10 research outputs found

    Automated extraction of low surface brightness sources and the physical nature of ultra-diffuse galaxies

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    As the size and depth of astronomical data improves, so must the software with which we use to extract sources from it. In this thesis, I describe a new software package, DeepScan, which I have written & designed to offer improvements over contemporary software packages such as SExtractor for detecting extended low surface brightness (LSB) features, particularly to avoid issues of excessive segment fragmentation. I demonstrate the technique by applying it over a 5 degree2 portion of the Next-Generation Virgo Survey data to reveal 53 LSB galaxies that are candidate cluster members based on their sizes and colours; 30 of which are new detections. The final sample have extremely low surface brightness (26:0 _ __e _ 28:5) and low stellar masses (106:3_0:5M_), making them some of the faintest known dwarf galaxies in the Virgo Cluster. Improved detection and measurement techniques are crucial for identifying large samples of LSB galaxies, which are important for characterising the formation mechanisms of ultra-diffuse galaxies (UDGs): large, LSB galaxies with mysterious origins. In this thesis I have used the Kilo-Degree Survey together with the Hyper Suprime- Cam Subaru Strategic Program to measure the colours and abundances of UDGs in the field, where they are expected to form preferentially via secular mechanisms compared with those in denser environments. I show that a scenario in which cluster-like red sequence UDGs occupy a large fraction of field galaxies is unlikely, with most field UDGs being significantly bluer. I also estimate an upper-limit on the total field abundance of UDGs of 8_3_1

    Automated detectionof very low surface brightness galaxiesin the Virgo cluster

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    We report the automatic detection of a new sample of very low surface brightness (LSB) galaxies, likely members of the Virgo cluster. We introduce our new software, {\tt DeepScan}, that has been designed specifically to detect extended LSB features automatically using the DBSCAN algorithm. We demonstrate the technique by applying it over a 5 degree2^2 portion of the Next-Generation Virgo Survey (NGVS) data to reveal 53 low surface brightness galaxies that are candidate cluster members based on their sizes and colours. 30 of these sources are new detections despite the region being searched specifically for LSB galaxies previously. Our final sample contains galaxies with 26.0≤⟨μe⟩≤28.526.0\leq\langle \mu_{e}\rangle\leq28.5 and 19≤mg≤2119\leq m_{g}\leq21, making them some of the faintest known in Virgo. The majority of them have colours consistent with the red sequence, and have a mean stellar mass of 106.3±0.5M⊙10^{6.3\pm0.5} M_{\odot} assuming cluster membership. After using {\tt ProFit} to fit S\'ersic profiles to our detections, none of the new sources have effective radii larger than 1.5 Kpc and do not meet the criteria for ultra-diffuse galaxy (UDG) classification, so we classify them as ultra-faint dwarfs.Comment: 16 pages, 14 figures, Accepted for publication in MNRAS 201
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