Machine learning fully hadronic events with spectral functions

Jul 16, 2026, 10:00 AM
20m

Speaker

Kazuki Sakurai (University of Warsaw)

Description

Fully hadronic events at hadron colliders are difficult to analyse because extra QCD radiation creates many possible jet combinations and varying jet multiplicities. I will discuss how the two-point correlation spectral function can provide a compact, permutation-invariant event representation for machine-learning analyses. As a benchmark, I apply this method to gluino pair production followed by decays to top quarks and neutralinos, and show that it can improve the expected gluino-mass reach compared with standard strategies.

Author

Kazuki Sakurai (University of Warsaw)

Presentation materials