A bstract Machine Learning algorithms have played an important role in hadronic jet
classification problems. The large variety of models applied to Large Hadron Collider data …

High-energy physics is facing a daunting computing challenge with the large amount of data
expected from the HL-LHC and other future colliders. In addition, the landscape of …

Merging machine learning with the power of quantum computing holds great potential for
data-driven decision making and the development of powerful models for complex datasets …

Charged particle reconstruction or track reconstruction is one of the most crucial
components of pattern recognition in high-energy collider physics. It is known to entail …

The LUXE experiment is a new experiment in planning in Hamburg, which will study
quantum electrodynamics at the strong-field frontier. LUXE intends to measure the positron …

Nowadays, there has been a growing trend in the fields of high-energy physics (HEP) in its
both parts experimental and phenomenological studies, to incorporate machine learning …

High-energy physics is facing increasingly demanding computational challenges in real-
time event reconstruction for the near-future high-luminosity era. Using the LHCb vertex …

The reconstruction of trajectories of charged particles is a key computational challenge for
current and future collider experiments. Considering the rapid progress in quantum …

Current quantum systems have significant limitations affecting the processing of large
datasets with high dimensionality, typical of high energy physics. In the present paper …

Jet clustering or reconstruction, a procedure to identify sprays of collimated particles
originating from the fragmentation and hadronization of quarks and gluons, is a key …