Hubble Space Telescope Images of Magellanic Cloud Planetary Nebulae: Data and Correlations across Morphological Classes

The morphology of planetary nebulae (PNs) provides an essential tool for understanding their origin and evolution, since it reflects both the dynamics of the gas ejected at the tip of the asymptotic giant branch phase and the central-star energetics. Here we study the morphology of 27 Magellanic Cloud planetary nebulae (MCPNs) and present an analysis of their physical characteristics across morphological classes. Similar studies have been successfully carried out for Galactic PNs but were compromised by the uncertainty of individual PN distances. We present our own Hubble Space Telescope (HST) Faint Object Camera (FOC) images of 15 MCPNs acquired through a narrowband [O III] λ5007 filter. We use the Richardson-Lucy deconvolution technique on these pre-COSTAR images to achieve post-COSTAR quality. Three PNs imaged before and after COSTAR confirm the high reliability of our deconvolution procedure. We derive morphological classes, dimensions, and surface photometry for all of these PNs. We have combined this sample with HST/PC1 images of 15 MCPNs, three of which are in common with the FOC set acquired by Dopita et al., to obtain the largest MCPNs sample ever examined from the morphological viewpoint. By using the entire database, supplemented with published data from the literature, we have analyzed the properties of the MCPNs and compared them to a typical, complete Galactic sample. Morphology of the MCPNs is then correlated with PN density, chemistry, and evolution

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde