Just as surveys form an important component of research in areas as diverse as economics, medicine, and zoology, astronomers use surveys to provide deep insights into the properties of stars and galaxies. And with some astronomical surveys containing data for billions of stars and galaxies, astronomers have a wealth of data at hand to investigate why today's stars and galaxies look the way they do. A major challenge, however, is distilling all this data into useful information. Our team researches new ways of interrogating our astronomical surveys to gain new insights into how today's galaxies formed and evolved.
All massive galaxies contain, at their centres, a supermassive black hole. Depending on the size of their host galaxies, these black holes have masses of a few million to a few billion times the mass of our Sun. These black holes grow by accreting gas and dust from their immediate surroundings. However, astronomers have little understanding of what triggers this accretion. We can use surveys of growing black holes to identify the galactic conditions that promotes their growth, but this is hampered by the limited sensitivity of our telescopes. My collaborators and I develop advanced statistical techniques to overcome these limitations and gain insights into the causes of supermassive black hole growth.
Survey astronomy is in the process of undergoing major revolution. Traditional astronomical surveys took a single snapshot of the sky, providing a static "photograph" of the Universe. The next generation of surveys, however, are repeatedly surveying the sky night after night to provide what are, in a very real sense, the first "movies" of the Universe. These surveys will identify unprecendent numbers of so-called transient events, including stars being ripped apart by black holes, stellar explosions, and many other previously unseen phenomena. As members of the Gravitational-wave Optical Transient Observer (GOTO) collaboration, my colleagues and I are researching how to process and analyse the wealth of data collected by this new breed of time-domain astronomical surveys.
Today, the field of astronomy is not alone in the collection of vast quantities of digital data. Indeed, there is barely any sector of the world's economy that has not been transformed by the availability of large amounts of data. However, many businesses and organisations - especially those in developing economies - lack the resources to make full use of such "Big Data". With assistance from the Global Challenges Research Fund (GCRF), the technologies we develop to process and analyse our sky survey data are being re-purposed to educate and train Thai students in the analysis of large datasets. Today, these students are developing machine-learning algorithms to help solve the data-related problems of Thai businesses in sectors as diverse as tourism, food retail, and aviation.