3 papers
hep-ph2026
Machine learning fully hadronic events with spectral functions
Mohammad Mahdi Altakach, Hadi Hassan, Sabine Kraml +2
Characterising fully hadronic events is a difficult task at hadron colliders. Signal jets from the hard process are mingled with an arbitrary number of ISR and FSR jets, leading to…
hep-ph2025
Machine learning-based b-jet tagging in collisions at TeV
Hadi Hassan, Neelkamal Mallick, D. J. Kim
Studying heavy-flavor jets in collision is important since they can test pQCD calculations and be used as a reference for heavy-ion collisions. Jets in this analysis are recon…
hep-ph2025
Charm-hadron reconstruction through three body decay in hadronic collisions using Machine Learning
Neelkamal Mallick, Hadi Hassan, D. J. Kim
Studies of heavy-quark (charm and beauty) production in hadronic and nuclear collisions provide excellent testing grounds for the theory of strong interaction, quantum chromodynami…