Mass and Distance Estimation Simulations for the Nancy Grace Roman Space Telescope Using PyLIMASS and a Case Study on Intellectual Property Frameworks in Space Collaborations
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McGee_cmcgee32_SM_AA_2025_thesis.pdf
Description
Thesis PDF
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10.29 MB
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Author(s)
McGee, Carissma
Advisor(s)
Cahoy, Kerri
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
Gravitational microlensing is a phenomenon in which a foreground star or planet briefly magnifies light from a more distant background star. This effect enables the discovery of exoplanets that are otherwise undetectable, including those orbiting faint hosts and at large separations. Microlensing is well suited to characterizing exoplanets beyond the snow line, revealing mass ratios and orbital geometries inaccessible to transit or radial velocity methods. The Nancy Grace Roman Space Telescope will carry out the Galactic Exoplanet Survey to detect thousands of microlensing events with the cadence and precision necessary for statistical exoplanet population studies. To verify Roman’s ability to meet its core science requirement, recovering the lens mass and distance in at least 40% of planetary events with better than 20% uncertainty, targeted simulations are essential. Using the pyLIMASS inference framework and Fisher matrix-based uncertainty propagation, I demonstrate that for the well-characterized event OGLE-2013-BLG-0132Lb, the lens mass can be constrained to within 18.7% uncertainty, validating the feasibility of Roman’s requirement on a case-study basis. This thesis also addresses the legal and policy foundations needed to ensure global access to these simulation tools. By advancing open-source software models and proposing a space IP framework for equitable knowledge sharing, it supports collaborative scientific infrastructure for future international space missions.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Technology and Policy Program
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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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