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Ultra Low Surface Brightness Imaging with the Dragonfly Telephoto Array

Published 21 Jan 2014 in astro-ph.IM, astro-ph.CO, astro-ph.GA, and astro-ph.SR | (1401.5473v1)

Abstract: We describe the Dragonfly Telephoto Array, a robotic imaging system optimized for the detection of extended ultra low surface brightness structures. The array consists of eight Canon 400mm f/2.8 telephoto lenses coupled to eight science-grade commercial CCD cameras. The lenses are mounted on a common framework and are co-aligned to image simultaneously the same position on the sky. The system provides an imaging capability equivalent to a 0.4m aperture f/1.0 refractor with a 2.6 deg X 1.9 deg field of view. The system has no obstructions in the light path, optimized baffling, and internal optical surfaces coated with a new generation of anti-reflection coatings based on sub-wavelength nanostructures. As a result, the array's point spread function has a factor of ~10 less scattered light at large radii than well-baffled reflecting telescopes. The Dragonfly Telephoto Array is capable of imaging extended structures to surface brightness levels below 30 mag/arcsec2 in 10h integrations (without binning or foreground star removal). This is considerably deeper than the surface brightness limit of any existing wide-field telescope. At present no systematic errors limiting the usefulness of much longer integration times has been identified. With longer integrations (50-100h), foreground star removal and modest binning the Dragonfly Telephoto Array is capable of probing structures with surface brightnesses below 32 mag/arcsec2. Detection of structures at these surface brightness levels may hold the key to solving the "missing substructure" and "missing satellite" problems of conventional hierarchical galaxy formation models. The Dragonfly Telephoto Array is therefore executing a fully-automated multi-year imaging survey of a complete sample of nearby galaxies in order to undertake the first census of ultra-faint substructures in the nearby Universe.

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