The TOTEM experiment at the CERN LHC has measured elastic proton–proton scattering at the centre-of-mass energy $$\sqrt{s}=8\,$$ TeV and four-momentu

Two high-accuracy goniometers equipped with two bent silicon crystals were installed in the betatron cleaning insertion of the CERN Large Hadron Collider (LHC) during its long shutdown. First beam tests were recently performed at the LHC with 450 GeV/c and 6500 GeV/c stored proton beams to investigate the feasibility of beam halo collimation assisted by bent crystals. For the first time channeling of 6500 GeV/c protons was observed in a particle accelerator. A strong reduction of beam losses due to nuclear inelastic interactions in the aligned crystal in comparison with its amorphous orientation was detected. The loss reduction value was about 24. Thus, the results show that deflection of particles by a bent crystal due to channeling is effective for this record particle energy

Numerical optimization algorithms are already established tools to increase and stabilize the performance of particle accelerators. These algorithms have many advantages, are available out of the box, and can be adapted to a wide range of optimization problems in accelerator operation. The next boost in efficiency is expected to come from reinforcement learning algorithms that learn the optimal policy for a certain control problem and hence, once trained, can do without the time-consuming exploration phase needed for numerical optimizers. To investigate this approach, continuous model-free reinforcement learning with up to 16 degrees of freedom was developed and successfully tested at various facilities at CERN. The approach and algorithms used are discussed and the results obtained for trajectory steering at the AWAKE electron line and LINAC4 are presented. The necessary next steps, such as uncertainty aware model-based approaches, and the potential for future applications at particle accelerators are addressed.

The CERN Large Hadron Collider (LHC) is designed to collide proton beams of unprecedented energy, in order to extend the frontiers of high-energy particle physics. During the first very successful running period in 2010–2013, the LHC was routinely storing protons at 3.5–4 TeV with a total beam energy of up to 146 MJ, and even higher stored energies are foreseen in the future. This puts extraordinary demands on the control of beam losses. An uncontrolled loss of even a tiny fraction of the beam could cause a superconducting magnet to undergo a transition into a normal-conducting state, or in the worst case cause material damage. Hence a multistage collimation system has been installed in order to safely intercept high-amplitude beam protons before they are lost elsewhere. To guarantee adequate protection from the collimators, a detailed theoretical understanding is needed. This article presents results of numerical simulations of the distribution of beam losses around the LHC that have leaked out of the collimation system. The studies include tracking of protons through the fields of more than 5000 magnets in the 27 km LHC ring over hundreds of revolutions, and Monte Carlo simulations of particle-matter interactions both in collimators and machine elements being hit by escaping particles. The simulation results agree typically within a factor 2 with measurements of beam loss distributions from the previous LHC run. Considering the complex simulation, which must account for a very large number of unknown imperfections, and in view of the total losses around the ring spanning over 7 orders of magnitude, we consider this an excellent agreement. Our results give confidence in the simulation tools, which are used also for the design of future accelerators.