently reported for the American Astronomical Society membership. We suggest that membership of extremely large consortia such as the Sloan Digital Sky Survey may partially explain the difference. We further suggest that many student ASA members with large h-index values have probably already received their Ph.D. and need to upgrade their ASA membership status. To attempt to specify the h-index distribution relative to opportunity, we also detail the percentiles of its distribution by years since Ph.D. award date. This shows a steady increase in h-index with seniority, as can be expected.

Pimbblet (2011) published an evaluation of the Hirsch h-index in the context of the Australian astronomical community. This addenda adds treatment of changes of surname to the computation of the h-index and presents derivative data on the m-index.