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In this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations, components, and workflow of a typical supervised learning…
The accurate and precise extraction of information from a modern particle physics detector, such as an electromagnetic calorimeter, may be complicated and challenging. In order to overcome the difficulties we propose processing the detector…
We introduce the usage of equivariant neural networks in the search for violations of the charge-parity ($\textit{CP}$) symmetry in particle interactions at the CERN Large Hadron Collider. We design neural networks that take as inputs…
In the past two decades, the electron-ion merged-beams technique has extensively been exploited at heavy-ion storage rings equipped with electron coolers for spectroscopic studies of highly charged ions as well as for measuring absolute…
We present results from exploratory studies, supported by the Physics Beyond Colliders (PBC) Study Group, of the suitability of a CERN site and its infrastructure for hosting a vertical atom interferometer (AI) with a baseline of about 100…
Precision physics at future multi-TeV lepton colliders such as CLIC requires excellent jet energy resolution. The detectors need deep calorimeter systems to limit the energy leakage also for very highly energetic particles and jets. At the…
We review a subset of experimental results from the heavy-ion collisions at the Large Hadron Collider (LHC) facility at CERN. Excellent consistency is observed across all the experiments at the LHC (at center of mass energy of 2.76 TeV) for…
The "Physics Beyond Colliders (PBC)" study explores fundamental physics opportunities at the CERN accelerator complex complementary to collider experiments. Three new collaborations aim to exploit the M2 beamline in the North Area with…
Methods to make precision measurements of SUSY masses and parameters at the CERN Large Hadron Collider are described.
A precise measurement of the top-Higgs coupling is essential in particle physics, as it offers a powerful probe of potential new physics beyond the Standard Model (BSM), particularly scenarios involving ${\cal CP}$ violation, which is a key…
The staged commissioning of the Large Hadron Collider presents an opportunity to map gross features of particle production over a significant energy range. I suggest a visual tool - event displays in (pseudo)rapidity-transverse-momentum…
The High Luminosity upgrade of the CERN Large Hadron Collider will be able to reach a peak instantaneous luminosity of 5E34/cm2 s. The innermost detectors of the CMS and ATLAS experiments will have to cope with unprecedented requirements on…
This review deals with measurements and future experiments of light pentaquark searches using hadron beams.
The challenges in beam instrumentation and diagnostics for present and future particle accelerator projects are presented. A few examples for advanced hadron and lepton beam diagnostics are given.
Colliders, among the most successful tools of particle physics, have revealed much about matter. This review describes how colliders contribute to the search for particle dark matter, focusing on the highest-energy collider currently in…
To evaluate different technologies for calorimetry at the International Linear Collider, the CALICE collaboration has constructed a highly granular analog hadron calorimeter with small scintillator cells, individually read out by silicon…
Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. Given the fast pace of this research, we have created a living review with the goal of providing a…
The Beam Instrumentation group at CERN has developed a new scintillating fibre beam monitor for the measurement of secondary particle beams in the CERN Experimental Areas. The monitor has a simple design that stands out for its low material…
This work investigates the use of machine learning applied to the beam tracking problem in 5G networks and beyond. The goal is to decrease the overhead associated to MIMO millimeter wave beamforming. In comparison to beam selection (also…
The purpose of this paper is to review the most popular deep learning methods used to analyze astroparticle data obtained with Imaging Atmospheric Cherenkov Telescopes and provide references to the original papers.