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The goal of this study is to understand the observed differences in ATLAS software performance, when comparing results measured under ideal laboratory conditions with those from ATLAS computing resources on the Worldwide LHC Computing Grid (WLCG). The laboratory results are based on the full simulation of ttbar events and use dedicated, local hardware. In order to have a common and reproducible base to which to compare, thousands of identical ttbar full simulation benchmark jobs were submitted to hundreds of Grid sites using the HammerCloud infrastructure. The impact of the heterogeneous hardware of the Grid sites and the performance difference of different hardware generations is analysed in detail, and a direct, in-depth comparison of jobs performed on identical CPU types is also done. The choice of the physics sample used in the benchmark is validated by comparing the performance on each Grid site measured with HammerCloud, weighted by its contribution to the total ATLAS full simulation production output.

During ATLAS Run 2, in the online track reconstruction algorithm of the Inner Detector, a large proportion of the CPU time was dedicated to the track finding. With the proposed HL-LHC upgrade, where the event pile-up is predicted to reach ⟨ μ ⟩ = 200, track finding will see a further large increase in CPU usage. Moreover, only a small subset of track candidate seeds is accepted after the track finding procedure, spending the CPU time on seeds that are discarded. Therefore, a computationally cheap track candidate seed pre-selection procedure based on approximate track following was designed, which is described in this report. The algorithm uses a simplified track extrapolation and a combinatorial Kalman filter simplified by a reference-related coordinate system to find the best track candidates. For such candidates, a set of numerical features were created to classify seeds using a Support Vector Classifier, tuned with a high True Positive rate to ensure no significant loss of track finding efficiency. The algorithm was implemented into the Athena framework for online seed pre-selection, and could be potentially adapted for the ITk geometry for the Run 4 of the HL-LHC.

Experiments at the CERN High-Luminosity Large Hadron Collider (HL-LHC) will produce hundreds of petabytes of data per year. Efficient processing of this dataset represents a significant human resource and technical challenge. Today, ATLAS data processing applications run in multi-threaded mode, using Intel TBB for thread management, which allows efficient utilization of all available CPU cores on the computing resources. However, modern HPC systems and high-end computing clusters are increasingly based on heterogeneous architectures, usually a combination of CPU and accelerators (e.g., GPU, FPGA). It is increasingly desirable to utilize High Performance Computing facilities for ATLAS data processing, and this work explores the possibility of using HPX as a basis for a next-generation scheduler for Athena running on HPCs.

Searches for new physics at the LHC set exclusion limits in multi-dimensional parameter spaces of various theories. Typically, these are presented as 1- or 2-dimensional parameter scans; however, the relevant theory’s parameter space is usually of a higher dimension. As a result only a subspace is covered, which is due to the exponential computing requirements of simulations for scattering processes of interest. An Active Learning approach using a Gaussian Process is presented to address this limitation. Compared to the usual grid scan, this iterative procedure reduces the number of points in parameter space for which exclusion limits need to be determined. The Active Learning procedure is applied to a dark matter search performed by the ATLAS experiment, extending its interpretation from a 2 to a 4-dimensional parameter space while keeping the computational effort at a low level.

The LHC High Energy Physics experiments will face challenging trigger requirements in the next decade. The increase of the peak of luminosity to 5-7.5 × 10 –34 cm –2 s –1 will push the major experiments such as ATLAS to exploit the online tracking for their inner detector to achieve 10 kHz of events from 1 MHz. In this paper is presented the proposal for a tuned Hough Transform algorithm implemented on high-end FPGA, versatile and adaptable to different tracking situations. The platform developed allows to study different dataset, including ATLAS simulations, using a software simulating the firmware. Xilinx FPGA have been selected for this implementation, exploiting currently the VC709 commercial board and its PCI Express Generation 3 technology. The system provides the features to possibly process a 200 pile up event of ATLAS Run4 in the order of 10 μs averagely, with the possibility to run two events at a time. Preliminary tests showed a tracking efficiency > 95 % for single muon. The project plans to be proposed for the Event Filter TDAQ ATLAS Upgrade of Phase-II.

Abstract The inclusive top quark pair ($$t\\bar{t}$$t t ¯ ) cross-section$$\\sigma _{t\\bar{t}}$$σ t t ¯ has been measured in proton–proton collisions at$$\\sqrt{s}=13\\,\\text {TeV}$$s = 13 TeV , using$$140\\,{\\text {fb}^{-1}} $$140 fb - 1 of data collected by the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge$$e\\mu $$e μ pair and b-tagged jets, the cross-section is measured to be:$$\\begin{aligned} \\sigma _{t\\bar{t}} & = 829.3\\pm 1.3\\,\\mathrm {(stat)}\\ \\pm 8.0\\,\\mathrm {(syst)}\\ \\pm 7.3\\,\\mathrm {(lumi)}\\ \\\ & \\quad \\pm 1.9\\,\\mathrm {(beam)}\\,\\textrm{pb}, \\end{aligned}$$σ t t ¯ = 829.3 ± 1.3 ( stat ) ± 8.0 ( syst ) ± 7.3 ( lumi ) ± 1.9 ( beam ) pb , where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the proton beam energy, giving a total uncertainty of 1.3%. The result is used to determine the top quark pole mass via the dependence of the predicted cross-section on$${m_{t}^\\textrm{pole}}$$m t pole , giving$${m_{t}^\\textrm{pole}}=172.8^{+1.5}_{-1.7}$$m t pole = 172 . 8 - 1.7 + 1.5  $$\\text {GeV}$$GeV . The same event sample is used to measure absolute and normalised differential cross-sections for the$$t\\bar{t} \\rightarrow e\\mu \\nu \\bar{\\nu }b\\bar{b} $$t t ¯ → e μ ν ν ¯ b b ¯ process as a function of single-lepton and dilepton kinematic variables. Complementary measurements of$$e\\mu b\\bar{b} $$e μ b b ¯ production, treating both$$t\\bar{t}$$t t ¯ and Wt events as signal, are also provided. Both sets of differential cross-sections are compared to the predictions of various Monte Carlo event generators, demonstrating that the state-of-the-art generators Powheg MiNNLO and Powheg bb4l describe the data better than Powheg hvq.

Abstract The angular distributions of Drell–Yan lepton pairs provide sensitive probes of the underlying dynamics of quantum chromodynamics (QCD) effects in vector-boson production. This paper presents for the first time the measurement of the full set of angular coefficients together with the differential cross-section as a function of the transverse momentum of the W boson, in the full phase space of the decay leptons. The measurements are performed separately for theW⁻W - andW⁺W + channels. The analysis uses proton–proton collision data recorded by the ATLAS experiment at the Large Hadron Collider in 2017 and 2018, during special low-luminosity runs with a reduced number of interactions per bunch crossings (pile-up). The data correspond to an integrated luminosity of 338 pb⁻¹- 1 at a centre-of-mass energy of√s̅ = 13s = 13  TeV. The low pile-up environment provides excellent experimental conditions for high-precision measurements of W-boson production. All results agree with theoretical predictions incorporating finite-order QCD corrections up to orderα _(S)²α S 2 .

Abstract This paper reports the observation of electroweak diboson (WW/WZ/ZZ) production in association with a high-mass dijet system, in which final states with one boson decaying leptonically and the other boson decaying hadronically are studied. The hadronically decaying W/Z boson is reconstructed as either two small-radius jets or one large-radius jet with jet substructure requirements. The data analyzed correspond to an integrated luminosity of$$140 \\ \\text {fb}^{-1}$$140 fb - 1 of proton–proton collisions at a center-of-mass energy of$$\\sqrt{s}=13$$s = 13 TeV collected with the ATLAS detector during the 2015-2018 data taking at the Large Hadron Collider. The electroweak production of WW/WZ/ZZ in association with two jets is observed in a phase space dominated by vector-boson scattering with a significance of$$7.4\\sigma $$7.4 σ (expected$$6.1\\sigma $$6.1 σ ) and the signal strength is determined to be$$1.28^{+0.23}_{-0.21}$$1 . 28 - 0.21 + 0.23 . The corresponding production cross section in a fiducial phase space is measured in addition. The signal strengths of both electroweak and QCD associated diboson productions are furthermore measured in a two-dimensional fit, the result of which agrees with the Standard Model prediction. The data are interpreted in the context of a dimension-8 effective field theory to probe anomalous quartic gauge couplings resulting in the first set of exclusion limits on the Wilson coefficients in the semileptonic channel reported by the ATLAS Collaboration. The observed limits for the S02, T0 and M0 operators are$$(-\\,3.96< f_{S02} / \\Lambda ^4 < 3.96)$$( - 3.96 < f S 02 / Λ 4 < 3.96 )  TeV$$^{-4}$$- 4 ,$$(-\\,0.25< f_{T0} / \\Lambda ^4 < 0.22)$$( - 0.25 < f T 0 / Λ 4 < 0.22 )  TeV$$^{-4}$$- 4 ,$$(-\\,1.26< f_{M0} / \\Lambda ^4 < 1.25)$$( - 1.26 < f M 0 / Λ 4 < 1.25 )  TeV$$^{-4}$$- 4 .

Abstract A model-agnostic search for Beyond the Standard Model physics is presented, targeting final states with at least four light leptons (electrons or muons). The search regions are separated by event topology and unsupervised machine learning is used to identify anomalous events in the full 140 fb⁻¹- 1 of proton–proton collision data collected with the ATLAS detector during Run 2. No significant excess above the Standard Model background expectation is observed. Model-agnostic limits are presented in each topology, along with limits on several benchmark models including vector-like leptons, wino-like charginos and neutralinos, or smuons. Limits are set on the flavourful vector-like lepton model for the first time.