635 citations · 3.7k across the 50 of their papers we have counts for
50 papers
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…
Uncertainty Quantification From Scaling Laws in Deep Neural Networks
Ibrahim Elsharkawy, Yonatan Kahn, Benjamin Hooberman
Quantifying the uncertainty from machine learning analyses is critical to their use in the physical sciences. In this work we focus on uncertainty inherited from the initialization…
Search for displaced leptons in TeV collisions with the ATLAS detector
ATLAS Collaboration
A search for charged leptons with large impact parameters using 139 fb of TeV collision data from the ATLAS detector at the LHC is presented, addressing…
Search for resonances decaying into a weak vector boson and a Higgs boson in the fully hadronic final state produced in protonproton collisions at TeV with the ATLAS detector
ATLAS Collaboration
A search for heavy resonances decaying into a or boson and a Higgs boson produced in protonproton collisions at the Large Hadron Collider at TeV is prese…
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics
Dawit Belayneh, Federico Carminati, Amir Farbin +13
Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of particles produced i…
First tracking performance results from the ATLAS Fast TracKer
Benjamin Hooberman
Particle physicists at the Large Hadron Collider investigate the properties of matter at subatomic length scales by colliding together bunches of high-energy protons and observing…