Automated detection of very Low Surface Brightness galaxies in the Virgo Cluster

TL;DR

This paper introduces DeepScan, an automated software using DBSCAN to detect very low surface brightness galaxies in the Virgo Cluster, revealing 53 candidates including 30 new detections, and classifies them as ultra-faint dwarfs.

Contribution

The paper presents a novel automated detection method, DeepScan, specifically designed for low surface brightness galaxies, applied to Virgo data to identify new ultra-faint dwarf candidates.

Findings

Detected 53 low surface brightness galaxy candidates in Virgo.

Identified 30 new low surface brightness galaxies not previously cataloged.

Classified all detected galaxies as ultra-faint dwarfs, not ultra-diffuse galaxies.

Abstract

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 degree$^2$ 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 $26.0\leq\langle \mu_{e}\rangle\leq28.5$ and $19\leq m_{g}\leq21$, 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 $10^{6.3\pm0.5} M_{\odot}$ 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.