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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. [ABSTRACT FROM AUTHOR]

Numerically estimating the integral of functions in high dimensional spaces is a nontrivial task. A oft-encountered example is the calculation of the marginal likelihood in Bayesian inference, in a context where a sampling algorithm such as a Markov Chain Monte Carlo provides samples of the function. We present an Adaptive Harmonic Mean Integration (AHMI) algorithm. Given samples drawn according to a probability distribution proportional to the function, the algorithm will estimate the integral of the function and the uncertainty of the estimate by applying a harmonic mean estimator to adaptively chosen regions of the parameter space. We describe the algorithm and its mathematical properties, and report the results using it on multiple test cases. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports published within the issue including one by Michael Peskin on the necessity of the Higgs mechanism in the Standard Model, another by Jim Virdee on the genesis of the Standard Model and the main features of the Higgs and a piece by Klaus Jungmann on flavour physics.

A number of experiments are currently underway on antimatter, particularly anti‐hydrogen, to test whether the fundamental interactions behave the same way as for matter. Here we present a simple argument showing that a bound on a difference in gravitational forces exerted on matter and antimatter is already so severe that is goes well beyond the sensitivity of the above measurements. A number of experiments are currently underway on antimatter, particularly anti‐hydrogen, to test whether the fundamental interactions behave the same way as for matter. Here a simple argument is presented showing that a bound on a difference in gravitational forces exerted on matter and antimatter is already so severe that is goes well beyond the sensitivity of the above measurements. [ABSTRACT FROM AUTHOR]

Plasmas excited by laser beams or bunches of relativistic electrons have been used to produce electric fields of 10–100 GV m−1. This has opened up the possibility of building compact particle accelerators at the gigaelectronvolt scale. However, it is not obvious how to scale these approaches to the energy frontier of particle physics—the teraelectronvolt regime. Here, we introduce the possibility of proton-bunch-driven plasma-wakefield acceleration, and demonstrate through numerical simulations that this energy regime could be reached in a single accelerating stage. [ABSTRACT FROM AUTHOR]

Some aspects of the Frequentist approach to statistical data analysis are presented and discussed. The construction of confidence intervals for parameters is explained and made concrete with a detailed example. The intervals correspond to parameter ranges where the observed data is in a 'favored' part of the expected results distribution. Goodness‐of‐fit tests are defined similarly; here, a Bayesian argument is given for the usefulness of these tests. The possible over‐interpretation of Frequentist results is also discussed. Some aspects of the Frequentist approach to statistical data analysis are presented and discussed. The construction of confidence intervals for parameters is explained and made concrete with a detailed example. Goodness‐of‐fit tests are defined similarly; here, a Bayesian argument is given for the usefulness of these tests. The possible over‐interpretation of Frequentist results is also discussed. [ABSTRACT FROM AUTHOR]

Many experiments in physics involve searching for a localized excess over background expectations in an observed spectrum. If the background is known and there is Gaussian noise, the amount of excess of successive observations can be quantified by the SQUARES (squares-of-run-residuals sum) statistic taking care of the look-elsewhere effect. The distribution of the SQUARES statistic under the background model is known analytically but the computation becomes too expensive for more than about a hundred observations. Here a principled high-precision extrapolation from a few dozen up to millions of data points is derived. It is most precise in the interesting regime when an excess is present. The method is verified for benchmark cases and successfully applied to real data from an axion search. C++ code that implements our method is available at https://github.com/fredRos/runs. [ABSTRACT FROM AUTHOR]