Using distributed computing to process terabytes of photometric astronomical data to determine star flux.
Within the field of Photometric Astronomy, the measurement of stellar objects involves the recording of optical images using digital capture devices such as CCDs. Precise calibration of those images to remove source of noise, and the calculation of the object Flux over a period of time is required to create high precision light curves. This research is focused on the Computer Engineering aspects of this problem, including implementation of computational models designed to improve the precision of light curve generation where the images are taken below the atmosphere. Following current research trends to take high-speed images from ground-based telescopes, a vast amount of data is now generated in photometric astronomy. This research looks at distributed computing as one technique to help process vast amounts of data, and considers how to improve light curve generation using selective image process in a technique called “Lucky Photometry”