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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Radiation Tolerant Electronics and Digital Processing for the Phase-I Trigger Readout Upgrade of the ATLAS Liquid Argon Calorimeters

The high luminosities of L > 10{sup 34} cm{sup -2}s{sup -1} at the Large Hadron Collider (LHC) at CERN produce an intense radiation environment that the detectors and their electronics must withstand. The ATLAS detector is a multi-purpose apparatus constructed to explore the new particle physics regime opened by the LHC. Of the many decay particles observed by the ATLAS detector, the energy of the created electrons and photons is measured by a sampling calorimeter technique that uses Liquid Argon (LAr) as its active medium. The front end (FE) electronic readout of the ATLAS LAr calorimeter located on the detector itself consists of a combined analog and digital processing system. In order to exploit the higher luminosity while keeping the same trigger bandwidth of 100 kHz, higher transverse granularity, higher resolution and longitudinal shower shape information will be provided from the LAr calorimeter to the Level-l trigger processors. New trigger readout electronics have been designed for this purpose, which will withstand the radiation dose levels expected for an integrated luminosity of 3000 fb{sup -1} during the high luminosity LHC (HL-LHC), which is well above the original LHC design qualifications. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Micromegas chambers for the experiment ATLAS at the LHC (A Brief Overview)

The increase in luminosity and energy of the Large hadron collider (LHC) in the next upgrade (Phase-1) in 2018–2019 will lead to a significant increase in radiation load on the ATLAS detector, primarily in the areas close to the interaction point of the LHC proton beams. One of these regions is the Small Wheel of the ATLAS Muon Spectrometer. It is planned to be replaced with the New Small Wheel that will have Micromegas chambers as main coordinate detectors. The paper gives an overview of all existing types of Micromegas detectors with special focus on the Micromegas chambers for the ATLAS detector upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Study of performance of the ATLAS transition radiation tracker in run 1 of the LHC: Tracking characteristics

The ATLAS Transition Radiation Tracker (TRT) contains more than 350000 large straw tubes and it is the outermost of the three subsystems of the ATLAS Inner Detector (ID). The TRT contributes substantially to the ATLAS ID resolution for the tracks of high-energy particles, providing excellent particle identification capabilities and electron-pion separation. Basic performance parameters of the TRT related to its tracking function are described in this paper. The data used in this study were collected during the first period of the Large Hadron Collider (LHC) operation in 2012 with a proton collision energy of 8 TeV. The tracking performance of the TRT has been studied in the case of operating with a Xe-based gas mixture and as a function of the straw occupancy. Special attention was paid to investigation of tracking parameters inside hadronic jets. The experimental data and simulation are in reasonable agreement, even within the dense cores of the most energetic jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Operational experience and R&D results using the Google Cloud for High-Energy Physics in the ATLAS experiment

The ATLAS experiment at CERN relies on a Worldwide Distributed Computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and operation, elasticity and availability of diverse infrastructures. Here this paper examines the seamless integration of cloud computing services as a conventional Grid site within the ATLAS workflow management and data management systems, while also offering new setups for interactive, parallel analysis. It underscores pivotal results that enhance the on-site computing model and outlines several R&D projects that have benefited from large-scale, elastic resource provisioning models. Furthermore, this study discusses the impact of cloud-enabled R&D projects in three domains: accelerators and AI/ML, ARM CPUs and columnar data analysis techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2019

The Global Fire Atlas of Individual Fire Size, Duration, Speed and Direction

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

global fire atlas↗
DOE OSTI2015

Radiation Tolerant Electronics and Digital Processing for the Phase-1 Read-out Upgrade of the ATLAS Liquid Argon Calorimeters

The ATLAS Liquid Argon calorimeters are designed and built to study proton-proton collisions produced at the LHC at centre-of-mass energies up to 14 TeV. Liquid argon (LAr) sampling calorimeters are employed for all electromagnetic calorimetry in the pseudorapidity region |η|<3.2, and for hadronic calorimetry in the region from |η|=1.5 to |η|=4.9. Although the nominal LHC experimental programme is still in progress, an upgrade of the read-out electronics is being launched to cope with luminosities of up to 3x10{sup 34} cm{sup -2}s{sup -1}, which are beyond the original design by a factor of 3. An improved spatial granularity of the trigger primitives is therefore proposed in order to improve the identification performance for trigger signatures, like electrons, photons, tau leptons, jets, total and missing energy, at high background rejection rates. For the upgrade Phase-1 in 2018, new LAr Trigger Digitizer Boards (LTDB) are being designed to receive higher granularity signals, digitize them on detector and send them via fast optical links to a new LAr digital processing system (LDPS). The LDPS applies a digital filtering and identifies significant energy depositions in each trigger channel. The refined trigger primitives are then transmitted to the first level trigger system to extract improved trigger signatures. The read-out of the trigger signals will process 34000 so-called Super Cells at every LHC bunch-crossing at a frequency of 40 MHz. The new LTDB on-detector electronics is designed to be radiation tolerant in order to be operated for the remaining live-time of the ATLAS detector up to a total luminosity of 3000 fb{sup -1}. For the analog-to-digital conversion (12-bit ADC at 40 MSPS), the data serialization and the fast optical link (5.44 Gb/s) custom components have been developed. They have been qualified for the expected radiation environment of a total ionization dose of 1.3 kGy and a hadron fluence of 6 x 10{sup 13} h/cm{sup 2} with energies above 20 MeV. For the digital components like the ADC, cross-sections for single event effects have been determined. This talk will present R and D results from tests of the radiation tolerant components, the fast data processing electronics and prototypes of the LTDB and LDPS boards. First experience from a Demonstrator setup will be reported, in which about 1/10 of the full Super Cell readout will be equipped with prototype versions of the LTDB and LDPS boards. The Demonstrator will be operated in parallel to the regular ATLAS trigger read-out during the upcoming LHC run. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

ATLAS Run 2 searches for electroweak production of supersymmetric particles interpreted within the pMSSM

A summary of the constraints from searches performed by the ATLAS collaboration for the electroweak production of charginos and neutralinos is presented. Results from eight separate ATLAS searches are considered, each using 140 fb −1 of proton-proton data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV collected at the Large Hadron Collider during its second data-taking run. The results are interpreted in the context of the 19-parameter phenomenological minimal supersymmetric standard model, where R-parity conservation is assumed and the lightest supersymmetric particle is assumed to be the lightest neutralino. Constraints from previous electroweak, flavour and dark matter related measurements are also considered. The results are presented in terms of constraints on supersymmetric particle masses and are compared with limits from simplified models. Also shown is the impact of ATLAS searches on parameters such as the dark matter relic density and the spin-dependent and spin-independent scattering cross-sections targeted by direct dark matter detection experiments. The Higgs boson and Z boson ‘funnel regions’, where a low-mass neutralino would not oversaturate the dark matter relic abundance, are almost completely excluded by the considered constraints. Example spectra for non-excluded supersymmetric models with light charginos and neutralinos are also presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A search for the decays of stopped long-lived particles at $ \sqrt{\mathrm{s}} $ = 13 TeV with the ATLAS detector

A search for long-lived particles, which have come to rest within the ATLAS detector, is presented. The subsequent decays of these particles can produce high-momentum jets, resulting in large out-of-time energy deposits in the ATLAS calorimeters. These de- cays are detected using data collected during periods in the LHC bunch structure when collisions are absent. The analysed dataset is composed of events from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy of s = 13 TeV and recorded by the ATLAS experiment during 2017 and 2018. The dataset used for this search corresponds to a total live time of 579 hours. The results of this search are used to derive lower limits on the mass of gluino R -hadrons, assuming a branching fraction $ \mathcal{B}\left(\overset{\sim }{g}\to q\overline{q}{\chi}_1^0\right) $ B g ~ → q q ¯ χ 1 0 = 100%, with masses of up to 1 . 4 TeV excluded for gluino lifetimes of 10 - 5 to 10 3 s.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Determination of the parton distribution functions of the proton from ATLAS measurements of differential W ± and Z boson production in association with jets

This article presents a new set of proton parton distribution functions, AT-LASepWZVjet20, produced in an analysis at next-to-next-to-leading order in QCD. The new data sets considered are the measurements of W + and W - boson and Z boson production in association with jets in pp collisions at $\sqrt{s}$ = 8TeV performed by the ATLAS experiment at the LHC with integrated luminosities of 20.2 fb -1 and 19.9 fb -1 , respectively. The analysis also considers the ATLAS measurements of differential W ± and Z boson production at $\sqrt{s}$ = 7TeV with an integrated luminosity of 4.6 fb -1 and deep-inelastic-scattering data from e ± p collisions at the HERA accelerator. An improved determination of the sea-quark densities at high Bjorken x is shown, while confirming a strange-quark density similar in size to the up- and down-sea-quark densities in the range x ≲ 0.02 found by previous ATLAS analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for neutral long-lived particles that decay into displaced jets in the ATLAS calorimeter in association with leptons or jets using pp collisions at $\sqrt{\textrm{s}}$ = 13 TeV

A search for neutral long-lived particles (LLPs) decaying in the ATLAS hadronic calorimeter using 140 fb -1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV delivered by the LHC is presented. The analysis is composed of three channels. The first targets pair-produced LLPs, where at least one LLP is produced with sufficiently low boost that its decay products can be resolved as separate jets. The second and third channels target LLPs respectively produced in association with a W or Z boson that decays leptonically. In each channel, different search regions target different kinematic regimes, to cover a broad range of LLP mass hypotheses and models. No excesses of events relative to the background predictions are observed. Higgs boson branching fractions to pairs of hadronically decaying neutral LLPs larger than 1% are excluded at 95% confidence level for proper decay lengths in the range of 30 cm to 4.5 m depending on the LLP mass, a factor of three improvement on previous searches in the hadronic calorimeter. The production of long-lived dark photons in association with a Z boson with cross-sections above 0.1 pb is excluded for dark photon mean proper decay lengths in the range of 20 cm to 50 m, improving previous ATLAS results by an order of magnitude. Finally, long-lived photo-phobic axion-like particle models are probed for the first time by ATLAS, with production cross-sections above 0.1 pb excluded in the 0.1 mm to 10 m range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Deep Generative Models for Fast Photon Shower Simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using GEANT4 . Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants

In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model to investigate the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Automated Segmentation of the Parotid Gland Based on Atlas Registration and Machine Learning: A Longitudinal MRI Study in Head-and-Neck Radiation Therapy

Purpose: To develop an automated magnetic resonance imaging (MRI) parotid segmentation method to monitor radiation-induced parotid gland changes in patients after head and neck radiation therapy (RT). Methods and Materials: The proposed method combines the atlas registration method, which captures the global variation of anatomy, with a machine learning technology, which captures the local statistical features, to automatically segment the parotid glands from the MRIs. The segmentation method consists of 3 major steps. First, an atlas (pre-RT MRI and manually contoured parotid gland mask) is built for each patient. A hybrid deformable image registration is used to map the pre-RT MRI to the post-RT MRI, and the transformation is applied to the pre-RT parotid volume. Second, the kernel support vector machine (SVM) is trained with the subject-specific atlas pair consisting of multiple features (intensity, gradient, and others) from the aligned pre-RT MRI and the transformed parotid volume. Third, the well-trained kernel SVM is used to differentiate the parotid from surrounding tissues in the post-RT MRIs by statistically matching multiple texture features. A longitudinal study of 15 patients undergoing head and neck RT was conducted: baseline MRI was acquired prior to RT, and the post-RT MRIs were acquired at 3-, 6-, and 12-month follow-up examinations. The resulting segmentations were compared with the physicians' manual contours. Results: Successful parotid segmentation was achieved for all 15 patients (42 post-RT MRIs). The average percentage of volume differences between the automated segmentations and those of the physicians' manual contours were 7.98% for the left parotid and 8.12% for the right parotid. The average volume overlap was 91.1% ± 1.6% for the left parotid and 90.5% ± 2.4% for the right parotid. The parotid gland volume reduction at follow-up was 25% at 3 months, 27% at 6 months, and 16% at 12 months. Conclusions: We have validated our automated parotid segmentation algorithm in a longitudinal study. This segmentation method may be useful in future studies to address radiation-induced xerostomia in head and neck radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Distribution Atlas of Proliferating Bone Marrow in Non-Small Cell Lung Cancer Patients Measured by FLT-PET/CT Imaging, With Potential Applicability in Radiation Therapy Planning

Purpose: Proliferating bone marrow is exquisitely sensitive to ionizing radiation. Knowledge of its distribution could improve radiation therapy planning to minimize unnecessary marrow exposure and avoid consequential prolonged myelosuppression. [18F]-Fluoro-3-deoxy-3-L-fluorothymidine (FLT)–positron emission tomography (PET) is a novel imaging modality that provides detailed quantitative images of proliferating tissues, including bone marrow. We used FLT-PET imaging in cancer patients to produce an atlas of marrow distribution with potential clinical utility. Methods and Materials: The FLT-PET and fused CT scans of eligible patients with non-small cell lung cancer (no distant metastases, no prior cytotoxic exposure, no hematologic disorders) were reviewed. The proportions of skeletal FLT activity in 10 predefined bony regions were determined and compared according to age, sex, and recent smoking status. Results: Fifty-one patients were studied: 67% male; median age 68 (range, 31-87) years; 8% never smokers; 70% no smoking in the preceding 3 months. Significant differences in marrow distribution occurred between sex and age groups. No effect was detected from smoking in the preceding 3 months. Using the mean percentages of FLT uptake per body region, we created an atlas of the distribution of functional bone marrow in 4 subgroups defined by sex and age. Conclusions: This atlas has potential utility for estimating the distribution of active marrow in adult cancer patients to guide radiation therapy planning. However, because of interindividual variation it should be used with caution when radiation therapy risks ablating large proportions of active marrow; in such cases, individual FLT-PET scans may be required.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Forward-backward multiplicity correlations in pp, p+Pb and Pb+Pb collisions with the ATLAS detector

Two-particle pseudorapidity correlations are measured in √s NN = 2.76 TeV Pb+Pb, √s NN = 5.02 TeV p +Pb and √s = 13 TeV pp collisions [ATLAS Collaboration, ATLAS-CONF-2015-051; ATLAS-CONF-2015-020]. Correlation function is measured using charged particles in the pseudorapidity range |η|<2.4 with transverse momentum p T >0.2 GeV, and it is measured as a function of event multiplicity, defined by number of charged particles with |η|<2.5 and p T >0.4 GeV. The correlation function is decomposed into a short-range component (SRC) and a long-range component (LRC). The SRC differs significantly between the opposite-charge pairs and same-charge pairs, and between the three collision systems at similar multiplicity. The LRC is described approximately by 1 + n1n2 in all collision systems over the full multiplicity range. The values of are consistent between the opposite-charge and same-charge pairs, and are similar for the three collision systems at similar multiplicity. The values of and the magnitude of the SRC both follow a power-law dependence on the event multiplicity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Characterising the Higgs boson with ATLAS data from the LHC Run-2

The Higgs boson was discovered by the ATLAS and CMS Collaborations in 2012 using data from Run 1 of the Large Hadron Collider (2010 2012). In Run 2 (2015 2018), about 140 fb -1 of proton–proton collisions at a centre-of-mass energy of 13 TeV were collected by the ATLAS experiment. This review presents the most important Run 2 results obtained by the ATLAS Collaboration regarding the properties of the Higgs boson and its interactions with other particles. The performed studies significantly enhance the understanding of the Higgs boson, while hunting for deviations from the predictions of the Standard Model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

ATLAS Data Carousel

The ATLAS experiment at CERN's LHC stores detector and simulation data in raw and derived data formats across more than 150 Grid sites world-wide, currently in total about 200PB on disk and 250PB on tape. Data have different access characteristics due to various computational workflows, and can be accessed from different media, such as remote I/O, disk cache on hard disk drives or SSDs. Also, larger data centers provide the majority of offline storage capability via tape systems. For the High-Luminosity LHC (HL-LHC), the estimated data storage requirements are several factors bigger than the present forecast of available resources, based on a flat budget assumption. On the computing side, ATLAS Distributed Computing was very successful in the last years with high performance and high throughput computing integration and in using opportunistic computing resources for the Monte Carlo simulation. On the other hand, equivalent opportunistic storage does not exist. ATLAS started the "Data Carousel" project to increase the usage of less expensive storage, i.e. tapes or even commercial storage, so it is not limited to tape technologies exclusively. Data Carousel orchestrates data processing between workload management, data management, and storage services with the bulk data resident on offline storage. The processing is executed by staging and promptly processing a sliding window of inputs onto faster buffer storage, such that only a small percentage of input data are available at any one time. With this project, we aim to demonstrate that this is the natural way to dramatically reduce our storage cost. The first phase of the project was started in the fall of 2018 and was related to I/O tests of the sites archiving systems. Phase II now requires a tight integration of the workload and data management systems. Additionally, the Data Carousel studies the feasibility to run multiple computing workflows from tape. The project is progressing very well and the results presented in this document will be used before the LHC Run 3.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Rucio beyond ATLAS: experiences from Belle II, CMS, DUNE, EISCAT3D, LIGO/VIRGO, SKA, XENON

For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. These locations do not necessarily coincide with the places where data is produced nor where data is stored, analysed by researchers, or archived for safe long-term storage. To fulfil these needs, the data management system Rucio has been developed to allow the high-energy physics experiment ATLAS at LHC to manage its large volumes of data in an efficient and scalable way. But ATLAS is not alone, and several diverse scientific projects have started evaluating, adopting, and adapting the Rucio system for their own needs. As the Rucio community has grown, many improvements have been introduced, customisations have been added, and many bugs have been fixed. Additionally, new dataflows have been investigated and operational experiences have been documented. In this article we collect and compare the common successes, pitfalls, and oddities that arose in the evaluation efforts of multiple diverse experiments, and compare them with the ATLAS experience. This includes the high-energy physics experiments Belle II and CMS, the neutrino experiment DUNE, the scattering radar experiment EISCAT3D, the gravitational wave observatories LIGO and VIRGO, the SKA radio telescope, and the dark matter search experiment XENON.

Lassnig, Mario↗