Speaker
Description
Understanding strongly interacting matter under extreme conditions is
a common theme across relativistic astrophysics, early-Universe
cosmology, and high-energy nuclear physics. Relativistic heavy-ion
collisions offer a terrestrial laboratory for probing the quark–gluon
plasma through its collective flow. In this talk, I will present a
maximum-likelihood-estimation (MLE) framework that extracts flow
harmonics and event-plane angles directly from final-state azimuthal
distributions. The method estimates multiple flow parameters
simultaneously and provides a statistically controlled treatment of
finite-multiplicity effects. Applications to event-by-event
hydrodynamic simulations and CMS Open Data yield integrated and
differential flows consistent with conventional cumulant and
event-plane methods. We further apply MLE to flow factorization,
event-plane correlations, and mixed and higher-order harmonics,
including observables difficult to access with standard multiparticle
correlators. These results demonstrate how modern statistical
inference can sharpen our understanding of fluctuations and the
properties of strongly interacting relativistic matter.