The influence of diffuse scattered light II. Observations of galaxy haloes and thick discs and hosts of BCGs

Studies of deep photometry of galaxies have presented discoveries of excess light in surface-brightness and colour profiles at large radii in the form of diffuse faint haloes and thick discs. In a majority of the cases, it has seemed necessary to use exotic stellar populations or alternative physical solutions to explain the excess. Few studies have carefully scrutinized the role of scattered light in this context. I explore the influence of scattered light on ground-based observations of haloes and thick discs around edge-on galaxies, haloes around face-on disc galaxies, host galaxies around blue compact galaxies (BCGs), and haloes around elliptical galaxies. Surface-brightness structures of all considered types of galaxies are modelled and analysed to compare scattered-light haloes and thick discs with measurements. I simulate the influence of scattered light and accurate sky subtraction on simplified S\'ersic-type and face-on disc galaxy models. All galaxy models are convolved with both lower-limit and brighter point spread functions (PSFs); for a few galaxies it was possible to use dedicated PSFs. The results show bright scattered-light haloes and high amounts of red excess at large radii and faint surface brightnesses for nearly all types of galaxies; exceptions are the largest elliptical-type galaxies where the influence of scattered light is smaller. Studies have underestimated the role of scattered light to explain their surface-brightness profiles. My analysis shows surface-brightness profiles that include scattered light that are very similar to and overlap measurements at all radii. The derivation of physical properties of haloes, thick discs, and BCG hosts from diffuse data is misleading since accurate and radially extended PSFs are non-existent. Significantly improved analyses that include new measurements of PSFs are required to study diffuse haloes further.Comment: 18 pages, 11 figures, and 15 pages + 11 figures in appendix, accepted for publication in A&

The influence of diffuse scattered light I. The PSF and its role to observations of the edge-on galaxy NGC 5907

All telescopes and instruments are to some degree affected by scattered light. It is possible to estimate the amount of such scattered light, and even correct for it, with a radially extended point spread function (PSF). The outer parts of the PSF have only rarely been determined, since they are faint and therefore difficult to measure. A mostly complete overview of existing properties and measurements of radially extended PSFs is presented, to both show their similarities and to indicate how bright extended objects can be used to measure the faintest regions. The importance of the far wings of the PSF and their possible temporal variations are demonstrated in three edge-on galaxy models. The same study is applied to the first edge-on galaxy where earlier observations reveal a halo, NGC 5907. All PSFs were collected in two diagrams, after they were offset or normalized, when that was possible. Surface-brightness structures of edge-on galaxies were modelled and analysed to study scattered-light haloes that result with an exponential disc. The models were convolved with both a lower-limit PSF and a more average PSF. The PSF of the observed data could be used in the case of NGC 5907. The comparison of the PSFs demonstrates a lower-limit $r^{-2}$ power-law decline at larger radii. The analysis of the galaxy models shows that also the outer parts of the PSF are important to correctly model and analyse observations and, in particular, fainter regions. The reassessed analysis of the earlier measurements of NGC 5907 reveals an explanation for the faint halo in scattered light, within the quoted level of accuracy.Comment: 17 pages, 9 figures, Astronomy & Astrophysics, in pres

The Australian Space Eye: studying the history of galaxy formation with a CubeSat

The Australian Space Eye is a proposed astronomical telescope based on a 6U CubeSat platform. The Space Eye will exploit the low level of systematic errors achievable with a small space based telescope to enable high accuracy measurements of the optical extragalactic background light and low surface brightness emission around nearby galaxies. This project is also a demonstrator for several technologies with general applicability to astronomical observations from nanosatellites. Space Eye is based around a 90 mm aperture clear aperture all refractive telescope for broadband wide field imaging in the i and z bands.Comment: 19 pages, 14 figures, submitted for publication as Proc. SPIE 9904, 9904-56 (SPIE Astronomical Telescopes & Instrumentation 2016

Future Prospects: Deep Imaging of Galaxy Outskirts using Telescopes Large and Small

The Universe is almost totally unexplored at low surface brightness levels. In spite of great progress in the construction of large telescopes and improvements in the sensitivity of detectors, the limiting surface brightness of imaging observations has remained static for about forty years. Recent technical advances have at last begun to erode the barriers preventing progress. In this Chapter we describe the technical challenges to low surface brightness imaging, describe some solutions, and highlight some relevant observations that have been undertaken recently with both large and small telescopes. Our main focus will be on discoveries made with the Dragonfly Telephoto Array (Dragonfly), which is a new telescope concept designed to probe the Universe down to hitherto unprecedented low surface brightness levels. We conclude by arguing that these discoveries are probably only scratching the surface of interesting phenomena that are observable when the Universe is explored at low surface brightness levels.Comment: 27 pages, 10 figures, Invited review, Book chapter in "Outskirts of Galaxies", Eds. J. H. Knapen, J. C. Lee and A. Gil de Paz, Astrophysics and Space Science Library, Springer, in pres

Outskirts of Nearby Disk Galaxies: Star Formation and Stellar Populations

The properties and star formation processes in the far-outer disks of nearby spiral and dwarf irregular galaxies are reviewed. The origin and structure of the generally exponential profiles in stellar disks is considered to result from cosmological infall combined with a non-linear star formation law and a history of stellar migration and scattering from spirals, bars, and random collisions with interstellar clouds. In both spirals and dwarfs, the far-outer disks tend to be older, redder and thicker than the inner disks, with the overall radial profiles suggesting inside-out star formation plus stellar scattering in spirals, and outside-in star formation with a possible contribution from scattering in dwarfs. Dwarf irregulars and the far-outer parts of spirals both tend to be gas dominated, and the gas radial profile is often non-exponential although still decreasing with radius. The ratio of H-alpha to far-UV flux tends to decrease with lower surface brightness in these regions, suggesting either a change in the initial stellar mass function or the sampling of that function, or a possible loss of H-alpha photons.Comment: 20 pages, 8 figures, Invited review, Book chapter in "Outskirts of Galaxies", Eds. J. H. Knapen, J. C. Lee and A. Gil de Paz, Astrophysics and Space Science Library, Springer, in pres

Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies

The accurate modelling of the Point Spread Function (PSF) is of paramount importance in astronomical observations, as it allows for the correction of distortions and blurring caused by the telescope and atmosphere. PSF modelling is crucial for accurately measuring celestial objects' properties. The last decades brought us a steady increase in the power and complexity of astronomical telescopes and instruments. Upcoming galaxy surveys like Euclid and LSST will observe an unprecedented amount and quality of data. Modelling the PSF for these new facilities and surveys requires novel modelling techniques that can cope with the ever-tightening error requirements. The purpose of this review is three-fold. First, we introduce the optical background required for a more physically-motivated PSF modelling and propose an observational model that can be reused for future developments. Second, we provide an overview of the different physical contributors of the PSF, including the optic- and detector-level contributors and the atmosphere. We expect that the overview will help better understand the modelled effects. Third, we discuss the different methods for PSF modelling from the parametric and non-parametric families for ground- and space-based telescopes, with their advantages and limitations. Validation methods for PSF models are then addressed, with several metrics related to weak lensing studies discussed in detail. Finally, we explore current challenges and future directions in PSF modelling for astronomical telescopes.Comment: 63 pages, 14 figures. Submitte

Classification and Segmentation of Galactic Structuresin Large Multi-spectral Images

Extensive and exhaustive cataloguing of astronomical objects is imperative for studies seeking to understand mechanisms which drive the universe. Such cataloguing tasks can be tedious, time consuming and demand a high level of domain specific knowledge. Past astronomical imaging surveys have been catalogued through mostly manual effort. Immi-nent imaging surveys, however, will produce a magnitude of data that cannot be feasibly processed through manual cataloguing. Furthermore, these surveys will capture objects fainter than the night sky, termed low surface brightness objects, and at unprecedented spatial resolution owing to advancements in astronomical imaging. In this thesis, we in-vestigate the use of deep learning to automate cataloguing processes, such as detection, classification and segmentation of objects. A common theme throughout this work is the adaptation of machine learning methods to challenges specific to the domain of low surface brightness imaging.We begin with creating an annotated dataset of structures in low surface brightness images. To facilitate supervised learning in neural networks, a dataset comprised of input and corresponding ground truth target labels is required. An online tool is presented, allowing astronomers to classify and draw over objects in large multi-spectral images. A dataset produced using the tool is then detailed, containing 227 low surface brightness images from the MATLAS survey and labels made by four annotators. We then present a method for synthesising images of galactic cirrus which appear similar to MATLAS images, allowing pretraining of neural networks.A method for integrating sensitivity to orientation in convolutional neural networks is then presented. Objects in astronomical images can present in any given orientation, and thus the ability for neural networks to handle rotations is desirable. We modify con-volutional filters with sets of Gabor filters with different orientations. These orientations are learned alongside network parameters during backpropagation, allowing exact optimal orientations to be captured. The method is validated extensively on multiple datasets and use cases.We propose an attention based neural network architecture to process global contami-nants in large images. Performing analysis of low surface brightness images requires plenty of contextual information and local textual patterns. As a result, a network for processing low surface brightness images should ideally be able to accommodate large high resolu-tion images without compromising on either local or global features. We utilise attention to capture long range dependencies, and propose an efficient attention operator which significantly reduces computational cost, allowing the input of large images. We also use Gabor filters to build an attention mechanism to better capture long range orientational patterns. These techniques are validated on the task of cirrus segmentation in MAT-LAS images, and cloud segmentation on the SWIMSEG database, where state of the art performance is achieved.Following, cirrus segmentation in MATLAS images is further investigated, and a com-prehensive study is performed on the task. We discuss challenges associated with cirrus segmentation and low surface brightness images in general, and present several tech-niques to accommodate them. A novel loss function is proposed to facilitate training of the segmentation model on probabilistic targets. Results are presented on the annotated MATLAS images, with extensive ablation studies and a final benchmark to test the limits of the detailed segmentation pipeline.Finally, we develop a pipeline for multi-class segmentation of galactic structures and surrounding contaminants. Techniques of previous chapters are combined with a popu-lar instance segmentation architecture to create a neural network capable of segmenting localised objects and extended amorphous regions. The process of data preparation for training instance segmentation models is thoroughly detailed. The method is tested on segmentation of five object classes in MATLAS images. We find that unifying the tasks of galactic structure segmentation and contaminant segmentation improves model perfor-mance in comparison to isolating each task