Astronomical ideas to innovation

<p dir="ltr">For optical astronomers, bright sky backgrounds present a difficult challenge to perform accurate photometry of targets in highly sky background limited observations. In this thesis, perhaps the two most extreme examples are explored: ground based photometry of stars and satellites during the day, and the detection of faint, diffuse light from the first stars and galaxies in the Universe from low Earth orbit. The methods developed in this work to meet the challenges of studying these astrophysical sources will also be used to explore practical applications on Earth. In doing so, this thesis aims to demonstrate the value of pursuing synergies between traditional astronomy research and practical applications of astronomy. </p><p dir="ltr">In summary, the primary results of this thesis will include: </p><p dir="ltr"><br></p><ul><li>A demonstration of the use of data from the Hubble Legacy Archive to train a machine learning algorithm to accurately predict the sky surface brightness in low Earth orbit observed by the Hubble Space Telescope. These results are applied to support the SKYSURF survey which aims to map the Zodiacal Light, and determine an upper limit on the Extragalactic Background Light. </li></ul><p><br></p><ul><li>A detailed study of the photometric accuracy that can be achieved from optical daytime observations with the Huntsman Telescope Pathfinder are presented and applied to observations of the variable star Betelgeuse over a 7 month daytime survey. </li></ul><p><br></p><ul><li>The discovery of a large sample of remarkably bright Starlink satellite light curves observed during the day are presented. This is shown to be a result of considerable Earthshine contribution to optical satellite brightness during the day for the first time.</li></ul><p></p>