In high-energy proton–proton collisions, thousands of particles are produced in a tiny volume. Surprisingly, these systems can exhibit patterns of fluid-like behaviour, similar to those in heavy-ion collisions or neutron stars, where a quark–gluon plasma (QGP) is formed. This project studies such collective effects using particle correlations at the STAR experiment, exploring whether even the smallest systems can behave like a strongly interacting liquid.
Outline:
1. Learn the physics of hadronic collisions (pp, pA, AA) and collectivity in QCD.
2. Study observables sensitive to collective behaviour, focusing on momentum correlations and radial flow.
3. Analyse particle momentum distributions using simulations and/or RHIC data.
4. Investigate event properties (activity, topology) and their influence on correlations.
5. Apply Machine Learning / Deep Learning for reconstruction and detector corrections.