In this lab, students will get a chance to explore computational aspects in the acquisition and processing of astronomical image data. After a hands-on introduction to practical and technical aspects of astrophotography, we will use astronomical equipment to capture data on deep sky objects such as nebulae and galaxies. Accounting for the weather, daylight, and moon situation, in this first phase of the lab we may meet on campus late in the evening to collect data that will be used in a second phase. In the second phase of the lab, students will form groups that will address key tasks in astronomical image processing, such as image registration to automatically align different exposures, image stacking to improve the signal-to-noise ratio, multi narrow-band color composition, strectching/rescaling of the histogram, plate-solving to identify sky coordinates in a given image, classification of deep sky objects, etc. Solving these tasks requires the development of python code based on libraries such as astropy, pyTorch, scikit-image, or Pillow.

Interested students are required to participate in an initial information event, and formally register for the lab until October 30th.