Exploring Analog Gravity Experiments with Novel Theoretical and Phenomenological Tools

01/05/2026 to 30/04/2028

This project introduces a generalized theoretical model extending the analog black-hole vortex framework, with deviation parameters derived from first principles. It will serve as a strong theoretical basis for experimental studies. I will then develop statistical tools to analyze data from laboratory black-hole analogs and use them to constrain the model’s free parameters. Methods include Bayesian inference (MCMC), machine learning (neural networks), and a semi-analytical inverse technique from earlier work. These analyses aim to provide new insights into the link between tabletop analogs and astrophysical black holes, advancing laboratory studies of gravity.