Title: Learning from all hits/particles – Machine Learning at cosmic-ray/collider Frontier

Speaker: Professor Manqi Ruan (Institute of High Energy Physics, Chinese Academy of Sciences)

Time: 14:00pm, July 10, 2026

Location: 3-402, PMO Xianlin Campus

Abstract: The machine learning technologies could efficiently extract information from data, and significantly boost the performance and discovery power of large science facilities.

Using ParticleNet or ParticleTransformer, the significance of standard candle – crab nebula - could be improved by 50% to 3 times at the LHASSO experiments. Apply the similar methodology to the collider experiments, including both LEP experimental data and simulated data for future Higgs factories, we observe 3-4 folds improvements on benchmark physics measurements.

We also observe significant scaling behavior that describes the emerge and saturation of performance, which could be used to diagnosis the AI behavior and to quantify/control the effect of data-MC discrepancy.