I’m an independent data researcher. For the past few months, I've been approaching the missing mass problem in galaxies purely from a data and systems-architecture perspective (treating spatial topology as a discrete lattice without adding free parameters).
I took the raw SLACS dataset (100 strong gravitational lenses) and the SPARC database (175 galaxies) and wrote a Python script to see if a geometric boundary threshold could predict the kinematics strictly from the visible baryonic mass, with zero curve-fitting.
To my surprise, the model output an R^2=0.9917 for the Einstein Ring radii, and R^2=0.9150 for global galactic velocities.
I know how astronomical claims usually go here, which is why I’m not asking anyone to just believe the theory. I put the raw datasets and the Python verification scripts in the GitHub repo.
I would genuinely appreciate it if anyone here with a background in data science, statistics, or astrophysics could run the code, tear it apart, and tell me where my methodology or assumptions fail.
For those interested in the underlying math and queueing-theory derivations, the full pre-print paper is available on Zenodo: https://doi.org/10.5281/zenodo.21920452