ATLAS Detector Research Articles

Setups for eliminating static charge of the ATLAS18 strip sensors

Construction of the new all-silicon Inner Tracker (ITk), developed by the ATLAS collaboration to beable to track charged particles produced at the High-Luminosity LHC, started in 2020 and is expected tocontinue till 2028. The ITk detector will include 18,000 highly segmented and radiation hard n+-in-psilicon strip sensors (ATLAS18), which are being manufactured by Hamamatsu Photonics. Mechanical and electrical characteristics of produced sensors are measured upon their delivery at several institutes participating in a complex Quality Control (QC) program. The QC tests performed on each individual sensor check the overall integrity and quality of the sensor.During the QC testing of ATLAS18 strip sensors, an increased number of sensors thatfailed the electrical tests was observed. In particular, IV measurements indicated an early breakdown,while large areas containing several tens or hundreds of neighbouring strips with low interstrip isolationwere identified by the Full strip tests, and leakage current instabilities were measured in a long-term leakage current stability setup. Moreover, a high surface electrostatic charge reaching a level of several hundreds of volts per inch was measured on a large number of sensors and on the plastic sheets, whichmechanically protect these sensors in their paper envelopes. Accumulated data indicates a clearcorrelation between observed electrical failures and the sensor charge-up.To mitigate the above-described issues, the QC testing sites significantly modified the sensor handlingprocedures and introduced sensor recovery techniques based on irradiation of the sensor surface with UVlight or application of intensive flows of ionized gas. In this presentation, we will describe the setupsimplemented by the QC testing sites to treat silicon strip sensors affected by static charge andevaluate the effectiveness of these setups in terms of improvement of the sensor performance.

SMEFT at NNLO+PS: Vh production

In the context of the Standard Model effective field theory (SMEFT) the next-to-next-to-leading (NNLO) QCD corrections to the Higgsstrahlungs (Vh) processes in hadronic collisions are calculated and matched to a parton shower (PS). NNLO+PS precision is achieved for the complete sets of SMEFT operators that describe the interactions between the Higgs and two vector bosons and the couplings of the Higgs, a W or a Z boson, and light fermions. A POWHEG-BOX implementation of the computed NNLO SMEFT corrections is provided that allows for a realistic exclusive description of Vh production at the level of hadronic events. This feature makes it an essential tool for future Higgs characterisation studies by the ATLAS and CMS collaborations. Utilising our new Monte Carlo code the numerical impact of NNLO+PS corrections on the kinematic distributions in pp → Zh → ℓ+ℓ−h production is explored, employing well-motivated SMEFT benchmark scenarios.

Isolating semi-leptonic H→WW∗\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H\\rightarrow WW^{*}$$\\end{document}decays for Bell inequality tests

We present a method for identifying H→WW∗→ℓνjj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H\\rightarrow WW^* \\rightarrow \\ell \ u j j$$\\end{document} events in the presence of large Standard Model backgrounds and illustrate how this decay mode may be applied to the study of Bell-type Inequalities. Our findings reveal the feasibility of complete reconstruction of such Higgs decays and the efficacy of our suggested combination of selection criteria in effectively mitigating the otherwise overwhelming backgrounds. Our approach is based on a combination of bottom and charm tagging, alongside innovative reconstruction techniques. A realistic simulation based on publicly available object identification, reconstruction, and tagging efficiencies from the ATLAS experiment is used to explore the potential sensitivity to violations of the Collins-Gisin-Linden-Massar-Popescu (CGLMP) inequality in existing and expected future data collected at the Large Hadron Collider (LHC). It is found that, the proposed method provides a powerful means of distinguishing the Higgs decay mode from the background, allowing us to achieve an expectation of approximately 3σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma $$\\end{document} significance in detecting violations of these inequalities with 300 fb-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {fb}^{-1}$$\\end{document} of data, soon-to-be collected by the LHC.

Light-by-light scattering in ultraperipheral collisions of heavy ions at two future detectors

We discuss possible future studies of photon-photon (light-by-light) scattering using a planned FoCal and ALICE 3 detectors. We include different mechanisms of γγ→γγ scattering such as double-hadronic photon fluctuations, t/u-channel neutral pion exchange or resonance excitations (γγ→R) and deexcitation (R→γγ). The broad range of (pseudo)rapidities and lower cuts on transverse momenta open a necessity to consider not only dominant box contributions but also other subleading contributions. Here we include low mass resonant R=π0, η, η′ contributions. The resonance contributions give intermediate photon transverse momenta. However, these contributions can be eliminated by imposing windows on diphoton invariant mass. We study and quantify individual box contributions (leptonic, quarkish). The electron/positron boxes dominate at low Mγγ<1 GeV diphoton invariant masses. The PbPb→PbPbγγ cross section is calculated within equivalent photon approximation in the impact parameter space. Several differential distributions are presented and discussed. We consider four different kinematic regions. We predict a cross section in the (mb-b) range for typical ALICE 3 cuts, a few orders of magnitude larger than for the current ATLAS or CMS experiments. We also consider the two-π0 background which can, in principle, be eliminated at the new kinematical range for the ALICE 3 measurements by imposing dedicated cuts on diphoton transverse momentum and/or so-called vector asymmetry. Published by the American Physical Society 2024

Differential cross-section measurements of the production of four charged leptons in association with two jets using the ATLAS detector

Differential cross-sections are measured for the production of four charged leptons in association with two jets. These measurements are sensitive to final states in which the jets are produced via the strong interaction as well as to the purely-electroweak vector boson scattering process. The analysis is performed using proton-proton collision data collected by ATLAS at sqrt{s} = 13 TeV and with an integrated luminosity of 140 fb−1. The data are corrected for the effects of detector inefficiency and resolution and are compared to state-of-the-art Monte Carlo event generator predictions. The differential cross-sections are used to search for anomalous weak-boson self-interactions that are induced by dimension-six and dimension-eight operators in Standard Model effective field theory.

A Flexible and Efficient Approach to Missing Transverse Momentum Reconstruction

Missing transverse momentum is a crucial observable for physics at hadron colliders, being the only constraint on the kinematics of “invisible” objects such as neutrinos and hypothetical dark matter particles. Computing missing transverse momentum at the highest possible precision, particularly in experiments at the energy frontier, can be a challenging procedure due to ambiguities in the distribution of energy and momentum between many reconstructed particle candidates. This paper describes a novel solution for efficiently encoding information required for the computation of missing transverse momentum given arbitrary selection criteria for the constituent reconstructed objects. Pileup suppression using information from both the calorimeter and the inner detector is an integral component of the reconstruction procedure. Energy calibration and systematic variations are naturally supported. Following this strategy, the ATLAS Collaboration has been able to optimise the use of missing transverse momentum in diverse analyses throughout Runs 2 and 3 of the Large Hadron Collider and for future analyses.

Precision measurements of B-meson decays at ATLAS

The precise measurement of the CP-violating phase ϕs, the average decay width Γs and the difference between the widths of the light and heavy mass eigenstates ΔΓs is presented in the $${B_s^0} $$ → J/ψϕ decay channel. Data of pp collisions at √s = 13 TeV are used, corresponding to 80.5 fb−1 of integrated lu-minosity collected by the ATLAS detector at the Large Hadron Collider in years 2015–2017. Results are statistically combined with the previous measurement with 19.2 fb−1 data with 7 and 8 TeV energy. The measured values are: ϕs = −0.087 ± 0.036 (stat.) ± 0.021 (syst.) Γs = 0.6703 ± 0.0014 (stat.) ± 0.0018 (syst.) ΔΓs = 0.0657 ± 0.0043 (stat.) ± 0.0037 (syst.). Moreover, a study estimating the ATLAS detector performance in measuring the CP-violating phase ϕs after the HL-LHC upgrade is presented.

Efficient Search for New Physics Using Active Learning in the ATLAS Experiment

Searches for new physics set exclusion limits in parameter spaces of typically up to 2 dimensions. However, the relevant theory parameter space is usually of a higher dimension but only a subspace is covered due to the computing time requirements of signal process simulations. An Active Learning approach is presented to address this limitation. Compared to the usual grid sampling, it reduces the number of parameter space points for which exclusion limits need to be determined. Hence it allows to extend interpretations of searches to higher dimensional parameter spaces and therefore to raise their value, e.g. via the identification of barely excluded subspaces which motivate dedicated new searches. In an iterative procedure, a Gaussian Process is fit to excluded signal cross-sections. Within the region close to the exclusion contour predicted by the Gaussian Process, Poisson disc sampling is used to determine further parameter space points for which the cross-section limits are determined. The procedure is aided by a warm-start phase based on computationally inexpensive, approximate limit estimates such as total signal cross-sections. The procedure is applied to a dark matter search on data collected by the ATLAS detector at the LHC, extending its interpretation from a 2 to a 4-dimensional parameter space while keeping the computational effort at a low level. The result is published in two formats: on one hand there is a publication of the Gaussian Process model. On the other hand, a visualization of the full 4-dimensional contour is presented as a collection of 2-dimensional exclusion contours where the 2 remaining parameters are chosen by the user.

The ATLAS Alarm Helper

The Detector Safety System is the last line of defence to protect the ATLAS detector against abnormal and potentially even unforeseen situations. It is designed to return the detector to a safe state based on predefined actions triggered by alarms which are triggered on their part by specific sets of conditions. Every alarm whether it results in an action taken or not is followed up by the operations team that assesses the criticality, takes countermeasures and identifies the point of failure. From experience abnormal situations can result either from faults or from side effects of planned interventions which were either not properly identified despite the mandatory planning and review or where a mistake during execution occurred. In many cases there are multiple interventions ongoing simultaneously in order to profit from shutdown periods. The rapid analysis of alarms while the incident is ongoing is often complicated due to the complexity of the ATLAS detector and its infrastructure and the large number of responsible groups and experts. A new Alarm Helper tool was designed to assist the operation team, particularly the operator in the control room responsible for infrastructure and safety (SLIMOS – Shift Leader in Matters of Safety), by providing real-time information about ongoing interventions and the possible related causes of failure. The new tool will combine historical events, documentation, and limited knowledge about ongoing interventions. It extends the Expert System which visualizes and simulates infrastructure inter-dependencies and allows to trace faults or alarms to a list of potential points of failure. The new tool also proposes which experts should be contacted in the particular circumstances.

FELIX: First operational experience with the new ATLAS readout system and perspectives for HL-LHC

The Front-End Link eXchange (FELIX) readout system is deployed as the new interface connecting detector front-end electronics with the data acquisition and Timing, Trigger and Control (TTC) systems. FELIX functions as a router between custom serial links from front-end ASICs and FPGAs to data collection and processing components via a commodity switched network. FELIX uses commodity server technology in combination with FPGA-based PCIe I/O cards. FELIX servers run a software routing platform serving data to network clients performing a number of data preparation, monitoring and control functions. This paper covers the design of FELIX as well as the first operational experience gained during the Run 3 start, including the challenges faced commissioning the system for each ATLAS sub-detector. Over the next decade, the ATLAS detector will be required to operate in an increasingly harsh collision environment and challenging data taking conditions. To maintain physics performance, the detector will undergo a series of upgrades. In particular, the readout system capabilities will be improved. The planned evolution of FELIX for High-Luminosity LHC will be described, including architectural changes and status of early integration with detector development projects.

Probing initial state effects in nuclear collisions via jet and top-quark measurements with the ATLAS detector

Proton-lead collisions at the Large Hadron Collider energies offer a unique possibility to investigate initial state effects in nuclear collisions. Thanks to its wide acceptance, ATLAS can measure several probes that can help characterise these effects over a wide kinematic range. By analyzing the centrality dependence of dijet production, it is possible to investigate the suppression of dijet events in central collisions compared to peripheral ones and correlate it to the kinematic of the parton-parton scattering, accessible via the measurement of both jets in the final state. Also, the first measurement of the inclusive crosssection for top-quark pair production in dilepton and lepton+jet decay modes is reported. This process is sensitive to effects at high Bjorken-x values, which are hard to access experimentally using other available probes, and thus provides complementary information on the behavior of nuclear parton densities. In 2016, the ATLAS experiment collected 165 nb−1 of proton-lead collisions at a center-of-mass energy of 8.16 TeV per nucleon pair. In this article, new measurements of the centrality dependence of dijet production and the observation of top-quark pair production using this dataset are presented.

Novel fully-heterogeneous GNN designs for track reconstruction at the HL-LHC

Data from the LHC detectors are not easily represented using regular data structures. These detectors are comprised of several species of subdetectors and therefore produce heterogeneous data. LHC detectors are highly granular by design so that nearby particles may be distinguished. As a consequence, LHC data are sparse, in that many detector channels are not active during a given collision event. Graphs offer a flexible and efficient alternative to rectilinear data structures for representing LHC data. Accordingly, graph-based machine learning algorithms are becoming increasingly popular for a large number of LHC physics tasks [1, 2]. This popularity, and the corresponding potential for substantial increase in physics output, are illustrated on the cover of a recent issue [3] of the CERN Courier magazine. The graphs used in almost all practical applications at the LHC so far are homogeneous, i.e. each node is assigned the same features, and each edge is assigned the same features. In other words, the power of graphs to represent sparse data has been exploited in applications for the LHC, but the potential of graphs to represent heterogeneous data has not. The pink graph on the cover of the CERN Courier [3] can be seen as an illustration of this limitation: all nodes are pink, regardless of their position in the detector. We present novel fully-heterogeneous GNN designs and apply them to simulated data from a tracking detector that resembles the trackers that will be used at the HL-LHC. It contains a pixel subsystem that provides 3D hits and a strip subsystem that provides 2D hits. We present a new design which solves the degraded performance observed in the strip detector in the first GNNbased tracking studies presented by the ATLAS Collaboration [4].

Transverse momentum fluctuation in ultra-central Pb+Pb collision at the LHC

The ATLAS collaboration has recently observed that the variance of the transverse momentum per particle ([pt]), when measured as a function of the collision multiplicity (Nch) in Pb+Pb collisions, decreases by a factor 2 for the largest values of Nch, corresponding to ultra-central collisions. We show that this phenomenon is naturally explained by invoking impact parameter (b) fluctuations, which contribute to the variance, and gradually disappear in ultracentral collisions. It implies that Nch and [pt] are strongly correlated at fixed b, which is explained by the local thermalization of the QGP medium.

Accounting and monitoring tools enhancement for Run 3 in the ATLAS distributed computing

The ATLAS experiment at the LHC utilizes complex multicomponent distributed systems for processing (PanDA WMS) and managing (Rucio) data. The complexity of the relationships between components, the amount of data being processed and the continuous development of new functionalities of the critical systems are the main challenges to consider when creating monitoring and accounting tools able to adapt to this dynamic environment in a short time. To overcome these challenges, ATLAS uses the unified monitoring infrastructure (UMA) provided by CERN-IT since 2018, which accumulates information from distributed data sources and then makes it available for different ATLAS distributed computing user groups. The information is displayed using Grafana dashboards. Based on the information provided, they can be grouped as “data transfers”, “site accounting”, “jobs accounting” and so on. These monitoring tools are used daily by ATLAS members to spot and fix issues. In addition, LHC Run 3 required the implementation of significant changes in the monitoring and accounting infrastructure to collect and process data collected by ATLAS during the LHC run. This paper describes the recent enhancements to the UMA-based monitoring and accounting dashboards.

Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS

Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS

A grid site reimagined: Building a fully cloud-native ATLAS Tier 2 on Kubernetes

The University of Victoria (UVic) operates an Infrastructure-asa-Service scientific cloud for Canadian researchers, and a Tier 2 site for the ATLAS experiment at CERN as part of the Worldwide LHC Computing Grid (WLCG). At first, these were two distinctly separate systems, but over time we have taken steps to migrate the Tier 2 grid services to the cloud. This process has been significantly facilitated by basing our approach on Kubernetes, a versatile, robust, and very widely adopted automation platform for orchestrating containerized applications. Previous work exploited the batch capabilities of Kubernetes to run grid computing jobs and replace the conventional grid computing elements by interfacing with the Harvester workload management system of the ATLAS experiment. However, the required functionality of a Tier 2 site encompasses more than just batch computing. Likewise, the capabilities of Kubernetes extend far beyond running batch jobs, and include for example scheduling recurring tasks and hosting long-running externally-accessible services in a resilient way. We are now undertaking the more complex and challenging endeavour of adapting and migrating all remaining services of the Tier 2 site — such as APEL accounting and Squid caching proxies, and in particular the grid storage element — to cloud-native deployments on Kubernetes. We aim to enable fully comprehensive deployment of a complete ATLAS Tier 2 site on a Kubernetes cluster via Helm charts, which will benefit the community by providing a streamlined and replicable way to install and configure an ATLAS site. We also describe our experience running a high-performance self-managed Kubernetes ATLAS Tier 2 cluster at the scale of 8 000 CPU cores for the last two years, and compare with the conventional setup of grid services.

Precision Measurements of Higgs-boson Properties with the ATLAS Experiment

Precision Measurements of Higgs-boson Properties with the ATLAS Experiment

Optimization of opportunistic utilization of the ATLAS high-level trigger farm for LHC Run 3

Optimization of opportunistic utilization of the ATLAS high-level trigger farm for LHC Run 3

Towards a new conditions data infrastructure in ATLAS

Towards a new conditions data infrastructure in ATLAS

Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing

The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D projects on Amazon Web Services and Google Cloud as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures. The proof of concept phases have concluded with the cloud-native, vendoragnostic integration with the experiment’s data and workload management frameworks. Google Cloud has been used to evaluate elastic batch computing, ramping up ephemeral clusters of up to O(100k) cores to process tasks requiring quick turnaround. Amazon Web Services has been exploited for the successful physics validation of the Athena simulation software on ARM processors. We have also set up an interactive facility for physics analysis allowing endusers to spin up private, on-demand clusters for parallel computing with up to 4 000 cores, or run GPU enabled notebooks and jobs for machine learning applications. The success of the proof of concept phases has led to the extension of the Google Cloud project, where ATLAS will study the total cost of ownership of a production cloud site during 15 months with 10k cores on average, fully integrated with distributed grid computing resources and continue the R&D projects.