Gabriel is originally from Boston but grew up on Maui. He graduated as a homeschooled student and currently attends the University of Hawai’i at Manoa as an undergraduate pursuing a Bachelor of Science in Physics and a minor in Computer Science. He is interested in computational physics, quantum mechanics, astronomy, and mathematics, and he is currently exploring detection of neutrinos.
Home Island: Maui
High School: Homeschooled
Institution when accepted: University of Hawai’i at Manoa
Project Site: Daniel K. Inouye Solar Telescope: NSO/DKIST, Pukalani, Maui
Mentor: Tom Schad
Project Title: Informing DKIST Targeting Decisions for Optimal Coronal Observations Based on Solar and Sky Conditions
Abstract:
The National Science Foundation’s Daniel K. Inouye Solar Telescope (DKIST) routinely targets the faint solar corona using coronagraphic methods. The quality of such observations can be severely limited by sunlight scattered by particles in our atmosphere, i.e. air molecules, aerosols, and water droplets. The aerosol group is the major contributor to near-sun sky brightness. Coronal light, which is a million times dimmer than the black body radiation emitted by the solar disk, is difficult to measure when the brightness of light scattered by our atmosphere exceeds that of the corona. Our project aims to understand how atmospheric and aerosol properties are related to the near-sun brightness. Here, we utilize the LibRadtran modeling package to perform radiative transfer calculations. This sky model can then be combined with synthetic calculations of coronal intensity which are computed using dedicated magnetohydrodynamic models of the sun, such as PSI, and with formulations for Thomson scattering by coronal electrons. Combining solar and sky models has major implications in the field of solar astronomy and is ultimately needed to accurately determine “clear-sky” conditions for optimal coronal observations at DKIST, and for other coronagraphs. Simulations of near-sun sky brightness are used to predict acceptable margins for imaging the corona. We also explore the process of integrating over the entire visible spectrum to produce visible light images to predict what the sky might look like to the human eye, which is useful for real-time comparisons of site conditions with simulated sky conditions.