| 1. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 2. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 3. |
- Aad, G., et al.
(författare)
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- 2011
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swepub:Mat__t
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| 4. |
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| 5. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 6. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 7. |
- Abate, E., et al.
(författare)
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Combined performance tests before installation of the ATLAS Semiconductor and Transition Radiation Tracking Detectors
- 2008
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- The ATLAS (A Toroidal LHC ApparatuS) Inner Detector provides charged particle tracking in the centre of the ATLAS experiment at the Large Hadron Collider (LHC). The Inner Detector consists of three subdetectors: the Pixel Detector, the Semiconductor Tracker (SCT), and the Transition Radiation Tracker (TRT). This paper summarizes the tests that were carried out at the final stage of SCT+TRT integration prior to their installation in ATLAS. The combined operation and performance of the SCT and TRT barrel and endcap detectors was investigated through a series of noise tests, and by recording the tracks of cosmic rays. This was a crucial test of hardware and software of the combined tracker detector systems. The results of noise and cross-talk tests on the SCT and TRT in their final assembled configuration, using final readout and supply hardware and software, are reported. The reconstruction and analysis of the recorded cosmic tracks allowed testing of the offline analysis chain and verification of basic tracker performance parameters, such as efficiency and spatial resolution, in combined operation before installation.
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| 8. |
- Abat, E., et al.
(författare)
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The ATLAS TRT end-cap detectors
- 2008
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- The ATLAS TRT end-cap is a tracking drift chamber using 245,760 individual tubular drift tubes. It is a part of the TRT tracker which consist of the barrel and two end-caps. The TRT end-caps cover the forward and backward pseudo-rapidity region 1.0 < vertical bar eta vertical bar < 2.0, while the TRT barrel central eta region vertical bar eta vertical bar < 1.0. The TRT system provides a combination of continuous tracking with many measurements in individual drift tubes ( or straws) and of electron identification based on transition radiation from fibers or foils interleaved between the straws themselves. Along with other two sub-systems, namely the Pixel detector and Semi Conductor Tracker (SCT), the TRT constitutes the ATLAS Inner Detector. This paper describes the recently completed and installed TRT end-cap detectors, their design, assembly, integration and the acceptance tests applied during the construction.
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| 9. |
- Sherratt, K., et al.
(författare)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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| 10. |
- Abat, E., et al.
(författare)
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The ATLAS Transition Radiation Tracker (TRT) proportional drift tube: design and performance
- 2008
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 3:2
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Tidskriftsartikel (refereegranskat)abstract
- A straw proportional counter is the basic element of the ATLAS Transition Radiation Tracker (TRT). Its detailed properties as well as the main properties of a few TRT operating gas mixtures are described. Particular attention is paid to straw tube performance in high radiation conditions and to its operational stability.
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