Impedance and Instability Studies in LEIR with Xenon

In 2017, the LEIR accelerator has been operated with Xe39+ beam for fixed target experiments in the SPS North Area. The different ion species, with respect to the standard Pb54+, allowed for additional comparative measurements of tune shift versus intensity at injection energy both in coasting and bunched beams. The fast transverse instability observed for high accumulated intensities has been as well characterized and additional observations relevant to impedance have been collected from longitudinal Schottky signal and BTF measurements. The results of these measurements are summarised and compared to the currently developed machine impedance model

Automatic setup of 18 MeV electron beamline using machine learning

To improve the performance-critical stability and brightness of the electron bunch at injection into the proton-driven plasma wakefield at the AWAKE CERN experiment, automation approaches based on unsupervised Machine Learning (ML) were developed and deployed. Numerical optimisers were tested together with different model-free reinforcement learning agents. In order to avoid any bias, reinforcement learning agents have been trained also using a completely unsupervised state encoding using auto-encoders. To aid hyper-parameter selection, a full synthetic model of the beamline was constructed using a variational auto-encoder trained to generate surrogate data from equipment settings. This paper describes the novel approaches based on deep learning and reinforcement learning to aid the automatic setup of a low energy line, as the one used to deliver beam to the AWAKE facility. The results obtained with the different ML approaches, including automatic unsupervised feature extraction from images using computer vision are presented. The prospects for operational deployment and wider applicability are discussed

Active deep learning for nonlinear optics design of a vertical FFA accelerator

Vertical Fixed-Field Alternating Gradient (vFFA) accelerators exhibit particle orbits which move vertically during acceleration. This recently rediscovered circular accelerator type has several advantages over conventional ring accelerators, such as zero momentum compaction factor. At the same time, inherently non-planar orbits and a unique transverse coupling make controlling the beam dynamics a complex task. In general, betatron tune adjustment is crucial to avoid resonances, particularly when space charge effects are present. Due to highly nonlinear magnetic fields in the vFFA, it remains a challenging task to determine an optimal lattice design in terms of maximising the dynamic aperture. This contribution describes a deep learning based algorithm which strongly improves on regular grid scans and random search to find an optimal lattice: a surrogate model is built iteratively from simulations with varying lattice parameters to predict the dynamic aperture. The training of the model follows an active learning paradigm, which thus considerably reduces the number of samples needed from the computationally expensive simulations

Studies of the Injection and Cooling Efficiency in LEIR Using the Longitudinal Schottky Spectrum

The CERN Low Energy Ion Ring (LEIR) has two main operational beams with their associated cycles, the so-called EARLY and the NOMINAL beam. The EARLY beam consists of a single injected pulse from the LINAC3 accelerator, whereas seven consecutive injections are accumulated, and electron cooled for the NOMINAL beam. In both cases, the longitudinal Schottky monitor allows assessing the longitudinal particle distribution during the cooling process on the injection plateau. A method has been established to analyze the Schottky signal, reconstruct the initial particle momentum distribution and derive relevant parameters such as the cooling time, energy off-set of injected and stacked beam or the momentum distribution of the lost beam. The variations of the obtained parameters and the impact on the LEIR performance will be addressed

Detailed characterisation of the LEIR intensity limitations for a Pb ion beam

The equilibrium emittance of the Pb beam in the CERN Low Energy Ion Ring (LEIR) results from the interplay of electron cooling and heating processes, as intra-beam scattering and space charge. In this paper we present the measurements of the emittance evolution as a function of intensity, working point and resonance excitation, and compare them with the simulations of the heating processes. Optimum settings for normal and skew sextupoles have been found for the compensation of resonances excited by the lattice

Space Charge Studies on LEIR

The performance of the CERN Low Energy Ion Ring with electron cooled ion beams is presently limited by losses occurring once the beam has been captured in the RF buckets. An intense machine study program was started by the end of 2015 to mitigate the losses and improve the performance of the accelerator. The measurements pointed to the interplay of direct space charge forces and excited betatron resonances as the most plausible driving mechanism of these losses. In this paper, we present the systematic space-charge measurements performed in 2017 and compare them to space-charge tracking simulations based on an adaptive frozen potential

Electron Cooling Simulation and Experimental Benchmarks at LEIR

A simulation of the electron cooling has recently been implemented in the tracking code RF-Track. The implementation was based on a "hybrid kinetic" model, where the full 6-D phase space of a particle beam is immersed in a fluid plasma of electrons. The computation of the cooling force was based on analytic models derived using the “di-electric theory” and the “binary collision approximation”, numerically integrated to consider the thermal properties of the electrons. This gives the code the flexibility needed to simulate a large variety of realistic scenarios, including imperfections such as gradients in the electron density and hollow electron beam; relative misalignments of electron beam, ion beam, and solenoid field. Benchmarks of the simulations against results in the literature as well as against measurements performed at LEIR using Xenon ions are presented

Test of Machine Learning at the CERN LINAC4

The CERN H$^-$ linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared beforehand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed

LEIR Injection Efficiency Studies as a Function of the Beam Energy Distribution from Linac3

High intensities in the CERN Low Energy Ion Ring (LEIR) are achieved using multi-turn injections from the pre-accelerator Linac3 combined with simultaneous stacking in momentum and transverse phase spaces. Up to seven consecutive 200 $\mu$s long, 200 ms spaced pulses are injected from Linac3 into LEIR by stacking each of them into the six-dimensional phase-space over 70 turns. An inclined septum magnet allows proper filling of the transverse phase-space plane, while longitudinal stacking requires momentum variation achieved by a shift of mean momentum over time provided by phase shifting a combination of 2 RF cavities at the exit of Linac3. The achievable maximum accumulated intensity depends strongly on the longitudinal beam quality of the injected beam. The longitudinal Schottky signal is used to measure the received energy distribution of the circulating beam which is then correlated with the obtained injection efficiency. This paper presents the experimental studies to understand and further improve the injection reliability and the longitudinal stacking

Energy dependence of the reproducibility and injection efficiency of the LINAC3-LEIR complex

High intensities in the CERN Low Energy Ion Ring (LEIR) are achieved by stacking several multi-turn injections from the pre-accelerator LINAC3. Up to seven consecutive 200 μs long, 200 ms spaced pulses are injected from LINAC3 into LEIR. An inclined septum magnet combined with a collapsing horizontal orbit bump allows a 6-D phase space painting via a linearly ramped mean momentum along the LINAC3 pulse and injection at high dispersion. The injected energy distribution measured by the LEIR longitudinal Schottky is correlated with the obtained injection efficiency in this paper. Studies in 2018 revealed that the achievable accumulated intensity of LEIR strongly depends on the longitudinal distribution from LINAC3, which does not stay constant. This paper summarises the experimental results and means to further improve reproducibility and high injection efficiency