122 citations · 366 across the 11 of their papers we have counts for
12 papers
Beam Measurements and Machine Learning at the CERN Large Hadron Collider
P. Arpaia, G. Azzopardi, F. Blanc +16
This paper presents a review of the recent Machine Learning activities carried out on beam measurements performed at the CERN Large Hadron Collider. This paper has been accepted fo…
Automated segmentation of microtomography imaging of Egyptian mummies
Marc Tanti, Camille Berruyer, Paul Tafforeau +6
Propagation Phase Contrast Synchrotron Microtomography (PPC-SRCT) is the gold standard for non-invasive and non-destructive access to internal structures of archaeological remai…
Machine learning for beam dynamics studies at the CERN Large Hadron Collider
P. Arpaia, G. Azzopardi, F. Blanc +17
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of th…
A next-generation LHC heavy-ion experiment
D. Adamová, G. Aglieri Rinella, M. Agnello +395
The present document discusses plans for a compact, next-generation multi-purpose detector at the LHC as a follow-up to the present ALICE experiment. The aim is to build a nearly m…
First determination of the parameter at TeV -- probing the existence of a colourless three-gluon bound state
TOTEM Collaboration, G. Antchev, P. Aspell +93
The TOTEM experiment at the LHC has performed the first measurement at TeV of the parameter, the real to imaginary ratio of the nuclear elastic scattering ampli…
Opportunities in Machine Learning for Particle Accelerators
Auralee Edelen, Christopher Mayes, Daniel Bowring +10
Machine learning (ML) is a subfield of artificial intelligence. The term applies broadly to a collection of computational algorithms and techniques that train systems from raw data…