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The quest to discover supersymmetry at the ATLAS experiment

The search for supersymmetry with the ATLAS experiment at the CERN Large Hadron Collider intensified after the discovery of the Higgs boson in 2012. The search programme expanded in both breadth and depth, profiting from the increased integrated luminosity and higher centre-of-mass energy for the collision data collected between 2015 and 2018, and gaining new sensitivity to unexplored areas of supersymmetry parameter space through the use of novel experimental signatures and innovative analysis techniques. This report summarises the supersymmetry searches at ATLAS using up to 140 fb −1 of pp collisions at $\sqrt{s}$ = 13 TeV, including the limits set on the production of gluinos, squarks, and electroweakinos for scenarios with or without R-parity conservation, and including models where some of the supersymmetric particles are long-lived.

Koeck, Daniela↗

A global atlas of soil viruses reveals unexplored biodiversity and potential biogeochemical impacts

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities and interactions with the soil microbiome remains limited. Here we present the Global Soil Virus Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and composed of 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units. Rarefaction curves from the Global Soil Virus Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared viral operational taxonomic units across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents an extensive characterization of soil viral diversity and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

59 BASIC BIOLOGICAL SCIENCES↗

A detailed map of Higgs boson interactions by the ATLAS experiment ten years after the discovery

The standard model of particle physics describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles. The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN. Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons—the carriers of the strong, electromagnetic and weak forces—are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (τ)) are well measured and indications of interactions with a second-generation particle (muons, μ) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Updates to the ATLAS Data Carousel Project

The High Luminosity upgrade to the LHC (HL-LHC) is expected to deliver scientific data at the multi-exabyte scale. In order to address this unprecedented data storage challenge, the ATLAS experiment launched the Data Carousel project in 2018. Data Carousel is a tape-driven workflow whereby bulk production campaigns with input data resident on tape are executed by staging and promptly processing a sliding window to disk buffer such that only a small fraction of inputs are pinned on disk at any one time. Data Carousel is now in production for ATLAS in Run3. In this paper, we provide updates on recent Data Carousel R&D projects, including data-on-demand and tape smart writing. Data-on-demand removes from disk data that has not been accessed for a predefined period, when users request them, they will be either staged from tape or recreated by following the original production steps. Tape smart writing employs intelligent algorithms for file placement on tape in order to retrieve data back more efficiently, which is our long term strategy to achieve optimal tape usage in Data Carousel.

42 ENGINEERING↗

Multithreading ATLAS offline software: A retrospective

For Run 3, ATLAS redesigned its offline software, Athena, so that the main workflows run completely multithreaded. The resulting substantial reduction in the overall memory requirements allows for better use of machines with many cores. This note will discuss the performance achieved by the multithreaded reconstruction, the process of migrating the large ATLAS code base, and tools and techniques that were useful in debugging threading-related problems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs

A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. This has been developed for a specific type of analysis using ATLAS data, one popularly referred to as Simulation-Based Inference (SBI). The JAX library is used for the parts of the workflow to compute gradients as well as accelerate program execution using just-in-time compilation, which becomes essential in a full SBI analysis and can also offer significant speed-ups in more traditional types of analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The ATLAS Workflow Management System Evolution in the LHC Run3 and towards the High-Luminosity LHC era

The ATLAS experiment has 18+ years of experience using workload management systems to deploy and develop workflows to process and to simulate data on the distributed computing infrastructure. Simulation, processing and analysis of LHC experiment data require the coordinated work of heterogeneous computing resources. In particular, the ATLAS experiment utilizes the resources of 250 computing centers worldwide, the power of supercomputing centres, and national, academic and commercial cloud computing resources. In this contribution, we present new techniques for cost-effectively improving efficiency introduced in workflow management system software. The evolution from a mesh framework to new types of computing facilities such as cloud and HPCs is described, as well as new types of production and analysis workflows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS

In recent years, advanced and complex analysis workflows have gained increasing importance in the ATLAS experiment at CERN, one of the large scientific experiments at LHC. Support for such workflows has allowed users to exploit remote computing resources and service providers distributed worldwide, overcoming limitations on local resources and services. The spectrum of computing options keeps increasing across the Worldwide LHC Computing Grid (WLCG), volunteer computing, high-performance computing, commercial clouds, and emerging service levels like Platform-as-a-Service (PaaS), Container-as-a-Service (CaaS) and Function-as-a-Service (FaaS), each one providing new advantages and constraints. Users can significantly benefit from these providers, but at the same time, it is cumbersome to deal with multiple providers, even in a single analysis workflow with fine-grained requirements coming from their applications’ nature and characteristics. In this paper, we will first highlight issues in geographically-distributed heterogeneous computing, such as the insulation of users from the complexities of dealing with remote providers, smart workload routing, complex resource provisioning, seamless execution of advanced workflows, workflow description, pseudointeractive analysis, and integration of PaaS, CaaS, and FaaS providers. We will also outline solutions developed in ATLAS with the Production and Distributed Analysis (PanDA) system and future challenges for LHC Run4.

97 MATHEMATICS AND COMPUTING↗

Integration of RNTuple in ATLAS Athena

After using ROOT’s TTree I/O subsystem for over two decades and storing more than an exabyte of compressed High Energy Physics (HEP) data, advances in technology have motivated a complete redesign, RNTuple, which breaks backward-compatibility to take better advantage of these storage options. The RNTuple I/O subsystem has been designed to address performance bottlenecks and other shortcomings of TTree. Specifically, RNTuple comes with an updated, more compact binary data format that can be stored both in ROOT files and natively in object stores. It is designed for modern storage hardware (e.g. high-throughput low-latency NVMe SSDs), and provides robust and easy to use interfaces. The binary format of RNTuple is scheduled to become production grade in 2024, and recently has become mature enough to start exploring the integration into software used by HEP experiments. In this contribution, we discuss the developments to support the features as required by the ATLAS analysis Event Data Model (EDM) in RNTuple, which will enable its integration into the Athena software framework. With these developments in place, we evaluate the performance of the current most recent versions of RNTuple-based ATLAS data sets and compare this to that of TTree.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The git based ATLAS data acquisition configuration service in LHC Run 3

The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and data acquisition system composed of many computing nodes, networks, and hardware modules. Its configuration service is used to provide descriptions of control, monitoring, diagnostic, recovery, dataflow and data quality configurations, interconnections, and parameters for modules, chips, and channels of various online systems, detectors, and the whole ATLAS experiment. Those descriptions have historically been stored in more than one thousand interconnected XML files, which are updated by various experts many times per day. Maintaining error-free and consistent sets of such files and providing reliable and fast access to current and historical configurations is a major challenge. This paper gives details of the configuration service upgrade on the modern Git version control system backend for LHC Run 3 and its exploitation experience. It may be interesting for developers using human-readable file formats, where consistency of the files, performance, access control, traceability of modifications, and effective archiving are key requirements.

Soloviev, Igor [Univ. of California, Irvine, CA (U↗

Sputter sample preparation for ion beam delivery of radium-223 at ATLAS

A radium-223 ion beam was delivered to an experiment from the electron cyclotron resonance ion source, ECR2, at the Argonne Tandem Linac Accelerator System (ATLAS). Here, the radium-223 material was in a nitrate salt form within a vial, prior to being converted to a usable sputter sample. The sputter sample was produced using a new sample preparation method, where the radium nitrate was dissolved into a solution and pipetted onto pressed aluminum powder. This sample was then allowed to dry, distributing the radium-223 material throughout the sputter sample. Ion source operation using the radium sputter sample is described with the operating parameters listed. The intensity and energy requirements for this ion beam were 1 × 10 6 particles/s and 1.07 GeV, respectively. Because the intensity is relatively low compared to most experiments at ATLAS, previously developed accelerator mass spectrometry methods were used Scott et al. to avoid the need for tuning of the low-intensity beam of interest. Handling of the radium material, as well as loading and unloading of the sputter sample from ECR2, required collaboration with Health Physics. Procedures were used and dry runs were carried out before, during, and after the experiment to ensure the safety of the workers. The processes used and lessons learned are described within.

07 ISOTOPE AND RADIATION SOURCES↗

Technology progress and clean vehicle policies on fleet turnover and equity: insights from household vehicle fleet micro-simulations with $\text{ATLAS}$

This paper documents the design and application of ATLAS (Automobile and Technology Lifecycle-Based ASsignment), a comprehensive household vehicle transaction and technology adoption micro-simulator in the San Francisco Bay Area. ATLAS evolves the fleet mix of individual households by simulating the vehicle transaction and choice decisions in response to co-evolving demographics, land use, and vehicle technology simulations. While most existing literature has focused on the aggregate clean vehicle uptake, this paper differentiates distributional effects and decomposes the underlying mechanisms across heterogeneous sub-populations of households. Using scenarios and sensitivity simulations that vary vehicle technology and policy assumptions, we find that Zero Emission Vehicles (ZEVs) penetrate into higher income groups at a faster rate than into lower income groups, which is intuitive and aligns with expectations. Interestingly, the relative income disparity in ZEV ownership shrinks over time across all scenarios, with a ZEV mandate coupled with declining battery cost leading to the greatest reduction in disparity of ZEV ownership by 2050. Federal, state, and local financial incentives influence the redistribution of ZEV uptake across income groups and contribute to narrowing income disparity. Vehicle transaction frequency and new versus used market dynamics are found to be important factors contributing to the income disparity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance and calibration of quark/gluon-jet taggers using 140 fb -1 of pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using $\sqrt{s}$ = 13 TeV proton–proton collision data with an integrated luminosity of 140 fb -1 collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Operation and performance of the ATLAS semiconductor tracker in LHC Run 2

The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules. During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb ₋1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector. Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2. It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%. Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules.

47 OTHER INSTRUMENTATION↗

Comparison of measurement and simulation of ATLAS cavern radiation background

Sixteen Medipix2 pixel detector based (MPX) devices were operated at various positions within the ATLAS detector and cavern continuously from early 2008 up to 2013. In addition to photons, each MPX detector is capable to detect charged particles, and neutrons as it is covered with a mask of converter materials dividing its area into regions sensitive to thermal or fast neutrons. The MPX detector network was effectively used for real-time measurements of the spectral characteristics and composition of complex radiation fields in ATLAS. This article reports comparison of the results of measurements performed with MPX detectors during the LHC operation period in 2010 and 2011 with Monte Carlo simulations results from the FLUGG and GCALOR codes. For the purpose of this comparison, the MPX detectors were operated in tracking mode with low threshold (8–10 keV) allowing one to distinguish among particle categories based on the recognition of track patterns left by the particles in the MPX sensitive layer. The comparison of measurements with simulations shows that the agreement between measured and simulated data is satisfactory in most cases within a factor of two.

47 OTHER INSTRUMENTATION↗

Pre-production results from ATLAS ITk Strip Sensors Quality Assurance Testchip

The production of strip sensors within the framework of the ATLAS Inner Tracker (ITk) development is a process which requires continuous evaluation during the full production period (about 4 years). Such an evaluation is divided into two different parts: Quality Control (QC), which focuses on the final product (the actual sensors) and tries to identify possible defects once the fabrication is completed, and Quality Assurance (QA), which aims to prevent deviations in the manufacturing process and uses specifically-designed test structures. The initial sensor pre-production consists of 5% (1041 sensors) of the total number of sensors expected during production. As part of pre-production, the collaboration has measured key parameters from miniature strip sensors (minis), monitor diodes (MD8), and the ATLAS Testchip, before and after irradiation. In this contribution we focus on the analysis of the results of the MD8 and the Testchip. All parameters have been obtained from the test structures (MD8, bias resistors, interdigitated structures, field oxide capacitors, coupling capacitors, punch-through protection structures and cross-bridge resistors) measured at the different test sites (KEK/Tsukuba, Birmingham, Toronto, Ljubljana, Valencia, Carleton, Prague, CNM-Barcelona). The results are compared to predefined pre- and post-irradiation specifications for each tested parameter.

47 OTHER INSTRUMENTATION↗

Specifications and pre-production of n + -in-p large-format strip sensors fabricated in 6-inch silicon wafers, ATLAS18, for the Inner Tracker of the ATLAS Detector for High-Luminosity Large Hadron Collider

Abstract The ATLAS experiment is constructing new all-silicon inner tracking system for HL-LHC. The strip detectors cover the radial extent of 40 to 100 cm. A new approach is adopted to use p-type silicon material, making the readout in n + -strips, so-called n + -in-p sensors. This allows for enhanced radiation tolerance against an order of magnitude higher particle fluence compared to the LHC. To cope with varying hit rates and occupancies as a function of radial distance, there are two barrel sensor types, the short strips (SS) for the inner 2 and the long strips (LS) for the outer 2 barrel cylinders, respectively. The barrel sensors exhibit a square, 9.8 × 9.8 cm 2 , geometry, the largest possible sensor area from a 6-inch wafer. The strips are laid out in parallel with a strip pitch of 75.5 μm and 4 or 2 rows of strip segments. The strips are AC-coupled and biased via polysilicon resistors. The endcap sensors employ a “stereo-annulus” geometry exhibiting a skewed-trapezoid shapes with circular edges. They are designed in 6 unique shapes, R0 to R5, corresponding to progressively increasing radial extents and which allows them to fit within the petal geometry and the 6-inch wafer maximally. The strips are in fan-out geometry with an in-built rotation angle, with a mean pitch of approximately 75 μm and 4 or 2 rows of strip segments. The eight sensor types are labeled as ATLAS18xx where xx stands for SS, LS, and R0 to R5. According to the mechanical and electrical specifications, CAD files for wafer processing were laid out, following the successful designs of prototype barrel and endcap sensors, together with a number of optimizations. A pre-production was carried out prior to the full production of the wafers. The quality of the sensors is reviewed and judged excellent through the test results carried out by vendor. These sensors are used for establishing acceptance procedures and to evaluate their performance in the ATLAS collaboration, and subsequently for pre-production of strip modules and stave and petal structures.

Instruments & Instrumentation↗

Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC

Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to 'fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.

47 OTHER INSTRUMENTATION↗