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  1. Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes. 
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  2. Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy. 
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  3. Abstract The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range $$10 more » « less
  4. Abstract This paper presents a measurement of the electroweak production of two jets in association with a $$Z\gamma $$ Z γ pair, with the Z boson decaying into two neutrinos. It also presents a search for invisible or partially invisible decays of a Higgs boson with a mass of 125  $$\text {GeV}$$ GeV produced through vector-boson fusion with a photon in the final state. These results use data from LHC proton–proton collisions at $$\sqrt{s}$$ s = 13  $$\text {TeV}$$ TeV collected with the ATLAS detector and corresponding to an integrated luminosity of 139  $$\hbox {fb}^{-1}$$ fb - 1 . The event signature, shared by all benchmark processes considered for the measurements and searches, is characterized by a significant amount of unbalanced transverse momentum and a photon in the final state, in addition to a pair of forward jets. Electroweak $$Z\gamma $$ Z γ production in association with two jets is observed in this final state with a significance of 5.2 (5.1 expected) standard deviations. The measured fiducial cross-section for this process is $$1.31\pm 0.29$$ 1.31 ± 0.29  fb. An observed (expected) upper limit of 0.37 ( $$0.34^{+0.15}_{-0.10}$$ 0 . 34 - 0.10 + 0.15 ) at 95% confidence level is set on the branching ratio of a 125  $$\text {GeV}$$ GeV Higgs boson to invisible particles, assuming the Standard Model production cross-section. The signature is also interpreted in the context of decays of a Higgs boson into a photon and a dark photon. An observed (expected) 95% CL upper limit on the branching ratio for this decay is set at 0.018 ( $$0.017^{+0.007}_{-0.005}$$ 0 . 017 - 0.005 + 0.007 ), assuming the Standard Model production cross-section for a 125  $$\text {GeV}$$ GeV Higgs boson. 
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  5. Abstract During LHC Run 2 (2015–2018) the ATLAS Level-1 topological trigger allowed efficient data-taking by the ATLAS experiment at luminosities up to 2.1 $$\times $$ × 10 $$^{34}$$ 34  cm $$^{-2}$$ - 2 s $$^{-1}$$ - 1 , which exceeds the design value by a factor of two. The system was installed in 2016 and operated in 2017 and 2018. It uses Field Programmable Gate Array processors to select interesting events by placing kinematic and angular requirements on electromagnetic clusters, jets, $$\tau $$ τ -leptons, muons and the missing transverse energy. It allowed to significantly improve the background event rejection and signal event acceptance, in particular for Higgs and B -physics processes. 
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  6. Abstract A search for R-parity-violating supersymmetry in final states characterized by high jet multiplicity, at least one isolated light lepton and either zero or at least three b -tagged jets is presented. The search uses $${139}\,{\text {fb}^{-1}}$$ 139 fb - 1 of $$\sqrt{s} = {13}\hbox { TeV}$$ s = 13 TeV proton–proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the b -tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine-learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine-learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass. 
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  7. Abstract This paper presents a search for dark matter in the context of a two-Higgs-doublet model together with an additional pseudoscalar mediator, a , which decays into the dark-matter particles. Processes where the pseudoscalar mediator is produced in association with a single top quark in the 2HDM+ a model are explored for the first time at the LHC. Several final states which include either one or two charged leptons (electrons or muons) and a significant amount of missing transverse momentum are considered. The analysis is based on proton–proton collision data collected with the ATLAS experiment at $$\sqrt{s} = 13$$ s = 13  TeV during LHC Run 2 (2015–2018), corresponding to an integrated luminosity of 139  $$\hbox {fb}^{-1}$$ fb - 1 . No significant excess above the Standard Model predictions is found. The results are expressed as 95% confidence-level limits on the parameters of the signal models considered. 
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  8. Abstract The production cross-section of a top quark in association with a W boson is measured using proton–proton collisions at $$\sqrt{s} = 8\,\text {TeV}$$ s = 8 TeV . The dataset corresponds to an integrated luminosity of $$20.2\,\text {fb}^{-1}$$ 20.2 fb - 1 , and was collected in 2012 by the ATLAS detector at the Large Hadron Collider at CERN. The analysis is performed in the single-lepton channel. Events are selected by requiring one isolated lepton (electron or muon) and at least three jets. A neural network is trained to separate the tW signal from the dominant $$t{\bar{t}}$$ t t ¯ background. The cross-section is extracted from a binned profile maximum-likelihood fit to a two-dimensional discriminant built from the neural-network output and the invariant mass of the hadronically decaying W boson. The measured cross-section is $$\sigma _{tW} = 26 \pm 7\,\text {pb}$$ σ tW = 26 ± 7 pb , in good agreement with the Standard Model expectation. 
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  9. Abstract Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb $$^{-1}$$ - 1 of proton–proton collision data with a centre-of-mass energy of $$\sqrt{s}=13$$ s = 13   $${\text {Te}}{\text {V}}$$ TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti- $$k_t$$ k t jet algorithm with radius parameter $$R=0.4$$ R = 0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ( $$|\eta |<1.2$$ | η | < 1.2 ) vary from 1% for a wide range of high- $$p_{{\text {T}}}$$ p T jets ( $$2502.5~{\text {Te}}{\text {V}}$$ > 2.5 TeV ). The relative jet energy resolution is measured and ranges from ( $$24 \pm 1.5$$ 24 ± 1.5 )% at 20  $${\text {Ge}}{\text {V}}$$ GeV to ( $$6 \pm 0.5$$ 6 ± 0.5 )% at 300  $${\text {Ge}}{\text {V}}$$ GeV . 
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  10. null (Ed.)
    Abstract Jet substructure has provided new opportunities for searches and measurements at the LHC, and has seen continuous development since the optimization of the large-radius jet definition used by ATLAS was performed during Run 1. A range of new inputs to jet reconstruction, pile-up mitigation techniques and jet grooming algorithms motivate an optimisation of large-radius jet reconstruction for ATLAS. In this paper, this optimisation procedure is presented, and the performance of a wide range of large-radius jet definitions is compared. The relative performance of these jet definitions is assessed using metrics such as their pileup stability, ability to identify hadronically decaying W bosons and top quarks with large transverse momenta. A new type of jet input object, called a ‘unified flow object’ is introduced which combines calorimeter- and inner-detector-based signals in order to achieve optimal performance across a wide kinematic range. Large-radius jet definitions are identified which significantly improve on the current ATLAS baseline definition, and their modelling is studied using pp collisions recorded by the ATLAS detector at $$\sqrt{s}=13~\text {TeV}$$ s = 13 TeV during 2017. 
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