Operational results with fast automatic beam-based LHC collimator alignment

The CERN Large Hadron Collider (LHC) is the largest and highest-energy particle accelerator ever built. It is designed to collide particles at a centre-of-mass energy of 14 TeV to explore the fundamental forces and constituents of matter. Due to the potentially destructive high-energy particle beams, with a total design energy of 362 MJ, the collider is equipped with a series of machine protection systems. The beam cleaning or collimation system is designed to passively intercept and absorb particles at large amplitudes. The cleaning efficiency depends heavily on the accurate positioning of the jaws with respect to the beam trajectory. Beam-based collimator alignment is currently the only feasible technique that can be used to determine the beam centre and beam size at the collimator locations. If the alignment is performed without any automation, it can require up to 30 hours to complete for all collimators. This reduces the beam time available for physics experiments. This article provides a brief recap of the algorithms and software developed to automate and speed up the alignment procedure, and presents the operational results achieved with fast automatic beam-based alignment in the 2011-2013 LHC runs.peer-reviewe

Conceptual design of hollow electron lenses for beam halo control in the Large Hadron Collider

Collimation with hollow electron beams is a technique for halo control in high-power hadron beams. It is based on an electron beam (possibly pulsed or modulated in intensity) guided by strong axial magnetic fields which overlaps with the circulating beam in a short section of the ring. The concept was tested experimentally at the Fermilab Tevatron collider using a hollow electron gun installed in one of the Tevatron electron lenses. Within the US LHC Accelerator Research Program (LARP) and the European FP7 HiLumi LHC Design Study, we are proposing a conceptual design for applying this technique to the Large Hadron Collider at CERN. A prototype hollow electron gun for the LHC was built and tested. The expected performance of the hollow electron beam collimator was based on Tevatron experiments and on numerical tracking simulations. Halo removal rates and enhancements of halo diffusivity were estimated as a function of beam and lattice parameters. Proton beam core lifetimes and emittance growth rates were checked to ensure that undesired effects were suppressed. Hardware specifications were based on the Tevatron devices and on preliminary engineering integration studies in the LHC machine. Required resources and a possible timeline were also outlined, together with a brief discussion of alternative halo-removal schemes and of other possible uses of electron lenses to improve the performance of the LHC.Comment: 24 pages, 1 table, 10 figure

Data-driven cross-talk modeling of beam losses in LHC collimators

The Large Hadron Collider at CERN is equipped with a collimation system to intercept potentially dangerous beam halo particles before they damage its sensitive equipment. The collimator settings are determined following a beam-based alignment procedure, in which the collimator jaws are moved towards the beam until losses appear in the beam loss monitors. When the collimator reaches the beam envelope, beam losses propagate mainly in the direction of the beam and are, therefore, also observed by other nearby beam loss monitors. This phenomenon is known as cross talk. Due to this, collimators are aligned sequentially to be able to identify which losses are generated by which collimator, such that any cross talk across beam loss monitors positioned close to each other is avoided. This paper seeks to quantify the levels of cross-talk observed by beam loss monitors when multiple collimators are moving, to be able to determine the actual beam loss signals generated by their corresponding collimators. The results obtained successfully predicted the amount of cross-talk observed for each of the cases tested in this study. This was then extended to predict loss map case studies and the proton impacts at each collimator by comparing them to simulations.peer-reviewe

Machine learning applied at the LHC for beam loss pattern classification

Beam losses at the LHC are constantly monitored because they can heavily impact the performance of the machine. One of the highest risks is to quench the LHC superconducting magnets in the presence of losses leading to a long machine downtime to recover cryogenic conditions. Smaller losses are more likely to occur and have an impact on the machine performance, reducing the luminosity production or reducing the lifetime of accelerator systems due to radiation effects, such as magnets. Understanding the characteristics of the beam loss, such as the beam and the plane, is crucial to correct them. Regularly during the year, dedicated loss map measurements are performed to validate the beam halo cleaning of the collimation system. These loss maps have the particular advantage that they are performed in well controlled conditions and can therefore be used by a machine learning algorithm to classify the type of losses during the LHC machine cycle. This study shows the result of the beam loss classification and its retrospective application to beam loss data from the 2017 run.peer-reviewe

Measurements of the effect of collisions on transverse beam halo diffusion in the Tevatron and in the LHC

Beam-beam forces and collision optics can strongly affect beam lifetime, dynamic aperture, and halo formation in particle colliders. Extensive analytical and numerical simulations are carried out in the design and operational stage of a machine to quantify these effects, but experimental data is scarce. The technique of small-step collimator scans was applied to the Fermilab Tevatron collider and to the CERN Large Hadron Collider to study the effect of collisions on transverse beam halo dynamics. We describe the technique and present a summary of the first results on the dependence of the halo diffusion coefficient on betatron amplitude in the Tevatron and in the LHC.Comment: 4 pages, 2 figures. Submitted to the Proceedings of the ICFA Mini-Workshop on Beam-beam Effects in Hadron Colliders (BB2013), Geneva, Switzerland, 18-22 March 201

Operational results on the fully automatic LHC collimator alignment

The Large Hadron Collider has a complex collimation system installed to protect its sensitive equipment from normal and abnormal beam losses. The collimators are set around the beam following a multistage transverse setting hierarchy. The insertion position of each collimator is established using beam-based alignment techniques to determine the local beam position and rms beam size at each collimator. During previous years, collimator alignments were performed semiautomatically, with collimation experts present to oversee and control the alignment. During run II, a new fully automatic alignment tool was developed and used for collimator alignments throughout 2018. This paper discusses the improvements on the alignment software to automate it using machine learning, whilst focusing on the operational results obtained when testing the new software in the LHC. The alignment tests were conducted with both proton and ion beams, and angular alignments were performed with proton beams. This upgraded software successfully decreased the alignment time by a factor of 3 and made the results more reproducible, which is particularly important when performing angular alignments.peer-reviewe

Software architecture for automatic LHC collimator alignment using machine learning

The Large Hadron Collider at CERN relies on a collimation system to absorb unavoidable beam losses before they reach the superconducting magnets. The collimators are positioned close to the beam in a transverse setting hierarchy achieved by aligning each collimator with a precision of a few tens of micrometres. In previous years, collimator alignments were performed semi-automatically, requiring collimation experts to be present to oversee and control the entire process. In 2018, expert control of the alignment procedure was replaced by dedicated machine learning algorithms, and this new software was used for collimator alignments throughout the year. This paper gives an overview of the software re-design required to achieve fully automatic collimator alignments, describing in detail the software architecture and controls systems involved. Following this successful deployment, this software will be used in the future as the default alignment software for the LHC.peer-reviewe

Beam halo dynamics and control with hollow electron beams

Experimental measurements of beam halo diffusion dynamics with collimator scans are reviewed. The concept of halo control with a hollow electron beam collimator, its demonstration at the Tevatron, and its possible applications at the LHC are discussed.Comment: 5 pages, 4 figures, in Proceedings of the 52nd ICFA Advanced Beam Dynamics Workshop on High-Intensity and High-Brightness Hadron Beams (HB2012), Beijing, China, 17-21 September 201