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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.

Plasma wakefield acceleration is a promising technology to reduce the size of particle accelerators. The use of high energy protons to drive wakefields in plasma has been demonstrated during Run 1 of the AWAKE programme at CERN. Protons of energy 400 GeV drove wakefields that accelerated electrons to 2 GeV in under 10 m of plasma. The AWAKE collaboration is now embarking on Run 2 with the main aims to demonstrate stable accelerating gradients of 0.5–1 GV/m, preserve emittance of the electron bunches during acceleration and develop plasma sources scalable to 100s of metres and beyond. By the end of Run 2, the AWAKE scheme should be able to provide electron beams for particle physics experiments and several possible experiments have already been evaluated. This article summarises the programme of AWAKE Run 2 and how it will be achieved as well as the possible application of the AWAKE scheme to novel particle physics experiments.

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 (RL) agents. In order to avoid any bias, RL 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 RL 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.

A bstract Searches for invisible decays of the Higgs boson are presented. The data collected with the CMS detector at the LHC correspond to integrated luminosities of 5.1, 19.7, and 2.3 fb −1 at centre-of-mass energies of 7, 8, and 13 TeV, respectively. The search channels target Higgs boson production via gluon fusion, vector boson fusion, and in association with a vector boson. Upper limits are placed on the branching fraction of the Higgs boson decay to invisible particles, as a function of the assumed production cross sections. The combination of all channels, assuming standard model production, yields an observed (expected) upper limit on the invisible branching fraction of 0.24 (0.23) at the 95% confidence level. The results are also interpreted in the context of Higgs-portal dark matter models.

A bstract A search is presented for decays beyond the standard model of the 125 GeV Higgs bosons to a pair of light bosons, based on models with extended scalar sectors. Light boson masses between 5 and 62.5 GeV are probed in final states containing four τ leptons, two muons and two b quarks, or two muons and two τ leptons. The results are from data in proton-proton collisions corresponding to an integrated luminosity of 19.7 fb −1 , accumulated by the CMS experiment at the LHC at a center-of-mass energy of 8 TeV. No evidence for such exotic decays is found in the data. Upper limits are set on the product of the cross section and branching fraction for several signal processes. The results are also compared to predictions of two-Higgs-doublet models, including those with an additional scalar singlet.

A bstract The transverse momentum spectra of weak vector bosons are measured in the CMS experiment at the LHC. The measurement uses a sample of proton-proton collisions at s = 8 TeV, collected during a special low-luminosity running that corresponds to an integrated luminosity of 18 . 4 ± 0 . 5 pb −1 . The production of W bosons is studied in both electron and muon decay modes, while the production of Z bosons is studied using only the dimuon decay channel. The ratios of W − to W + and Z to W differential cross sections are also measured. The measured differential cross sections and ratios are compared with theoretical predictions up to next-to-next leading order in QCD.

A bstract A search is conducted for new physics in a final state containing a photon and missing transverse momentum in proton-proton collisions at s = 13 TeV. The data collected by the CMS experiment at the CERN LHC correspond to an integrated luminosity of 12.9 fb −1 . No deviations are observed relative to the predictions of the standard model. The results are interpreted as exclusion limits on the dark matter production cross sections and parameters in models containing extra spatial dimensions. Improved limits are set with respect to previous searches using the monophoton final state. In particular, the limits on the extra dimension model parameters are the most stringent to date in this channel.

A bstract Single top quark events produced in the t channel are used to set limits on anomalous Wtb couplings and to search for top quark flavour-changing neutral current (FCNC) interactions. The data taken with the CMS detector at the LHC in proton-proton collisions at s = 7 and 8 TeV correspond to integrated luminosities of 5.0 and 19.7 fb −1 , respectively. The analysis is performed using events with one muon and two or three jets. A Bayesian neural network technique is used to discriminate between the signal and backgrounds, which are observed to be consistent with the standard model prediction. The 95% confidence level (CL) exclusion limits on anomalous right-handed vector, and left- and right-handed tensor Wtb couplings are measured to be | f V R | < 0.16, | f T L | < 0.057, and − 0.049 <  f T R  < 0.048, respectively. For the FCNC couplings κ tug and κ tcg , the 95% CL upper limits on coupling strengths are | κ tug |/ Λ  < 4.1 × 10 − 3 TeV −1 and | κ tcg |/ Λ  < 1.8 × 10 − 2 TeV −1 , where Λ is the scale for new physics, and correspond to upper limits on the branching fractions of 2 . 0 × 10 −5 and 4 . 1 × 10 −4 for the decays t → ug and t → cg, respectively.

A bstract A search for heavy resonances that decay to tau lepton pairs is performed using proton-proton collisions at s = 13 TeV. The data were collected with the CMS detector at the CERN LHC and correspond to an integrated luminosity of 2.2 fb −1 . The observations are in agreement with standard model predictions. An upper limit at 95% confidence level on the product of the production cross section and branching fraction into tau lepton pairs is calculated as a function of the resonance mass. For the sequential standard model, the presence of Z′ bosons decaying into tau lepton pairs is excluded for Z′ masses below 2.1 TeV, extending previous limits for this final state. For the topcolor-assisted technicolor model, which predicts Z′ bosons that preferentially couple to third-generation fermions, Z′ masses below 1.7 TeV are excluded, representing the most stringent limit to date.

A search is presented for an excess of events with heavy-flavor quark pairs ( t t ¯ and b b ¯ ) and a large imbalance in transverse momentum in data from proton–proton collisions at a center-of-mass energy of 13 TeV . The data correspond to an integrated luminosity of 2.2 fb - 1 collected with the CMS detector at the CERN LHC. No deviations are observed with respect to standard model predictions. The results are used in the first interpretation of dark matter production in t t ¯ and b b ¯ final states in a simplified model. This analysis is also the first to perform a statistical combination of searches for dark matter produced with different heavy-flavor final states. The combination provides exclusions that are stronger than those achieved with individual heavy-flavor final states.