Reyna Wood
Pronouns: she/her
Research Mentor(s): Enrico Landi, Professor
Research Mentor School/College/Department: Climate and Space Sciences and Engineering, College of Engineering
Presentation Date: Thursday, April 22, 2021
Session: Session 6 (4pm-4:50pm)
Breakout Room: Room 15
Presenter: 4
Abstract
Though the phenomenon of solar wind has been studied for years and we have data regarding its composition, velocity, and temperature, among other things, there is still much to learn about its evolution and how its internal forces interact. Our team aimed to create an empirical model that can accurately predict the behaviour of variables such as temperature and velocity in the solar wind as a function of distance. We created two different models, one using a Markov Chain Monte Carlo system, and another using gradient descent. By repetition and comparing results against a database of previously recorded solar wind measurements, parameters in a starting equation are allowed to randomly change, and the best fitting model is iteratively chosen. These results will not only give insight into the evolution of solar wind, but they will pave the way for other, more advanced techniques to produce more accurate models. Additionally, understanding the evolution of solar wind will provide guidance on the design of instrumentation to be launched aboard Solar Orbiter satellites.
Authors: Reyna Wood, Horacio Moreno Montanes, Enrico Landi
Research Method: Computer Programming
