December 10, 2021
Europe/Zurich timezone

Development of quantum machine learning algorithms to study Higgs boson decays with the LHCb detector

Dec 10, 2021, 10:50 AM
5m
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Speaker

Donatella Lucchesi

Description

Quantum Machine Learning (QML) algorithms are proposed as an exciting prospective application of quantum technologies. Problems that are classically hard to compute have potential to be solved faster by such new algorithms. The LHCb collaboration has already made a first step by studying the identification of b and b-bar jets showing new possibilities opened by these algorithms.
This new project proposes to demonstrate how QML can improve the determination of the Higgs boson decay rates to b and c jets by exploiting the different b and c jet sub-structure.

CERN group or section submitting a project proposal quantum computing and algorithms

Primary authors

Alessio Gianelle (Universita e INFN, Padova (IT)) Davide Nicotra (Universita e INFN, Padova (IT)) Donatella Lucchesi Carlos Vazquez Sierra (CERN) Davide Zuliani (Universita e INFN, Padova (IT)) Eduardo Rodrigues (University of Liverpool (GB)) Jacco Andreas De Vries (Universiteit Maastricht (NL)) Lorenzo Sestini (Universita e INFN, Padova (IT))

Presentation materials