Workshops

Machine learning (ML) has been recently used as a very effective tool for the study and prediction of data in various fields of physics, from statistical physics to theoretical high energy physics.

The emphasis will be on the study of dileptons, heavy-quark and quarkonium, less explored in this energy domain. The status on hadronic bulk observables, a crucial tool for the detection of critical phenomena, will also be discussed

This workshop will explore what aspects of QCD in particular can manifest in nuclei at an EIC, what measurements would be sensitive to these manifestations, and what design parameters are needed to make such measurements possible.

Heavy flavor (HF) quarks are excellent probes for the properties of the QGP created in ultra-relativistic heavy-ion collisions.

To understand the measurable content of QCD, hadron spectroscopy is valuable and time-honored tool.