The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

No abstract

This paper presents the observation of four-top-quark ($$t\bar{t}t\bar{t}$$ t t ¯ t t ¯ ) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 $$\hbox {fb}^{-1}$$ fb - 1 at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured $$t\bar{t}t\bar{t}$$ t t ¯ t t ¯ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The $$t\bar{t}t\bar{t}$$ t t ¯ t t ¯ production cross section is measured to be $$22.5^{+6.6}_{-5.5}$$ 22 . 5 - 5.5 + 6.6  fb, consistent with the SM prediction of $$12.0 \pm 2.4$$ 12.0 ± 2.4 fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect $$t\bar{t}t\bar{t}$$ t t ¯ t t ¯ production.

Charged particle reconstruction in High Energy Physics experiments is a significant part of overall event reconstruction. Depending on the physics environment, for instance in collider experiments with high multiplicities or luminosities, the tracking problem increases in complexity and often poses not only an algorithmic, but also a computational challenge. With the high-luminosity phase of the LHC at CERN approaching, research for new approaches and algorithms for track reconstruction has seen an increased interest. Both new technological approaches like hardware accelerators, as well as machine learning are being developed. However, testing and developing these new approaches against the existing experiments’ software stacks can prove to be challenging, as they typically focus on stable data taking, discouraging disruptive changes. This document presents a virtual tracking detector that is designed to be a simplified, but realistic model of a real-world detector, that can serve as a robust testbed for new developments.