A Digital Quantum Algorithm for Jet Clustering in High-Energy Physics
arXiv:2101.05618
Abstract
Experimental High-Energy Physics (HEP), especially the Large Hadron Collider (LHC) programme at the European Organization for Nuclear Research (CERN), is one of the most computationally intensive activities in the world. This demand is set to increase significantly with the upcoming High-Luminosity LHC (HL-LHC), and even more in future machines, such as the Future Circular Collider (FCC). As a consequence, event reconstruction, and in particular jet clustering, is bound to become an even more daunting problem, thus challenging present day computing resources. In this work, we present the first digital quantum algorithm to tackle jet clustering, opening the way for digital quantum processors to address this challenging problem. Furthermore, we show that, at present and future collider energies, our algorithm has comparable, yet generally lower complexity relative to the classical state-of-the-art clustering algorithm.
References in corpus (8)
- An Introduction to PYTHIA 8.2
- Dispelling the N^3 myth for the Kt jet-finder
- Quantum random access memory
- Quantum algorithms for supervised and unsupervised machine learning
- A Quantum Algorithm for Finding the Minimum
- Quantum Algorithms for Jet Clustering
- Quantum machine learning for data scientists
- Adiabatic Quantum Algorithm for Multijet Clustering in High Energy Physics