An experiment for electron-hadron scattering at the LHC

Novel considerations are presented on the physics, apparatus and accelerator designs for a future, luminous, energy frontier electron-hadron (eh) scattering experiment at the LHC in the thirties for which key physics topics and their relation to the hadron-hadron HL-LHC physics programme are discussed. Demands are derived set by these physics topics on the design of the LHeC detector, a corresponding update of which is described. Optimisations on the accelerator design, especially the interaction region (IR), are presented. Initial accelerator considerations indicate that a common IR is possible to be built which alternately could serve eh and hh collisions while other experiments would stay on hh in either condition. A forward-backward symmetrised option of the LHeC detector is sketched which would permit extending the LHeC physics programme to also include aspects of hadron-hadron physics. The vision of a joint eh and hh physics experiment is shown to open new prospects for solving fundamental problems of high energy heavy-ion physics including the partonic structure of nuclei and the emergence of hydrodynamics in quantum field theory while the genuine TeV scale DIS physics is of unprecedented rank.

Framing energetic top-quark pair production at the LHC

Top-quark pair production is central to many facets of LHC physics. At leading order, the top and anti-top are produced in a back-to-back topology, however this topology accounts only for a minority of the events with TeV-scale momentum transfer that contain a $$ t\overline{t} $$ t t ¯ pair. The remaining events instead involve the splitting of an initial or final-state gluon to $$ t\overline{t} $$ t t ¯ . We provide simple quantitative arguments that explain why this is the case, and examine the interplay between different topologies and a range of variables that characterise the event hardness. We then develop a method to classify the topologies of individual events and use it to illustrate our findings in the context of simulated events, using both top partons and suitably defined fiducial tops. For events with large $$ t\overline{t} $$ t t ¯ invariant mass, we comment on additional features that have important experimental and theoretical implications.

Challenges in Monte Carlo Event Generator Software for High-Luminosity LHC

We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group as an input to the LHCC review of HL-LHC computing, which has started in May 2020.

What Can We Learn About QCD and Collider Physics from $\mathcal {N}=4$ Super Yang–Mills?

Tremendous ongoing theory efforts are dedicated to developing new methods for quantum chromodynamics (QCD) calculations. Qualitative rather than incremental advances are needed to fully exploit data that are still to be collected at the LHC. The maximally supersymmetric Yang–Mills theory, 𝒩=4 super Yang–Mills (sYM), shares with QCD the gluon sector, which contains the most complicated Feynman graphs but also has many special properties and is believed to be solvable exactly. It is natural to ask what we can learn from advances in 𝒩=4 sYM for addressing difficult problems in QCD. With this in mind, I review several remarkable developments and highlights of recent results in 𝒩=4 sYM. This includes all-order results for certain scattering amplitudes, novel symmetries, surprising geometrical structures of loop integrands, novel tools for the calculation of Feynman integrals, and bootstrap methods. While several insights and tools have already been carried over to QCD and have contributed to state-of-the-art calculations for LHC physics, I argue that there is a host of further fascinating ideas waiting to be explored. Expected final online publication date for the Annual Review of Nuclear and Particle Science, Volume 71 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Power corrections to event shapes using Eikonal dressed gluon exponentiation

Event shapes are classical tools for the determination of the strong coupling and for the study of hadronization effects in electron-positron annihilation. In the context of analytical studies, hadronization corrections take the form of power-suppressed contributions to the cross section, which can be extracted from the perturbative ambiguity of Borel-resummed distributions. We propose a simplified version of the well-established method of Dressed Gluon Exponentiation (DGE), which we call Eikonal DGE (EDGE), which determines all dominant power corrections to event shapes by means of strikingly elementary calculations. We believe our method can be generalized to hadronic event shapes and jet shapes of relevance for LHC physics.

Design and engineering of a simplified workflow execution for the MG5aMC event generator on GPUs and vector CPUs

Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern hardware architectures, such as those deployed at HPC centers, is essential in view of the upcoming HL-LHC physics programme. In this paper, we describe an ongoing activity to reengineer the Madgraph5_aMC@NLO physics event generator, primarily to port it and allow its efficient execution on GPUs, but also to modernize it and optimize its performance on vector CPUs. We describe the motivation, engineering process and software architecture design of our developments, as well as the current challenges and future directions for this project. This paper is based on our submission to vCHEP2021 in March 2021, complemented with a few preliminary results that we presented during the conference. Further details and updated results will be given in later publications.

Development of FPGA-based neural network regression models for the ATLAS Phase-II barrel muon trigger upgrade

Effective selection of muon candidates is the cornerstone of the LHC physics programme. The ATLAS experiment uses a two-level trigger system for real-time selection of interesting collision events. The first-level hardware trigger system uses the Resistive Plate Chamber detector (RPC) for selecting muon candidates in the central (barrel) region of the detector. With the planned upgrades, the entirely new FPGA-based muon trigger system will be installed in 2025-2026. In this paper, neural network regression models are studied for potential applications in the new RPC trigger system. A simple simulation model of the current detector is developed for training and testing neural network regression models. Effects from additional cluster hits and noise hits are evaluated. Efficiency of selecting muon candidates is estimated as a function of the transverse muon momentum. Several models are evaluated and their performance is compared to that of the current detector, showing promising potential to improve on current algorithms for the ATLAS Phase-II barrel muon trigger upgrade.