From Stars to Waves: Non-deterministic Inference of Microlensed Gravitational Waves
This episode discusses a paper on non-deterministic inference of microlensed gravitational waves. Instead of tracking every individual star causing lensing interference, researchers use surrogate parameters and AI—specifically neural spline flows—to model probability distributions. This method allows scientists to map stellar densities and mass distributions in distant galaxies.