Automated detectionof very low surface brightness galaxiesin the Virgo cluster

Prole, Daniel; Davies, Jonathan Ivor; Keenan, Olivia; Davies, Luke J. M.

doi:10.1093/mnras/sty1021

Cited by 32 publications

(35 citation statements)

References 54 publications

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“…As a matter of fact, there already have been many surveys of dwarf galaxies outside the LG (e.g. Javanmardi et al 2016;Merritt et al 2016;Ordenes-Briceño et al 2016;Müller et al 2017a,b;Geha et al 2017;Bennet et al 2017;Danieli et al 2018;Müller et al 2018a;Greco et al 2018;Prole et al 2018;Xi et al 2018;Taylor et al 2018;Martinez-Delgado et al 2018). Such surveys would eventually enable more detailed studies of the small scale challenges of the standard galaxy formation paradigm, and in particular the relation studied in this work.…”

Section: Discussionmentioning

confidence: 99%

The Number of Dwarf Satellites of Disk Galaxies versus their Bulge Mass in the Standard Model of Cosmology

Raouf

Khosroshahi

Tavasoli

et al. 2019

ApJ

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There is a correlation between bulge mass of the three main galaxies of the Local Group (LG), i.e. M31, Milky Way (MW), and M33, and the number of their dwarf spheroidal galaxies. A similar correlation has also been reported for spiral galaxies with comparable luminosities outside the LG. These correlations do not appear to be expected in standard hierarchical galaxy formation. In this contribution, and for the first time, we present a quantitative investigation of the expectations of the standard model of cosmology for this possible relation using a galaxy catalogue based on the Millennium-II simulation. Our main sample consists of disk galaxies at the centers of halos with a range of virial masses similar to M33, MW, and M31. For this sample, we find an average trend (though with very large scatter) similar to the one observed in the LG; disk galaxies in heavier halos on average host heavier bulges and larger number of satellites. In addition, we study sub-samples of disk galaxies with very similar stellar or halo masses (but spanning a range of 2-3 orders of magnitude in bulge mass) and find no obvious trend in the number of satellites vs. bulge mass. We conclude that while for a wide galaxy mass range a relation arises (which seems to be a manifestation of the satellite number -halo mass correlation), for a narrow one there is no relation between number of satellites and bulge mass in the standard model. Further studies are needed to better understand the expectations of the standard model for this possible relation.

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Section: Discussionmentioning

confidence: 99%

The Number of Dwarf Satellites of Disk Galaxies versus their Bulge Mass in the Standard Model of Cosmology

Raouf

Khosroshahi

Tavasoli

et al. 2019

ApJ

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“…While early-type dwarf galaxies exist with Sérsic indices around one (e.g. Prole et al 2018), we are probing the field population and therefore expect that the main contribution from ETG interlopers will be from higher mass galaxies with correspondingly higher Sérsic indices. We discriminate against recovering such objects in our UDG candidate sample through the upper-limit cut in Sérsic index at n=2.5.…”

Section: Empirical Model For Massive Galaxiesmentioning

confidence: 95%

Observational properties of ultra-diffuse galaxies in low-density environments: field UDGs are predominantly blue and star forming

Prole

Burg

Hilker

et al. 2019

Monthly Notices of the Royal Astronomical Society

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Abstract While we have learnt much about ultradiffuse galaxies (UDGs) in groups and clusters, relatively little is known about them in less dense environments. More isolated UDGs are important for our understanding of UDG formation scenarios because they form via secular mechanisms, allowing us to determine the relative importance of environmentally driven formation in groups and clusters. We have used the public Kilo-Degree Survey together with the Hyper Suprime-Cam Subaru Strategic Program to constrain the abundance and properties of UDGs in the field, targeting sources with low surface brightness (24.0 ≤ $\bar{\mu }_{\mathrm{ e},r}$ ≤ 26.5) and large apparent sizes (3.0 arcsec ≤ $\bar{r}_{\mathrm{ e},r}$ ≤ 8.0 arcsec). Accounting for several sources of interlopers in our selection based on canonical scaling relations, and using an empirical UDG model based on measurements from the literature, we show that a scenario in which cluster-like red-sequence UDGs occupy a significant number of field galaxies is unlikely, with most field UDGs being significantly bluer and showing signs of localized star formation. An immediate conclusion is that UDGs are much more efficiently quenched in high-density environments. We estimate an upper limit on the total field abundance of UDGs of 8 ± 3 × 10−3 cMpc−3 within our selection range. We also compare the total field abundance of UDGs to a measurement of the abundance of H i-rich UDGs from the literature, suggesting that they occupy at least one-fifth of the overall UDG population. The mass formation efficiency of UDGs implied by this upper limit is similar to what is measured in groups and clusters.

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“…We chose to focus our comparison on four tools: SExtractor (Bertin & Arnouts 1996), which is in common use, and three recent alternatives: ProFound (Robotham et al 2018), NoiseChisel + Segment (Akhlaghi & Ichikawa 2015), and MTObjects (Teeninga et al 2013. We chose to exclude several other source-extraction tools from this comparison for various reasons, notably DeepScan (Prole et al 2018), which is dependent on the use of another tool (such as SExtractor) to produce an initial mask; and AstroDendro (Robitaille et al 2013a), which was prohibitively slow to run on large images.…”

Section: Compared Toolsmentioning

confidence: 99%

Optimising and comparing source-extraction tools using objective segmentation quality criteria

Haigh

Chamba

Venhola

et al. 2021

A&A

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Context. With the growth of the scale, depth, and resolution of astronomical imaging surveys, there is increased need for highly accurate automated detection and extraction of astronomical sources from images. This also means there is a need for objective quality criteria, and automated methods to optimise parameter settings for these software tools. Aims. We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on evaluating performance in situations that present challenges for detection. For example, faint and diffuse galaxies; extended structures, such as streams; and objects close to bright sources. Furthermore, we develop an automated method to optimise the parameters for the above tools. Methods. We present four different objective segmentation quality measures, based on precision, recall, and a new measure for the correctly identified area of sources. Bayesian optimisation is used to find optimal parameter settings for each of the four tools when applied to simulated data, for which a ground truth is known. After training, the tools are tested on similar simulated data in order to provide a performance baseline. We then qualitatively assess tool performance on real astronomical images from two different surveys. Results. We determine that when area is disregarded, all four tools are capable of broadly similar levels of detection completeness, while only NoiseChisel and MTObjects are capable of locating the faint outskirts of objects. MTObjects achieves the highest scores on all tests for all four quality measures, whilst SExtractor obtains the highest speeds. No tool has sufficient speed and accuracy to be well suited to large-scale automated segmentation in its current form.

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Automated detectionof very low surface brightness galaxiesin the Virgo cluster

Cited by 32 publications

References 54 publications

The Number of Dwarf Satellites of Disk Galaxies versus their Bulge Mass in the Standard Model of Cosmology

The Number of Dwarf Satellites of Disk Galaxies versus their Bulge Mass in the Standard Model of Cosmology

Observational properties of ultra-diffuse galaxies in low-density environments: field UDGs are predominantly blue and star forming

Optimising and comparing source-extraction tools using objective segmentation quality criteria

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