Speaker
Description
The study of Vector Boson Scattering (VBS) at LHC provides a unique window into the electroweak symmetry breaking mechanism. The polarization of the vector bosons enables precision tests of the heart Standard Model at the TeV scale, additionally sensibile to new physics. The highest experimental sensitivity can be achieved in the boosted regime, where the bosons are produced with large transverse momentum, and decay hadronically. However, the resulting collimated decay products are reconstructed as single large-R jets, posing a major challenge for event reconstruction and signal discrimination. In this talk we investigate quantum machine learning strategies for polarization reconstruction, particularly based on Quantum Convolutional Neural Network and Quantum Variational Algorithms.
| Sessions | Quantum Machine Learning: |
|---|---|
| Invited | No |