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- Aad, G., et al.
(författare)
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A search for heavy Higgs bosons decaying into vector bosons in same-sign two-lepton final states in pp collisions at √s=13 TeV with the ATLAS detector
- 2023
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Ingår i: Journal of High Energy Physics (JHEP). - : Springer Nature. - 1126-6708 .- 1029-8479. ; 2023:7
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Tidskriftsartikel (refereegranskat)abstract
- A search for heavy Higgs bosons produced in association with a vector boson and decaying into a pair of vector bosons is performed in final states with two leptons (electrons or muons) of the same electric charge, missing transverse momentum and jets. A data sample of proton–proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb−1. The observed data are in agreement with Standard Model background expectations. The results are interpreted using higher-dimensional operators in an effective field theory. Upper limits on the production cross-section are calculated at 95% confidence level as a function of the heavy Higgs boson’s mass and coupling strengths to vector bosons. Limits are set in the Higgs boson mass range from 300 to 1500 GeV, and depend on the assumed couplings. The highest excluded mass for a heavy Higgs boson with the coupling combinations explored is 900 GeV. Limits on coupling strengths are also provided.
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- Aad, G, et al.
(författare)
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Alignment of the ATLAS Inner Detector in Run 2
- 2020
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Ingår i: European Physical Journal C. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 80:12
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Tidskriftsartikel (refereegranskat)abstract
- The performance of the ATLAS Inner Detector alignment has been studied using pp collision data at s=13TeV collected by the ATLAS experiment during Run 2 (2015–2018) of the Large Hadron Collider (LHC). The goal of the detector alignment is to determine the detector geometry as accurately as possible and correct for time-dependent movements. The Inner Detector alignment is based on the minimization of track-hit residuals in a sequence of hierarchical levels, from global mechanical assembly structures to local sensors. Subsequent levels have increasing numbers of degrees of freedom; in total there are almost 750,000. The alignment determines detector geometry on both short and long timescales, where short timescales describe movements within an LHC fill. The performance and possible track parameter biases originating from systematic detector deformations are evaluated. Momentum biases are studied using resonances decaying to muons or to electrons. The residual sagitta bias and momentum scale bias after alignment are reduced to less than ∼0.1TeV-1 and 0.9 × 10 - 3, respectively. Impact parameter biases are also evaluated using tracks within jets. © 2020, The Author(s).
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| 6. |
- Aad, G., et al.
(författare)
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Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle X in hadronic final states using √s=13 TeV pp collisions with the ATLAS detector
- 2023
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Ingår i: Physical Review D. - : AMER PHYSICAL SOC. - 2470-0010 .- 2470-0029. ; 108:5
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Tidskriftsartikel (refereegranskat)abstract
- A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at √s=13 TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139 fb−1. The search targets the high Y-mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into , and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section for signals with mY between 1.5 and 6 TeV and mX between 65 and 3000 GeV.
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| 7. |
- Aad, G, et al.
(författare)
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ATLAS data quality operations and performance for 2015-2018 data-taking
- 2020
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Ingår i: Journal of Instrumentation. - : Institute of Physics Publishing (IOPP). - 1748-0221. ; 15:4
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Tidskriftsartikel (refereegranskat)abstract
- The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately 100 kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015-2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at s=13 TeV certified for physics analysis.
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| 8. |
- Aad, G., et al.
(författare)
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ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset
- 2023
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Ingår i: European Physical Journal C. - : Institute for Ionics. - 1434-6044 .- 1434-6052. ; 83:7
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Tidskriftsartikel (refereegranskat)abstract
- The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of √s=13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
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