activity
20152026
most citedCharged particle tracking via edge-classifying interaction networks

52 citations · 199 across the 16 of their papers we have counts for

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7 papers · 1 filter

physics.ins-det2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

Julia Gonski, Jennifer Ott, Jenni Ott +129

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…

physics.ins-det2025

Rapid Inference of Logic Gate Neural Networks for Anomaly Detection in High Energy Physics

Lino Gerlach, Elliott Kauffman, Liv Helen Våge +1

The increasing data rates and complexity of detectors at the Large Hadron Collider (LHC) necessitate fast and efficient machine learning models, particularly for rapid selection of…

physics.ins-det2025★ 1 cited

MAIA: A new detector concept for a 10 TeV muon collider

Charles Bell, Daniele Calzolari, Christian Carli +24

Muon colliders offer a compelling opportunity to explore the TeV scale and conduct precision tests of the Standard Model, all within a relatively compact geographical footprint. Th…

physics.ins-det2021★ 39 cited

Graph Neural Networks for Charged Particle Tracking on FPGAs

Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang +12

The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction…

physics.ins-det2021★ 14 cited

Test beam characterization of sensor prototypes for the CMS Barrel MIP Timing Detector

R. Abbott, A. Abreu, F. Addesa +196

The MIP Timing Detector will provide additional timing capabilities for detection of minimum ionizing particles (MIPs) at CMS during the High Luminosity LHC era, improving event re…

physics.ins-det2020★ 32 cited

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs

Aneesh Heintz, Vesal Razavimaleki, Javier Duarte +18

We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a fram…

physics.ins-det2015★ 7 cited

Run 2 Upgrades to the CMS Level-1 Calorimeter Trigger

B. Kreis, J. Berryhill, R. Cavanaugh +61

The CMS Level-1 calorimeter trigger is being upgraded in two stages to maintain performance as the LHC increases pile-up and instantaneous luminosity in its second run. In the firs…