52 citations · 199 across the 16 of their papers we have counts for
21 papers
AI Acceleration of Muon Collider R&D: A Report from the AI4MuC Workshop
J. Scott Berg, David Bizzozero, Tulika Bose +27
A Muon Collider is one of the most attractive routes to multi-TeV lepton collisions, but it requires the accelerator and detector communities to solve a tightly coupled set of prob…
Reconfigurable On-Chip AI for Particle Physics Detectors with Logic Neural Networks
Mila Bileska, Lino Gerlach, Jennet Dickinson +4
On-device machine learning is increasingly important in applications where extreme data rates or resource constraints make centralized processing infeasible. Logic neural networks…
WARP Logic Neural Networks
Lino Gerlach, Thore Gerlach, Liv Våge +2
Fast and efficient AI inference is increasingly important, and recent models that directly learn low-level logic operations have achieved state-of-the-art performance. However, exi…
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…
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…
Real-time Anomaly Detection for Liquid Argon Time Projection Chambers
Seokju Chung, Jack Cleeve, Akshay Malige +4
We present a real-time anomaly detection framework for liquid argon time projection chambers (LArTPCs), targeting applications in particle physics experiments such as the Short Bas…
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…
Knowledge Distillation for Anomaly Detection
Adrian Alan Pol, Ekaterina Govorkova, Sonja Gronroos +5
Unsupervised deep learning techniques are widely used to identify anomalous behaviour. The performance of such methods is a product of the amount of training data and the model siz…
Symbolic Regression on FPGAs for Fast Machine Learning Inference
Ho Fung Tsoi, Adrian Alan Pol, Vladimir Loncar +7
The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitiv…
Report of the Topical Group on Higgs Physics for Snowmass 2021: The Case for Precision Higgs Physics
Sally Dawson, Patrick Meade, Isobel Ojalvo +78
A future Higgs Factory will provide improved precision on measurements of Higgs couplings beyond those obtained by the LHC, and will enable a broad range of investigations across t…
Muon Collider Forum Report
K. M. Black, S. Jindariani, D. Li +182
A multi-TeV muon collider offers a spectacular opportunity in the direct exploration of the energy frontier. Offering a combination of unprecedented energy collisions in a comparat…
A Muon Collider Facility for Physics Discovery
D. Stratakis, N. Mokhov, M. Palmer +66
Muon colliders provide a unique route to deliver high energy collisions that enable discovery searches and precision measurements to extend our understanding of the fundamental law…
Prospects for the Measurement of the Standard Model Higgs Pair Production at the Muon Colliders
K. Black, T. Bose, S. Dasu +10
We study the Higgs pair production process at a muon collider using b-pair decays of the Higgs bosons. Efficient identification and good measurement resolution for the b-jet pair i…
Strategy for Understanding the Higgs Physics: The Cool Copper Collider
Sridhara Dasu, Emilio A. Nanni, Michael E. Peskin +26
A program to build a lepton-collider Higgs factory, to precisely measure the couplings of the Higgs boson to other particles, followed by a higher energy run to establish the Higgs…
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…
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…
The Muon Smasher's Guide
Hind Al Ali, Nima Arkani-Hamed, Ian Banta +31
We lay out a comprehensive physics case for a future high-energy muon collider, exploring a range of collision energies (from 1 to 100 TeV) and luminosities. We highlight the advan…
Charged particle tracking via edge-classifying interaction networks
Gage DeZoort, Savannah Thais, Javier Duarte +5
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high energ…
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…
HL-LHC Computing Review: Common Tools and Community Software
HEP Software Foundation, :, Thea Aarrestad +107
Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will b…
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…