8 citations · 18 across the 5 of their papers we have counts for
9 papers
Performance of the MICE diagnostic system
The MICE collaboration, M. Bogomilov, R. Tsenov +135
Muon beams of low emittance provide the basis for the intense, well-characterised neutrino beams of a neutrino factory and for multi-TeV lepton-antilepton collisions at a muon coll…
Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors
Francois Drielsma, Kazuhiro Terao, Laura Dominé +1
Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. Unlike previous efforts which tack…
Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data
Francois Drielsma, Qing Lin, Pierre Côte de Soux +7
Liquid Argon Time Projection Chambers (LArTPCs) are a class of detectors that produce high resolution images of charged particles within their sensitive volume. In these images, th…
A New Concept for Kilotonne Scale Liquid Argon Time Projection Chambers
M. Auger, R. Berner, Y. Chen +25
We develop a novel approach for a Time Projection Chamber (TPC) concept suitable for deployment in kilotonne scale detectors, with a charge-readout system free from reconstruction…
First demonstration of ionization cooling by the Muon Ionization Cooling Experiment
M. Bogomilov, R. Tsenov, G. Vankova-Kirilova +132
High-brightness muon beams of energy comparable to those produced by state-of-the-art electron, proton and ion accelerators have yet to be realised. Such beams have the potential t…
MAUS: The MICE Analysis User Software
R. Asfandiyarov, R. Bayes, V. Blackmore +43
The Muon Ionization Cooling Experiment (MICE) collaboration has developed the MICE Analysis User Software (MAUS) to simulate and analyze experimental data. It serves as the primary…