A Hubble Space Telescope Direct Imaging Investigation of Extrasolar Planets
Student: Katrina Bynum and Blake Mino
Major: Math and Astronomy
Mentors: Dr. Joe Carson
Department: Physics and Astronomy
A Hubble Space Telescope Direct Imaging Investigation of Extrasolar Planets
Principal Component Analysis (PCA) is a machine learning technique that isolates prominent parts of an image to allow for their subtraction. In particular, we used PCA to process infrared data from the Hubble Space Telescope's Near Infrared Camera and Multi-object Spectrometer (NICMOS) to directly image exoplanets by subtracting the host star's overwhelming starlight, in turn revealing a potential exoplanet signal. One main challenge associated with directly imaging planets is determining whether or not the detected signal is a planet or a dim background field star. Here, we study the average field star density as a function of magnitude around the star 51 Eridani to inform the possibility of a detected signal being a background star.