Probing NASA's Extragalactic Database for the Missing Mass Profile

An area of extreme interest in astrophysics is the missing mass profile. This density profile, which depicts a discrepancy between the measured and predicted mass of spiral galaxies, shows that there is unobserved mass. This is traditionally described as "dark matter," and potential candidates for this missing mass include MOND, WIMPs, and primordial black holes. The aim of this research is to explore an alternative theory for this dark matter by describing the density profile of a galaxy using general relativity's self-interaction model for gravitational acceleration and accounting for any external field effects (EFE). In order to thoroughly investigate this model, we created simulated random galaxies reflecting observed correlations among galaxy parameters and created a corresponding density profile under the influence of self-interacting gravity. In addition, through the use of Python and the NASA Extragalactic Database (NED), we created web scraping tools to collect data on clusters of galaxies to improve our model. This poster presentation will discuss the creation and results of this tool and how it is being used to improve our current understanding of gravitational self-interaction and the missing mass profile.