7 papers
On the Codesign of Scientific Experiments and Industrial Systems
Tommaso Dorigo, Pietro Vischia, Shahzaib Abbas +84
The optimization of large experiments in fundamental science, such as detectors for subnuclear physics at particle colliders, shares with the optimization of complex systems for in…
Towards replacing detector simulation with heterogeneous GNNs in flavour physics analyses
Guillermo Hijano, Davide Lancierini, Alexander Mclean Marshall +8
Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing th…
Ultra-Fast Muon Transport via Histogram Sampling on GPUs
Luis Felipe P. Cattelan, Shah Rukh Qasim, Patrick H. Owen +1
We present a GPU-accelerated method for muon transport based on histogram sampling that delivers orders of magnitude faster performance than CPU-based Geant4 simulation. Our method…
Leveraging Reinforcement Learning, Genetic Algorithms and Transformers for background determination in particle physics
Guillermo Hijano Mendizabal, Davide Lancierini, Alex Marshall +8
Experimental studies of beauty hadron decays face significant challenges due to a wide range of backgrounds arising from the numerous possible decay channels with similar final sta…
FastGraph: Optimized GPU-Enabled Algorithms for Fast Graph Building and Message Passing
Aarush Agarwal, Raymond He, Jan Kieseler +2
We introduce FastGraph, a novel GPU-optimized k-nearest neighbor algorithm specifically designed to accelerate graph construction in low-dimensional spaces (2-10 dimensions), criti…
Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
M. Aamir, G. Adamov, T. Adams +568
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…