| 1. |
- Aad, G., et al.
(author)
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Studies of the performance of the ATLAS detector using cosmic-ray muons
- 2011
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 71:3
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Journal article (peer-reviewed)abstract
- Muons from cosmic-ray interactions in the atmosphere provide a high-statistics source of particles that can be used to study the performance and calibration of the ATLAS detector. Cosmic-ray muons can penetrate to the cavern and deposit energy in all detector subsystems. Such events have played an important role in the commissioning of the detector since the start of the installation phase in 2005 and were particularly important for understanding the detector performance in the time prior to the arrival of the first LHC beams. Global cosmic-ray runs were undertaken in both 2008 and 2009 and these data have been used through to the early phases of collision data-taking as a tool for calibration, alignment and detector monitoring. These large datasets have also been used for detector performance studies, including investigations that rely on the combined performance of different subsystems. This paper presents the results of performance studies related to combined tracking, lepton identification and the reconstruction of jets and missing transverse energy. Results are compared to expectations based on a cosmic-ray event generator and a full simulation of the detector response.
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| 2. |
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| 3. |
- Aad, G., et al.
(author)
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Commissioning of the ATLAS Muon Spectrometer with cosmic rays
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:3, s. 875-916
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Journal article (peer-reviewed)abstract
- The ATLAS detector at the Large Hadron Collider has collected several hundred million cosmic ray events during 2008 and 2009. These data were used to commission the Muon Spectrometer and to study the performance of the trigger and tracking chambers, their alignment, the detector control system, the data acquisition and the analysis programs. We present the performance in the relevant parameters that determine the quality of the muon measurement. We discuss the single element efficiency, resolution and noise rates, the calibration method of the detector response and of the alignment system, the track reconstruction efficiency and the momentum measurement. The results show that the detector is close to the design performance and that the Muon Spectrometer is ready to detect muons produced in high energy proton-proton collisions.
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| 5. |
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| 6. |
- Aad, G., et al.
(author)
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Readiness of the ATLAS Tile Calorimeter for LHC collisions
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:4, s. 1193-1236
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Journal article (peer-reviewed)abstract
- The Tile hadronic calorimeter of the ATLAS detector has undergone extensive testing in the experimental hall since its installation in late 2005. The readout, control and calibration systems have been fully operational since 2007 and the detector has successfully collected data from the LHC single beams in 2008 and first collisions in 2009. This paper gives an overview of the Tile Calorimeter performance as measured using random triggers, calibration data, data from cosmic ray muons and single beam data. The detector operation status, noise characteristics and performance of the calibration systems are presented, as well as the validation of the timing and energy calibration carried out with minimum ionising cosmic ray muons data. The calibration systems' precision is well below the design value of 1%. The determination of the global energy scale was performed with an uncertainty of 4%.
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| 7. |
- Aad, G., et al.
(author)
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The ATLAS Inner Detector commissioning and calibration
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:3, s. 787-821
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Journal article (peer-reviewed)abstract
- The ATLAS Inner Detector is a composite tracking system consisting of silicon pixels, silicon strips and straw tubes in a 2 T magnetic field. Its installation was completed in August 2008 and the detector took part in data-taking with single LHC beams and cosmic rays. The initial detector operation, hardware commissioning and in-situ calibrations are described. Tracking performance has been measured with 7.6 million cosmic-ray events, collected using a tracking trigger and reconstructed with modular pattern-recognition and fitting software. The intrinsic hit efficiency and tracking trigger efficiencies are close to 100%. Lorentz angle measurements for both electrons and holes, specific energy-loss calibration and transition radiation turn-on measurements have been performed. Different alignment techniques have been used to reconstruct the detector geometry. After the initial alignment, a transverse impact parameter resolution of 22.1 +/- 0.9 mu m and a relative momentum resolution sigma (p) /p=(4.83 +/- 0.16)x10(-4) GeV(-1)xp (T) have been measured for high momentum tracks.
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| 8. |
- Aad, G., et al.
(author)
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The ATLAS Simulation Infrastructure
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:3, s. 823-874
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Journal article (peer-reviewed)abstract
- The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.
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| 9. |
- Morris, John A, et al.
(author)
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An atlas of genetic influences on osteoporosis in humans and mice.
- 2019
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 51, s. 258-266
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Journal article (peer-reviewed)abstract
- Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR)=58, P=1 × 10-75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P<0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development.
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| 10. |
- Brown, A. G. A., et al.
(author)
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Gaia Data Release 1 Summary of the astrometric, photometric, and survey properties
- 2016
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 595
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Journal article (peer-reviewed)abstract
- Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues - a realisation of the Tycho-Gaia Astrometric Solution (TGAS) - and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of similar to 3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr(-1) for the proper motions. A systematic component of similar to 0.3 mas should be added to the parallax uncertainties. For the subset of similar to 94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr(-1). For the secondary astrometric data set, the typical uncertainty of the positions is similar to 10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to similar to 0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.
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