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Accelerator Report: Optimisation for greater success (and new challenges)


Since the last Accelerator Report, lead-ion beams have been successfully provided to the SPS North Area, in particular to the NA61 experiment, which is their principal user. The optimisation of the SPS beam parameters and the slow extraction process last week, together with the optimisation of the beam transport to the North Area, have resulted in an optimal beam spill structure, 50% more efficient than in 2022.

On Friday, 6 October, the LHC completed the stepwise intensity ramp-up of the lead-ion beams and reached 1240 bunches per beam. However, this achievement came with two main challenges: beam losses during the last part of the acceleration ramp, causing the beam to be dumped, and a high level of background noise in the ALICE detector, in an area where the circulating beam interacts with the collimators.

These graphs from the ALICE collaboration show the level of background noise before and after the correction of the residual dispersion. The peak in the middle represents the level of beam signal.(Image: CERN)

To address the beam loss issue, the thresholds of the beam loss monitors that are distributed around the LHC and serve as input to the beam dump system have been increased. This allows more lead ions to be lost, especially in the areas with collimators, without compromising the safety and reliability of the accelerators. This and other adjustments allowed the losses during acceleration to be kept below the dump threshold and beams with 1240 bunches each to be collided.

Experts from the ALICE experiment and the LHC machine collaborated closely to tackle the issue of background noise in the ALICE detector: many different remedial strategies were studied and tested during several fills over a period of more than 30 hours. Finally, the correction of residual dispersion (see the box below) reduced the background noise to a satisfactory level for ALICE to take physics data in the coming weeks.

Efforts to enhance accelerator performance extend beyond the LHC beams. Teams are constantly fine-tuning the injectors, not only for LHC beams but also for various fixed-target beams. The new AD/ELENA antiproton beam intensity records that we saw last week are a nice example. At the start of the 2023 run, the AD extracted 3.1x107 antiprotons. This was increased gradually to reach 4x107 antiprotons in September. Following an increase in the number of protons on the AD target, which is the source of antiprotons, optimisations on the AD machine side were performed to increase – to up to 90% – the percentage of antiprotons that reach extraction, resulting in a record intensity of 4.9x107 antiprotons extracted from the AD. This is the result of meticulous work by the AD team to better understand the machine and gain a fraction of a percent each time.

After being first decelerated in the AD machine, the antiproton beam is injected into the ELENA machine, where the antiprotons are divided into four bunches that, after further deceleration, can be extracted individually and sent to the different antimatter experiments. In September, these experiments regularly received 8x106 antiprotons per bunch but, last week, after the recent optimisations, they received up to 9.7x106 antiprotons per bunch, a new intensity record for ELENA.

These remarkable achievements reflect the dedication and expertise of the many teams that, together, make the CERN accelerator complex run.

A brief explanation of dispersion

The particles circulating in the LHC do not all have the same energy: some particles in the beam have a slightly lower or higher energy than the average energy of all the particles. A beam of particles thus has an average energy and an energy spread.

The beam is curved by the LHC dipoles, which guide it along the 27-km-long accelerator, but the radius of curvature is different for particles with different energies. Therefore, the physical size of the beam at the exit of the dipoles will depend on the energy spread of the beam. This is what we call dispersion.