Date of Award

Spring 4-13-2022

Degree Type

Thesis

Department

History

First Advisor

Nick Wilding

Second Advisor

Jared Poley

Abstract

This paper focuses on a specific technology for deblurring astronomical images. Data are collected as digital matrices of image pixels. The technology reconstructs the object via computational manipulation of the blurred image. Dr Stuart Jefferies, Professor, Department of Physics and Astronomy, GSU, along with several colleagues developed a sequence of techniques over three decades, based on a single, powerful idea. Supported for a time by the US Air Force AMOS project and drawing on compatible ideas from physics, engineering, mathematics and computer science, they learned to extract more and more useful information from the raw data. Jefferies took the idea of blind deconvolution and, with his network, developed it into a powerful and adaptable tool for scientific knowledge making and an efficient and effective applied technology for an important national security mission.

We have located this work in the very long tradition of astronomical image making and in the more recent context of big science projects funded by government for military necessities. Galileo is celebrated as the first person to publish hand-drawn images from observing the night sky through a telescope. Indeed, hand-drawings were the only way to convey images of the night sky for over two hundred years, until the development of photography in the mid-1800s. Photography dominated astronomical image making for another hundred years. Today, we live in an era of huge sets of digital data. The infrastructure required to generate, transmit and analyze such data requires huge budgets. Hence the need for public funding.

In addition to scientific knowledge making and applied technology development, we noted that an important legacy of big, government funded, science project can be the building of institutions that outlive the original project, but carry-on related work. The GSU Imaging Innovation Hub, championed by Jefferies, follows that tradition.

DOI

https://doi.org/10.57709/28689649

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