Abstract: We attempt to clarify several aspects concerning the recently presented four-dimensional Einstein-Gauss-Bonnet gravity. We argue that the limiting procedure outlined in [Phys. Rev. Lett. 124, 081301 (2020)] generally involves ill-defined terms in the four dimensional field equations. Potential ways to circumvent this issue are discussed, alongside remarks regarding specific solutions of the theory. We prove that, although linear perturbations are well behaved around maximally symmetric backgrounds, the equations for second-order perturbations are ill-defined even around a Minkowskian background. Additionally, we perform a detailed analysis of the spherically symmetric solutions and find that the central curvature singularity can be reached within a finite proper time.

Abstract: The simulation and analysis of High Energy Physics experiments require a realistic simulation of the detector material and its distribution. The challenge is to describe all active and passive parts of large scale detectors like ATLAS in terms of their size, position and material composition. The common method for estimating the radiation length by weighing individual components, adding up their contributions and averaging the resulting material distribution over extended structures provides a good general estimate, but can deviate significantly from the material actually present. A method has been developed to assess its material distribution with high spatial resolution using the reconstructed scattering angles and hit positions of high energy electron tracks traversing an object under investigation. The study presented here shows measurements for an extended structure with a highly inhomogeneous material distribution. The structure under investigation is an End-of-Substructure-card prototype designed for the ATLAS Inner Tracker strip tracker – a PCB populated with components of a large range of material budgets and sizes. The measurements presented here summarise requirements for data samples and reconstructed electron tracks for reliable image reconstruction of large scale, inhomogeneous samples, choices of pixel sizes compared to the size of features under investigation as well as a bremsstrahlung correction for high material densities and thicknesses.

Abstract: Measuring temperature fluctuations in the 21 cm signal from the epoch of reionization and the cosmic dawn is one of the most promising ways to study the universe at high redshifts. Unfortunately, the 21 cm signal is affected by both cosmology and astrophysics processes in a nontrivial manner. We run a suite of 1000 numerical simulations with different values of the main astrophysical parameters. From these simulations we produce tens of thousands of 21 cm maps at redshifts 10 <= z <= 20. We train a convolutional neural network to remove the effects of astrophysics from the 21 cm maps and output maps of the underlying matter field. We show that our model is able to generate 2D matter fields not only that resemble the true ones visually but whose statistical properties agree with the true ones within a few percent down to scales 2 Mpc(-1). We demonstrate that our neural network retains astrophysical information that can be used to constrain the value of the astrophysical parameters. Finally, we use saliency maps to try to understand which features of the 21 cm maps the network is using in order to determine the value of the astrophysical parameters.