Abstract 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 …

The design stored beam energy in the CERN high-luminosity large hadron collider (HL-
LHC) upgrade is about 700 MJ, with about 36 MJ in the beam tails, according to estimates …

The CMS detector, including its muon system, has been operating at the CERN LHC in
increasingly challenging conditions for about 15 years. The muon detector was designed to …

Determining a model for the time scaling of the dynamic aperture of a circular accelerator is
a topic of strong interest and intense research efforts in accelerator physics. The motivation …

Nonlinear magnetic errors in low-β insertions can have a significant impact on the beam-
dynamics of a collider, such as the CERN Large Hadron Collider (LHC) and its luminosity …

In recent years, modelling the evolution of beam losses in circular proton machines starting
from the evolution of the dynamic aperture has been the focus of intense research. Results …

We investigate the ability of an ensemble reservoir computing approach to predict the long-
term behaviour of the phase-space region in which the motion of charged particles in hadron …

A Machine Learning approach to scientific problems has been in use in Science and
Engineering for decades. High-energy physics provided a natural domain of application of …

The dynamic aperture (DA) of a hadron accelerator is represented by the volume in phase
space that exhibits bounded motion, where we disregard any disconnected parts that could …

With the advent of Machine Learning a few decades ago, Science and Engineering have
had new powerful tools at their disposal. Particularly in the domain of particle physics …