2 citations · 4 across the 7 of their papers we have counts for
8 papers
Exploring new directions in enhancing the ACTS parameter optimization suite
Chance LaVoie, Qi Bin Lei, Rocky Bala Garg +1
Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are commonly tuned through expert i…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
MuCol Milestone Report No. 7: Consolidated Parameters
Rebecca Taylor, Antoine Chancé, Dario Augusto Giove +459
This document is comprised of a collection of consolidated parameters for the key parts of the muon collider. These consolidated parameters follow on from the October 2024 Prelimin…
The Muon Collider
Carlotta Accettura, Simon Adrian, Rohit Agarwal +450
Muons offer a unique opportunity to build a compact high-energy electroweak collider at the 10 TeV scale. A Muon Collider enables direct access to the underlying simplicity of the…
Auto-tuning capabilities of the ACTS track reconstruction suite
Corentin Allaire, Rocky Bala Garg, Hadrien Benjamin Grasland +5
The reconstruction of charged particle trajectories is a crucial challenge of particle physics experiments as it directly impacts particle reconstruction and physics performances.…
Training and Onboarding initiatives in High Energy Physics experiments
S. Hageboeck, A. Reinsvold Hall, N. Skidmore +16
In this paper we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fa…
Potentiality of automatic parameter tuning suite available in ACTS track reconstruction software framework
Rocky Bala Garg, Corentin Allaire, Andreas Salzburger +3
Particle tracking is among the most sophisticated and complex part of the full event reconstruction chain. A number of reconstruction algorithms work in a sequence to build these t…
Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC
Simon Akar, Mohamed Elashri, Rocky Bala Garg +6
We are studying the use of deep neural networks (DNNs) to identify and locate primary vertices (PVs) in proton-proton collisions at the LHC. Earlier work focused on finding primary…